2025

• Wang, C., Chan, A., Fu, X., Ghazanfar, S., Kim, J., Patrick, E., Yang, J. (2025). Benchmarking the translational potential of spatial gene expression prediction from histology. Nature Communications, 16(1), Article 1544 - 1-Article 1544 - 17. [More Information]
• Wang, W., Yu, C., Ahn, E., Pathan, S., Negishi, K., Kim, J. (2025). TQGDNet: Coronary artery calcium deposit detection on computed tomography. Computerized Medical Imaging and Graphics, 121, 102503. [More Information]

2024

• Fu, X., Lin, Y., Lin, D., Mechtersheimer, D., Wang, C., Ameen, F., Ghazanfar, S., Patrick, E., Kim, J., Yang, J. (2024). BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data. Nature Communications, 15(Article 509), 1-17. [More Information]
• Dong, J., Qian, T., Jiang, Y., Bi, L., Kim, J., Wang, L., Xu, X. (2024). ClarityDiffuseNet: Enhancing fundus image quality under black shadows with diffusion model-based research. Pattern Recognition Letters, 186, 279-285. [More Information]
• Bi, L., Fu, X., Liu, Q., Song, S., Feng, D., Fulham, M., Kim, J. (2024). Co-Learning Multi-Modality PET-CT Features via a Cascaded CNN-Transformer Network. IEEE Transactions on Radiation and Plasma Medical Sciences, , 1-1. [More Information]
• Qian, B., Xu, X., He, X., Sheng, B., Chen, H., Xu, Y., Wen, Y., Li, H., Xie, Y., Feng, D., Kim, J., et al (2024). Deep contour attention learning for scleral deformation from OCT images. The Visual Computer. [More Information]
• Ali, S., Wang, X., Li, P., Li, H., Yang, P., Jung, Y., Qin, J., Kim, J., Sheng, B. (2024). EGDNet: an efficient glomerular detection network for multiple anomalous pathological feature in glomerulonephritis. The Visual Computer. [More Information]
• Zhou, Y., Li, H., Liu, J., Kong, Z., Huang, T., Ahn, E., Lv, Z., Kim, J., Feng, D. (2024). Explicit Abnormality Extraction for Unsupervised Motion Artifact Reduction in Magnetic Resonance Imaging. IEEE Journal of Biomedical and Health Informatics, , 1-12. [More Information]
• Qian, B., Xie, J., Liu, S., Xing, G., Silva-Rodríguez, J., Kobbi, R., Li, P., Chen, T., Bi, L., Kim, J., et al (2024). HRDC challenge: a public benchmark for hypertension and hypertensive retinopathy classification from fundus images. The Visual Computer. [More Information]
• Bi, L., Buehner, U., Fu, X., Williamson, T., Choong, P., Kim, J. (2024). Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images. Computer Methods and Programs in Biomedicine, 243, 107875. [More Information]
• Huang, Z., Li, B., Cheng, Y., Kim, J. (2024). Odontogenic cystic lesion segmentation on cone-beam CT using an auto-adapting multi-scaled UNet. Frontiers in Oncology, 14. [More Information]
• Liu, J., Li, H., Huang, T., Ahn, E., Han, K., Razi, A., Xiang, W., Kim, J., Feng, D. (2024). Unsupervised Representation Learning for 3-Dimensional Magnetic Resonance Imaging Super-Resolution with Degradation Adaptation. IEEE Transactions on Artificial Intelligence, , 1-14. [More Information]

2023

• Wang, W., Ahn, E., Feng, D., Kim, J. (2023). A Review of Predictive and Contrastive Self-supervised Learning for Medical Images. Machine Intelligence Research, 20(4), 483-513. [More Information]
• Ding, W., Ding, Q., Chen, K., Zhang, M., Lv, L., Feng, D., Bi, L., Kim, J., Huang, Q. (2023). A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging. IEEE Transactions on Medical Imaging, , 1-1. [More Information]
• Ali, S., Wang, X., Li, P., Jung, Y., Bi, L., Kim, J., Chen, Y., Feng, D., Magnenat Thalmann, N., Wang, J., et al (2023). A systematic review: Virtual-reality-based techniques for human exercises and health improvement. Frontiers in Public Health, 11. [More Information]
• An, H., Kim, J., Sheng, B., Li, P., Jung, Y. (2023). A transfer function optimization using visual saliency for region of interest-based direct volume rendering. Displays, 80, 102531. [More Information]
• Xia, T., Fu, X., Fulham, M., Wang, Y., Feng, D., Kim, J. (2023). CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. Journal of Digital Imaging, 36(6), 2356-2366. [More Information]
• Masood, S., Ali, S., Wang, X., Masood, A., Li, P., Li, H., Jung, Y., Sheng, B., Kim, J. (2023). Deep choroid layer segmentation using hybrid features extraction from OCT images. The Visual Computer. [More Information]
• Fu, X., Patrick, E., Yang, J., Feng, D., Kim, J. (2023). Deep multimodal graph-based network for survival prediction from highly multiplexed images and patient variables. Computers in Biology and Medicine, 154. [More Information]
• Naseem, U., Khushi, M., Dunn, A., Kim, J. (2023). K-PathVQA: Knowledge-Aware Multimodal Representation for Pathology Visual Question Answering. IEEE Journal of Biomedical and Health Informatics. [More Information]
• Gu, B., Meng, M., Xu, M., Feng, D., Bi, L., Kim, J., Song, S. (2023). Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma. European Journal of Nuclear Medicine and Molecular Imaging, 50(13), 3996-4009. [More Information]
• Cai, Y., Liu, N., Huang, R., Sud, K., Kim, J. (2023). Predicting Remote Monitoring Patients' Non-compliance Behavior Through App-mediated Communications. 56th Annual Hawaii International Conference on System Sciences (HICSS 2023), Hawaii, United States: University of Hawaii. [More Information]
• Kalbas, Y., Jung, H., Ricklin, J., Jin, G., Li, M., Rauer, T., Dehghani, S., Navab, N., Kim, J., Pape, H., et al (2023). Remote Interactive Surgery Platform (RISP): Proof of Concept for an Augmented-Reality-Based Platform for Surgical Telementoring. Journal of Imaging, 9(3). [More Information]
• Naseem, U., Kim, J., Khushi, M., Dunn, A. (2023). Robust Identification of Figurative Language in Personal Health Mentions on Twitter. IEEE Transactions on Artificial Intelligence, 4(2), 362-372. [More Information]
• Al-Jebrni, A., Ali, S., Li, H., Lin, X., Li, P., Jung, Y., Kim, J., Feng, D., Sheng, B., Jiang, L., et al (2023). SThy-Net: a feature fusion-enhanced dense-branched modules network for small thyroid nodule classification from ultrasound images. The Visual Computer, 39(8), 3675-3689. [More Information]
• Naseem, U., Khushi, M., Kim, J. (2023). Vision-Language Transformer for Interpretable Pathology Visual Question Answering. IEEE Journal of Biomedical and Health Informatics, 27(4), 1681-1690. [More Information]

2022

• Zwi, S., Isautier, J., Webster, A., Lambert, K., Shepherd, H., McCaffery, K., Sud, K., Saunders, J., O'Lone, E., Liu, N., Kim, J., Muscat, D., et al (2022). A feasibility study of a best practice health literacy app for Australian adults with chronic kidney disease. PEC Innovation, 1, 100047. [More Information]
• Fu, X., Bi, L., Kumar, A., Fulham, M., Kim, J. (2022). An attention-enhanced cross-task network to analyse lung nodule attributes in CT images. Pattern Recognition, 126, 108576. [More Information]
• Naseem, U., Dunn, A., Khushi, M., Kim, J. (2022). Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT. BMC Bioinformatics, 23(1), 144. [More Information]
• Wang, J., Lillia, J., Kumar, A., Bray, P., Kim, J., Burns, J., Cheng, T. (2022). Clinical applications of machine learning in predicting 3D shapes of the human body: a systematic review. BMC Bioinformatics, 23(1). [More Information]
• Yan, K., Wang, X., Kim, J., Zuo, W., Feng, D. (2022). Deep Cognitive Gate: Resembling Human Cognition for Saliency Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(9), 4776-4792. [More Information]
• Bi, L., Kim, J., Su, T., Fulham, M., Feng, D., Ning, G. (2022). Deep Multi-Scale Resemblance Network for the Sub-class Differentiation of Adrenal Masses on Computed Tomography Images. arXiv preprint, 132, 102374-1-102374-9. [More Information]
• Meng, M., Gu, B., Bi, L., Song, S., Feng, D., Kim, J. (2022). DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT. IEEE Journal of Biomedical and Health Informatics, 26(9), 4497-4507. [More Information]
• Nazir, A., Cheema, M., Sheng, B., Li, P., Li, H., Xue, G., Qin, J., Kim, J., Feng, D. (2022). ECSU-Net: An Embedded Clustering Sliced U-Net Coupled with Fusing Strategy for Efficient Intervertebral Disc Segmentation and Classification. IEEE Transactions on Image Processing, 31, 880-893. [More Information]
• Meng, M., Bi, L., Fulham, M., Feng, D., Kim, J. (2022). Enhancing medical image registration via appearance adjustment networks. NeuroImage, 259. [More Information]
• Isautier, J., Webster, A., Lambert, K., Shepherd, H., McCaffery, K., Sud, K., Kim, J., Liu, N., De La Mata, N., Raihana, S., Kelly, P., Muscat, D. (2022). Evaluation of the SUCCESS Health Literacy App for Australian Adults With Chronic Kidney Disease: Protocol for a Pragmatic Randomized Controlled Trial. JMIR Research Protocols, 11(8). [More Information]
• Ali, S., Ali, R., Sheng, B., Chen, Y., Li, H., Yang, P., Li, P., Jung, Y., Zhu, F., Lu, P., Kim, J. (2022). Experimental protocol designed to employ Nd:YAG laser surgery for anterior chamber glaucoma detection via UBM. IET Image Processing, 16(8), 2171-2179. [More Information]
• Xia, T., Kumar, A., Fulham, M., Feng, D., Wang, Y., Kim, E., Jung, Y., Kim, J. (2022). Fused feature signatures to probe tumour radiogenomics relationships. Scientific Reports, 12(1), 2173. [More Information]
• Fu, X., Bi, L., Kumar, A., Fulham, M., Kim, J. (2022). Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images. IEEE Transactions on Medical Imaging, 41(11), 3266-3277. [More Information]
• Naseem, U., Khushi, M., Kim, J., Dunn, A. (2022). Hybrid Text Representation for Explainable Suicide Risk Identification on Social Media. IEEE Transactions on Computational Social Systems. [More Information]
• Bi, L., Fulham, M., Kim, J. (2022). Hyper-fusion network for semi-automatic segmentation of skin lesions. Medical Image Analysis, 76, 102334. [More Information]
• Qiao, X., Jiang, C., Li, P., Yuan, Y., Zeng, Q., Bi, L., Song, S., Kim, J., Feng, D., Huang, Q. (2022). Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization. IEEE Journal of Biomedical and Health Informatics, 26(7), 3261-3271. [More Information]
• Meng, M., Peng, Y., Bi, L., Kim, J. (2022). Multi-task Deep Learning for Joint Tumor Segmentation and Outcome Prediction in Head and Neck Cancer. Macro In Conference. [More Information]
• Gu, B., Meng, M., Bi, L., Kim, J., Feng, D., Song, S. (2022). Prediction of 5-year progression-free survival in advanced nasopharyngeal carcinoma with pretreatment PET/CT using multi-modality deep learning-based radiomics. Frontiers in Oncology, 12. [More Information]
• Zeghoud, S., Ali, S., Ertugrul, E., Kamel, A., Sheng, B., Li, P., Chi, X., Kim, J., Mao, L. (2022). Real-time spatial normalization for dynamic gesture classification. The Visual Computer, 38(4), 1345-1357. [More Information]
• Naseem, U., Khushi, M., Kim, J., Dunn, A. (2022). RHMD: A Real-World Dataset for Health Mention Classification on Reddit. IEEE Transactions on Computational Social Systems. [More Information]
• Karambakhsh, A., Sheng, B., Li, P., Li, H., Kim, J., Jung, Y., Chen, C. (2022). SparseVoxNet: 3-D Object Recognition With Sparsely Aggregation of 3-D Dense Blocks. IEEE Transactions on Neural Networks and Learning Systems. [More Information]
• Coorey, G., Figtree, G., Fletcher, D., Snelson, V., Vernon, S., Winlaw, D., Grieve, S., McEwan, A., Yang, J., Qian, P., Orchard, J., Kim, J., Patel, S., Redfern, J., et al (2022). The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field. npj Digital Medicine, 5(1), 1-12. [More Information]

2021

• Wen, Y., Xu, Y., Liu, K., Sheng, B., Bi, L., Kim, J., He, X., Xu, X. (2021). A Classification Network for Ocular Diseases Based on Structure Feature and Visual Attention. 38th Computer Graphics International Conference, CGI 2021, Cham: Springer Nature. [More Information]
• Ahn, E., Liu, N., Parekh, T., Patel, R., Baldacchino, T., Mullavey, T., Robinson, A., Kim, J. (2021). A mobile app and dashboard for early detection of infectious disease outbreaks: development study. JMIR Public Health and Surveillance, 7(3), e14837. [More Information]
• Yan, K., Wang, X., Kim, J., Feng, D. (2021). A New Aggregation of DNN Sparse and Dense Labeling for Saliency Detection. IEEE Transactions on Cybernetics, 51(12), 5907-5920. [More Information]
• Ahn, E., Feng, D., Kim, J. (2021). A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation. 24th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021), Cham: Springer Nature. [More Information]
• Zhou, Y., Chen, Z., Sheng, B., Li, P., Kim, J., Wu, E. (2021). AFF-Dehazing: Attention-based feature fusion network for low-light image Dehazing. Computer Animation and Virtual Worlds, 32, e2011. [More Information]
• Guo, Y., Bi, L., Zhu, Z., Feng, D., Zhang, R., Wang, Q., Kim, J. (2021). Automatic left ventricular cavity segmentation via deep spatial sequential network in 4D computed tomography. Computerized Medical Imaging and Graphics, 91, 101952. [More Information]
• Naseem, U., Khushi, M., Reddy, V., Rajendran, S., Razzak, I., Kim, J. (2021). BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Naseem, U., Khushi, M., Kim, J., Dunn, A. (2021). Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU. 2021 International Joint Conference on Neural Networks, IJCNN 2021, Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Huang, Z., Xia, T., Kim, J., Zhang, L., Li, B. (2021). Combining CNN with Pathological Information for the Detection of Transmissive Lesions of Jawbones from CBCT Images. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021, Mexico: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Naseem, U., Razzak, I., Khushi, M., Eklund, P., Kim, J. (2021). COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis. IEEE Transactions on Computational Social Systems, 8(4), 976-988. [More Information]
• Wang, J., Li, Z., Ali, S., Sheng, B., Li, P., Chi, X., Kim, J., Mao, L. (2021). Dynamic Shadow Synthesis Using Silhouette Edge Optimization. 38th Computer Graphics International Conference, CGI 2021, Cham: Springer Nature. [More Information]
• Kamel, A., Sheng, B., Li, P., Kim, J., Feng, D. (2021). Efficient body motion quantification and similarity evaluation using 3-d joints skeleton coordinates. IEEE Transactions on Systems, Man and Cybernetics: Systems, 51(5), 2774-2788. [More Information]
• Meng, M., Yang, X., Bi, L., Kim, J., Xiao, S., Yu, Z. (2021). High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning. Neurocomputing, 441, 92-104. [More Information]
• Kamel, A., Sheng, B., Li, P., Kim, J., Feng, D. (2021). Hybrid Refinement-Correction Heatmaps for Human Pose Estimation. IEEE Transactions on Multimedia, 23, 1330-1342. [More Information]
• Nazir, A., Cheema, M., Sheng, B., Li, P., Kim, J., Lee, T. (2021). Living Donor-Recipient Pair Matching for Liver Transplant via Ternary Tree Representation with Cascade Incremental Learning. IEEE Transactions on Biomedical Engineering, 68(8), 2540-2551. [More Information]
• Cottle, L., Gilroy, I., Deng, K., Loudovaris, T., Thomas, H., Gill, A., Samra, J., Kebede, M., Kim, J., Thorn, P. (2021). Machine learning algorithms, applied to intact islets of langerhans, demonstrate significantly enhanced insulin staining at the capillary interface of human pancreatic β cells. Metabolites, 11(6). [More Information]
• Cheema, M., Nazir, A., Yang, P., Sheng, B., Li, P., Li, H., Wei, X., Qin, J., Kim, J., Feng, D. (2021). Modified GAN-CAED to Minimize Risk of Unintentional Liver Major Vessels Cutting by Controlled Segmentation Using CTA/SPET-CT. IEEE Transactions on Industrial Informatics, 17(12), 7991-8002. [More Information]
• Wen, Y., Xu, Y., Sheng, B., Li, P., Bi, L., Kim, J., He, X., Xu, X. (2021). Multi-Stream Fusion Network for Multi-Distortion Image Super-Resolution. 38th Computer Graphics International Conference, CGI 2021, Cham: Springer Nature. [More Information]
• Fu, X., Bi, L., Kumar, A., Fulham, M., Kim, J. (2021). Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation. IEEE Journal of Biomedical and Health Informatics, 25(9), 3507-3516. [More Information]
• Ali, R., Sheng, B., Li, P., Chen, Y., Li, H., Yang, P., Jung, Y., Kim, J., Philip Chen, C. (2021). Optic Disk and Cup Segmentation through Fuzzy Broad Learning System for Glaucoma Screening. IEEE Transactions on Industrial Informatics, 17(4), 2476-2487. [More Information]
• Peng, Y., Bi, L., Kumar, A., Fulham, M., Feng, D., Kim, J. (2021). Predicting distant metastases in soft-tissue sarcomas from PET-CT scans using constrained hierarchical multi-modality feature learning. Physics in Medicine and Biology, 66(24), 245004. [More Information]
• Bi, L., Fulham, M., Li, N., Liu, Q., Song, S., Feng, D., Kim, J. (2021). Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation. Computer Methods and Programs in Biomedicine, 203, 106043. [More Information]
• Singh, V., Sridar, P., Kim, J., Nanan, R., Poornima, N., Priya, S., Sameera, G., Chandrasekaran, S., Krishnakumar, R. (2021). Semantic Segmentation of Cerebellum in 2D Fetal Ultrasound Brain Images using Convolutional Neural Networks. IEEE Access, 9, 85864-85873. [More Information]
• Muscat, D., Lambert, K., Shepherd, H., McCaffery, K., Zwi, S., Liu, N., Sud, K., Saunders, J., O’Lone, E., Kim, J., Webster, A. (2021). Supporting patients to be involved in decisions about their health and care: Development of a best practice health literacy App for Australian adults living with Chronic Kidney Disease. Health Promotion Journal of Australia, 32(S1), 115-127. [More Information]
• Baird, C., Oytam, Y., Rahman, K., Fornasari, M., Sharma, A., Kim, J., Ahn, E., Hughes, R. (2021). The checkpoint program: Collaborative care to reduce the reliance of frequent presenters on ED. International Journal of Integrated Care, 21(2), 29. [More Information]
• Wu, X., Bi, L., Fulham, M., Feng, D., Zhou, L., Kim, J. (2021). Unsupervised brain tumor segmentation using a symmetric-driven adversarial network. Neurocomputing, 455, 242-254. [More Information]
• Guo, Y., Bi, L., Wei, D., Chen, L., Zhu, Z., Feng, D., Zhang, R., Wang, Q., Kim, J. (2021). Unsupervised Landmark Detection-Based Spatiotemporal Motion Estimation for 4-D Dynamic Medical Images. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics. [More Information]
• Zhang, R., Zhuo, L., Zhang, H., Zhang, Y., Kim, J., Yin, H., Zhao, P., Wang, Z. (2021). Vestibule segmentation from CT images with integration of multiple deep feature fusion strategies. Computerized Medical Imaging and Graphics, 89, 101872. [More Information]

2020

• Guo, Y., Bi, L., Ahn, E., Feng, D., Wang, Q., Kim, J. (2020). A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image. 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Tang, Z., Huang, R., Liu, N., Kim, J. (2020). An Investigation of Social Support Features of Digital Health Applications. 31st Australasian Conference on Information Systems (ACIS 2020), Virtual Conference: Association for Information Systems (AIS). [More Information]
• Masood, A., Sheng, B., Yang, P., Li, P., Li, H., Kim, J., Feng, D. (2020). Automated Decision Support System for Lung Cancer Detection and Classification via Enhanced RFCN with Multilayer Fusion RPN. IEEE Transactions on Industrial Informatics, 16(12), 7791-7801. [More Information]
• Kim, J., Jung, Y., Feng, D., Fulham, M. (2020). Biomedical image visualization and display technologies. In David Dagan Feng (Eds.), Biomedical Information Technology (Second Edition), (pp. 561-583). London: Academic Press. [More Information]
• Masood, A., Po, Y., Sheng, B., Li, H., Li, P., Qin, J., Lanfranchi, V., Kim, J., Feng, D. (2020). Cloud-Based Automated Clinical Decision Support System for Detection and Diagnosis of Lung Cancer in Chest CT. IEEE Journal of Translational Engineering in Health and Medicine, 8, 8922769. [More Information]
• Kumar, A., Fulham, M., Feng, D., Kim, J. (2020). Co-Learning Feature Fusion Maps from PET-CT Images of Lung Cancer. IEEE Transactions on Medical Imaging, 39(1), 204-217. [More Information]
• Cai, W., Song, Y., Kumar, A., Kim, J., Feng, D. (2020). Content-based large-scale medical image retrieval. In David Dagan Feng (Eds.), Biomedical Information Technology (Second Edition), (pp. 321-368). London: Academic Press. [More Information]
• Huang, R., Liu, N., Nicdao, M., Mikaheal, M., Baldacchino, T., Albeos, A., Petoumenos, K., Sud, K., Kim, J. (2020). Emotion sharing in remote patient monitoring of patients with chronic kidney disease. Journal of the American Medical Informatics Association, 27(2), 185-193. [More Information]
• Wang, P., Xue, G., Li, P., Kim, J., Sheng, B., Mao, L. (2020). GHand: A Graph Convolution Network for 3D Hand Pose Estimation. 37th Computer Graphics International Conference, CGI 2020, Cham: Springer Nature Switzerland. [More Information]
• Lu, P., Zhu, F., Li, P., Kim, J., Sheng, B., Mao, L. (2020). Hierarchical Rendering System Based on Viewpoint Prediction in Virtual Reality. 37th Computer Graphics International Conference, CGI 2020, Cham: Springer Nature Switzerland. [More Information]
• Cao, K., Bi, L., Feng, D., Kim, J. (2020). Improving PET-CT Image Segmentation via Deep Multi-modality Data Augmentation. 3rd International Workshop Machine Learning for Medical Image Reconstruction (MLMIR 2020), Cham: Springer Nature Switzerland. [More Information]
• Kumar, A., Bi, L., Kim, J., Feng, D. (2020). Machine learning in medical imaging. In David Dagan Feng (Eds.), Biomedical Information Technology (Second Edition), (pp. 167-196). London: Academic Press. [More Information]
• Li, X., Bi, L., Kim, J., Li, T., Li, P., Tian, Y., Sheng, B., Feng, D. (2020). Malocclusion Treatment Planning via PointNet Based Spatial Transformation Network. 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020), Cham: Springer. [More Information]
• Bi, L., Feng, D., Fulham, M., Kim, J. (2020). Multi-Label classification of multi-modality skin lesion via hyper-connected convolutional neural network. Pattern Recognition, 107, 107502. [More Information]
• Peng, Y., Bi, L., Fulham, M., Feng, D., Kim, J. (2020). Multi-modality Information Fusion for Radiomics-Based Neural Architecture Search. 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020), Cham: Springer. [More Information]
• Sridar, P., Kennedy, N., Quinton, A., Robledo, K., Kim, J., Nanan, R. (2020). Normative ultrasound data of the fetal transverse thalamic diameter derived from 18 to 22 weeks of gestation in routine second-trimester morphology examinations. Australasian Journal of Ultrasound in Medicine, 23(1), 59-65. [More Information]
• Nazir, A., Cheema, M., Sheng, B., Li, H., Li, P., Yang, P., Jung, Y., Qin, J., Kim, J., Feng, D. (2020). OFF-eNET: An Optimally Fused Fully End-to-End Network for Automatic Dense Volumetric 3D Intracranial Blood Vessels Segmentation. IEEE Transactions on Image Processing, 29, 7192-7202. [More Information]
• Liu, Q., Sun, D., Li, N., Kim, J., Feng, D., Huang, G., Wang, L., Song, S. (2020). Predicting EGFR mutation subtypes in lung adenocarcinoma using 18F-FDG PET/CT radiomic features. Translational Lung Cancer Research, 9(3), 549-562. [More Information]
• Zhang, H., Ali, R., Sheng, B., Li, P., Kim, J., Wang, J. (2020). Preserving Temporal Consistency in Videos Through Adaptive SLIC. 37th Computer Graphics International Conference, CGI 2020, Cham: Springer Nature Switzerland. [More Information]
• Chen, Z., Hu, Z., Sheng, B., Li, P., Kim, J., Wu, E. (2020). Simplified non-locally dense network for single-image dehazing. The Visual Computer, 36, 2189-2200. [More Information]
• Liu, N., Huang, R., Baldacchino, T., Sud, A., Sud, K., Khadra, M., Kim, J. (2020). Telehealth for noncritical patients with chronic diseases during the COVID-19 pandemic. Journal of Medical Internet Research, 22(8), e19493. [More Information]
• Ahn, E., Kumar, A., Fulham, M., Feng, D., Kim, J. (2020). Unsupervised Domain Adaptation to Classify Medical Images Using Zero-Bias Convolutional Auto-Encoders and Context-Based Feature Augmentation. IEEE Transactions on Medical Imaging, 39(7), 2385-2394. [More Information]
• Wu, X., Bi, L., Fulham, M., Kim, J. (2020). Unsupervised Positron Emission Tomography Tumor Segmentation via GAN based Adversarial Auto-Encoder. 16th International Conference on Control, Automation, Robotics and Vision (ICARCV 2020), Shenzhen: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2019

• Phung, S., Kumar, A., Kim, J. (2019). A deep learning technique for imputing missing healthcare data. 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019), : Springer Verlag. [More Information]
• Jung, Y., Kim, J., Bi, L., Kumar, A., Feng, D., Fulham, M. (2019). A direct volume rendering visualization approach for serial PET–CT scans that preserves anatomical consistency. International Journal of Computer Assisted Radiology and Surgery, 14(5), 733-744. [More Information]
• Yan, K., Wang, X., Kim, J., Khadra, M., Fulham, M., Feng, D. (2019). A Propagation-DNN: Deep Combination Learning of Multi-level Features for MR Prostate Segmentation. Computer Methods and Programs in Biomedicine, 170, 11-21. [More Information]
• Jung, H., Jung, Y., Feng, D., Fulham, M., Kim, J. (2019). A web-based multidisciplinary team meeting visualisation system. International Journal of Computer Assisted Radiology and Surgery, 14(12), 2221-2231. [More Information]
• Sridar, P., Kumar, A., Quinton, A., Kennedy, N., Nanan, R., Kim, J. (2019). An automated framework for large scale retrospective analysis of ultrasound images. IEEE Journal of Translational Engineering in Health and Medicine, 7, 1-9. [More Information]
• Huang, R., Nedanoski, A., Fletcher, D., Singh, N., Schmid, J., Young, P., Stow, N., Bi, L., Traini, D., Wong, E., Phillips, C., Grunstein, R., Kim, J. (2019). An automated segmentation framework for nasal computational fluid dynamics analysis in computed tomography. Computers in Biology and Medicine, 115, 1-8. [More Information]
• De Ridder, M., Klein, K., Yang, J., Yang, P., Lagopoulos, J., Hickie, I., Bennett, M., Kim, J. (2019). An Uncertainty Visual Analytics Framework for fMRI Functional Connectivity. Neuroinformatics, 17(2), 211-223. [More Information]
• Yan, K., Wang, X., Kim, J., Li, C., Feng, D., Khadra, M. (2019). Automated Prostate Image Recognition and Segmentation. In Ayman El-Baz, Gyan Pareek, Jasjit S. Suri (Eds.), Prostate Cancer Imaging: An Engineering and Clinical Perspective, (pp. 243-258). Boca Raton: CRC Press. [More Information]
• Masood, A., Sheng, B., Li, P., Yang, P., Kim, J. (2019). Automatic computer aided system for lung cancer in chest CTs using MD-RFCN combined with tri-level region proposal network. 17th IEEE International Conference on Industrial Informatics (INDIN 2019), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Jaeger, S., Klein, K., Joos, L., Zagermann, J., De Ridder, M., Kim, J., Yang, J., Pfeil, U., Reiterer, H., Schreiber, F. (2019). Challenges for brain data analysis in VR environments. 12th IEEE Pacific Visualization Symposium (PacificVis 2019), Bangkok: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Ahn, E., Kumar, A., Fulham, M., Feng, D., Kim, J. (2019). Convolutional sparse kernel network for unsupervised medical image analysis. Medical Image Analysis, 56, 140-151. [More Information]
• Sridar, P., Kumar, A., Nanan, R., Quinton, A., Kim, J., Krishnakumar, R. (2019). Decision Fusion-Based Fetal Ultrasound Image Plane Classification Using Convolutional Neural Networks. Ultrasound in Medicine and Biology, 45(5), 1259-1273. [More Information]
• Yuan, Y., Sheng, B., Li, P., Bi, L., Kim, J., Wu, E. (2019). Deep Intrinsic Image Decomposition Using Joint Parallel Learning. In Marina Gavrilova, Jian Chang, Nadia Thalmann, Eckhard Hitzer, Hiroshi Ishikawa (Eds.), Advances in Computer Graphics: 36th Computer Graphics International Conference, CGI 2019, Calgary, AB, Canada, June 17-20, 2019, Proceedings, (pp. 336-341). Cham: Springer. [More Information]
• Guo, Y., Bi, L., Kumar, A., Gao, Y., Zhang, R., Feng, D., Wang, Q., Kim, J. (2019). Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images. 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2019), Cham: Springer. [More Information]
• Peng, Y., Bi, L., Guo, Y., Feng, D., Fulham, M., Kim, J. (2019). Deep multi-modality collaborative learning for distant metastases predication in PET-CT soft-tissue sarcoma studies. 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2019), : Springer Verlag. [More Information]
• Wu, L., Liu, Y., Shi, Y., Sheng, B., Li, P., Bi, L., Kim, J. (2019). Detect glaucoma with image segmentation and transfer learning. 32nd International Conference on Computer Animation and Social Agents (CASA 2019), New York: Association for Computing Machinery (ACM). [More Information]
• Cheema, M., Nazir, A., Sheng, B., Li, P., Qin, J., Kim, J., Feng, D. (2019). Image-Aligned Dynamic Liver Reconstruction Using Intra-Operative Field of Views for Minimal Invasive Surgery. IEEE Transactions on Biomedical Engineering, 66(8), 2163-2173. [More Information]
• Bi, L., Feng, D., Fulham, M., Kim, J. (2019). Improving skin lesion segmentation via stacked adversarial learning. 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Wu, L., Liu, Y., Shi, Y., Sheng, B., Li, P., Bi, L., Kim, J. (2019). Optic disc and cup segmentation based on enhanced segnet. 32nd International Conference on Computer Animation and Social Agents (CASA 2019), New York: Association for Computing Machinery (ACM). [More Information]
• Phan, H., Kumar, A., Feng, D., Fulham, M., Kim, J. (2019). Optimizing contextual feature learning for Mitosis detection with convolutional recurrent neural networks. 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Liu, X., Bi, L., Xu, Y., Feng, D., Kim, J., Xu, X. (2019). Robust deep learning method for choroidal vessel segmentation on swept source optical coherence tomography images. Biomedical Optics Express, 10(4), 1601-1612. [More Information]
• Jin, Y., Li, P., Sheng, B., Nie, Y., Kim, J., Wu, E. (2019). SRNPD: Spatial rendering network for pencil drawing stylization. Computer Animation and Virtual Worlds, 30(3-4), 1-13. [More Information]
• Bi, L., Kim, J., Ahn, E., Kumar, A., Feng, D., Fulham, M. (2019). Step-wise integration of deep class-specific learning for dermoscopic image segmentation. Pattern Recognition, 85, 78-89. [More Information]
• Ahn, E., Kumar, A., Feng, D., Fulham, M., Kim, J. (2019). Unsupervised deep transfer feature learning for medical image classification. 16th IEEE International Symposium on Biomedical Imaging (ISBI 2019), Venice: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Phan, H., Kumar, A., Feng, D., Fulham, M., Kim, J. (2019). Unsupervised Two-Path Neural Network for Cell Event Detection and Classification Using Spatiotemporal Patterns. IEEE Transactions on Medical Imaging, 38(6), 1477-1487. [More Information]

2018

• De Ridder, M., Klein, K., Kim, J. (2018). A review and outlook on visual analytics for uncertainties in functional magnetic resonance imaging. Brain Informatics, 5(2). [More Information]
• De Ridder, M., Klein, K., Kim, J. (2018). Adapted K-Core Decomposition and Visualization for Functional Magnetic Resonance Imaging Connectivity Networks. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2018), Honolulu, Hawaii: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Lemon, C., Liu, N., Lane, A., Sud, A., Branley, J., Khadra, M., Kim, J. (2018). Changes in User Perceptions of a Telemedicine System Over Time: From Initial Implementation to Everyday Use. Telemedicine and e-Health, 24(7), 552-559. [More Information]
• Chi, Y., Bi, L., Kim, J., Feng, D., Kumar, A. (2018). Controlled Synthesis of Dermoscopic Images via a New Color Labeled Generative Style Transfer Network to Enhance Melanoma Segmentation. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2018), Honolulu, Hawaii: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yuan, Y., Li, C., Kim, J., Cai, W., Feng, D. (2018). Dense and Sparse Labeling with Multi-Dimensional Features for Saliency Detection. IEEE Transactions on Circuits and Systems for Video Technology, 28(5), 1130-1143. [More Information]
• Ahn, E., Kim, J., Rahman, K., Baldacchino, T., Baird, C. (2018). Development of a risk predictive scoring system to identify patients at risk of representation to emergency department: a retrospective population-based analysis in Australia. BMJ Open, 8(9), 1-8. [More Information]
• Bi, L., Feng, D., Kim, J. (2018). Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation. The Visual Computer, 34(6-8), 1043-1052. [More Information]
• Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2018). Feature of Interest-Based Direct Volume Rendering Using Contextual Saliency-Driven Ray Profile Analysis. Computer Graphics Forum, 37(6), 5-19. [More Information]
• Czauderna, T., Haga, J., Kim, J., Klapperstuck, M., Klein, K., Kuhlen, T., Oeltze-Jafra, S., Sommer, B., Schreiber, F. (2018). Immersive analytics applications in life and health sciences. In K. Marriott,F. Schreiber,T. Dwyer,K. Klein,N. Riche,T. Itoh,W. Stuerzlinger etc. (Eds.), Immersive Analytics, (pp. 289-330). Cham: Springer. [More Information]
• Xia, T., Kumar, A., Feng, D., Kim, J. (2018). Patch-Level Tumor Classification in Digital Histopathology Images with Domain Adapted Deep Learning. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2018), Honolulu, Hawaii: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yan, K., Zheng, C., Huang, Q., Kim, J., Feng, D., Wang, X. (2018). Prior Knowledge Driven Energy for Saliency Detection. 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yuan, Y., Li, C., Kim, J., Cai, W., Feng, D. (2018). Reversion Correction and Regularized Random Walks Ranking for Saliency Detection. IEEE Transactions on Image Processing, 27(3), 1311-1322. [More Information]
• Li, X., Sheng, B., Li, P., Kim, J., Feng, D. (2018). Voxelized Facial Reconstruction Using Deep Neural Network. Computer Graphics International (CGI 2018), New York: Association for Computing Machinery (ACM). [More Information]

2017

• De Ridder, M., Kim, J., Jing, Y., Khadra, M., Nanan, R. (2017). A systematic review on incentive-driven mobile health technology: As used in diabetes management. Journal of Telemedicine and Telecare, 23(1), 26-35. [More Information]
• Bi, L., Kim, J., Su, T., Fulham, M., Feng, D., Ning, G. (2017). Adrenal lesions detection on low-contrast CT images using fully convolutional networks with multi-scale integration. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Kim, J., Lyndon, D., Fulham, M., Feng, D. (2017). An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification. IEEE Journal of Biomedical and Health Informatics, 21(1), 31-40. [More Information]
• Bi, L., Kim, J., Kumar, A., Wen, L., Feng, D., Fulham, M. (2017). Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies. Computerized Medical Imaging and Graphics, 60, 3-10. [More Information]
• Sridar, P., Kumar, A., Li, C., Woo, J., Quinton, A., Benzie, R., Peek, M., Feng, D., Kumar, R., Nanan, R., Kim, J. (2017). Automatic Measurement of Thalamic Diameter in 2D Fetal Ultrasound Brain Images using Shape Prior Constrained Regularized Level Sets. IEEE Journal of Biomedical and Health Informatics, 21(4), 1069-1078. [More Information]
• Bi, L., Kim, J., Ahn, E., Kumar, A., Fulham, M., Feng, D. (2017). Dermoscopic Image Segmentation via Multistage Fully Convolutional Networks. IEEE Transactions on Biomedical Engineering, 64(9), 2065-2074. [More Information]
• Xu, Y., Yan, K., Kim, J., Wang, X., Li, C., Su, L., Yu, S., Xu, X., Feng, D. (2017). Dual-stage deep learning framework for pigment epithelium detachment segmentation in polypoidal choroidal vasculopathy. Biomedical Optics Express, 8(9), 4061-4076. [More Information]
• Itoh, T., Kumar, A., Klein, K., Kim, J. (2017). High-dimensional data visualization by interactive construction of low-dimensional parallel coordinate plots. Journal of Visual Languages and Computing, 43, 1-13. [More Information]
• Lyndon, D., Kumar, A., Kim, J. (2017). Neural captioning for the ImageCLEF 2017 medical image challenges. 18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017, Aachen, Germany: CEUR-WS.
• Jung, H., Kim, J., Feng, D., Fulham, M. (2017). Occlusion and Slice-based Volume Rendering Augmentation for PET-CT. IEEE Journal of Biomedical and Health Informatics, 21(4), 1005-1014. [More Information]
• Liu, N., Kim, J., Jung, Y., Arisy, A., Nicdao, M., Mikaheal, M., Baldacchino, T., Khadra, M., Sud, K. (2017). Remote Monitoring Systems for Chronic Patients on Home Hemodialysis: Field Test of a Copresence-Enhanced Design. JMIR Human Factors, 4(3), 1-12. [More Information]
• Ahn, E., Kim, J., Bi, L., Kumar, A., Li, C., Fulham, M., Feng, D. (2017). Saliency-Based Lesion Segmentation via Background Detection in Dermoscopic Images. IEEE Journal of Biomedical and Health Informatics, 21(6), 1685-1693. [More Information]
• Bi, L., Kim, J., Ahn, E., Feng, D., Fulham, M. (2017). Semi-Automatic Skin Lesion Segmentation via Fully Convolutional Networks. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Kumar, A., Fulham, M., Feng, D. (2017). Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation. The Visual Computer, 33(6-Aug), 1061-1071. [More Information]
• Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2017). Synthesis of positron emission tomography (PET) images via multi-channel generative adversarial networks (GANs). Fifth International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, Cham: Springer International Publishing. [More Information]
• De Ridder, M., Klein, K., Kim, J. (2017). TemporalTracks: Visual analytics for exploration of 4D fMRI time-series coactivation. 2017 Computer Graphics International Conference (CGI 2017), New York: Association for Computing Machinery (ACM). [More Information]

2016

• Nicdao, M., Kim, J., Baldacchino, T., Jung, Y., Mikaheal, M., Patekar, A., Sud, K. (2016). 'My Home Hemo' app - A new telehealth tool for Remote Monitoring of patents on home haemodialysis. Renal Society of Australasia Journal, 12(2), 41-47. [More Information]
• Huang, R., Li, A., Bi, L., Li, C., Young, P., King, G., Feng, D., Kim, J. (2016). A locally constrained statistical shape model for robust nasal cavity segmentation in computed tomography. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Dyer, S., Kim, J., Li, C., Leong, P., Fulham, M., Feng, D. (2016). Adapting content-based image retrieval techniques for the semantic annotation of medical images. Computerized Medical Imaging and Graphics, 49, 37-45. [More Information]
• Yan, K., Li, C., Wang, X., Li, A., Yuan, Y., Kim, J., Feng, D. (2016). Adaptive background search and foreground estimation for saliency detection via comprehensive autoencoder. 23rd IEEE International Conference on Image Processing (ICIP 2016), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Adaptive Supervoxel Patch-based Region Classification in Whole-Body PET-CT. 18th International Conference on Medical Image Computing and Computer Assisted Interventions MICCAI15 and Computational Methods for Molecular Imaging (CMMI 2015), Munich, Germany: Springer Lecture Notes in Computer Science.
• Jung, Y., Kim, J., Kumar, A., Fulham, M., Feng, D. (2016). An intuitive sketch-based transfer function design via contextual and regional labelling. 33rd Computer Graphics International Conference (CGI 2016), New York: Association for Computing Machinery (ACM). [More Information]
• Bi, L., Kim, J., Ahn, E., Feng, D., Fulham, M. (2016). Automated skin lesion segmentation via image-wise supervised learning and multi-scale superpixel based cellular automata. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Ahn, E., Feng, D., Fulham, M. (2016). Automatic melanoma detection via multi-scale lesion-biased representation and joint reverse classification. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yan, K., Li, C., Wang, X., Li, A., Yuan, Y., Feng, D., Khadra, M., Kim, J. (2016). Automatic prostate segmentation on MR images with deep network and graph model. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2016), Orlando: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yan, K., Li, C., Wang, X., Yuan, Y., Li, A., Kim, J., Li, B., Feng, D. (2016). Comprehensive autoencoder for prostate recognition on MR images. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Yuan, Y., Shi, Y., Li, C., Kim, J., Cai, W., Han, Z., Feng, D. (2016). DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations. BMC Bioinformatics, 17(Suppl 17), 243-256. [More Information]
• Jung, Y., Kim, J., Kumar, A., Feng, D., Fulham, M. (2016). Efficient visibility-driven medical image visualisation via adaptive binned visibility histogram. Computerized Medical Imaging and Graphics, 51, 40-49. [More Information]
• Jung, Y., Kim, J. (2016). Multi-modal image processing and visualization: Application to PET-CT. 33rd Computer Graphics International Conference (CGI 2016), New York: Association for Computing Machinery (ACM). [More Information]
• Kumar, A., Sridar, P., Quinton, A., Kumar, R., Feng, D., Nanan, R., Kim, J. (2016). Plane Identification in Fetal Ultrasound Images Using Saliency Maps and Convolutional Neural Networks. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Lyndon, D., Kim, J., Feng, D. (2016). Subfigure and Multi-Label Classification using a Fine-Tuned Convolutional Neural Network. CLEF 2016 Conference and Labs of the Evaluation Forum, Evora: CEUR-WS.
• Phan, H., Kumar, A., Kim, J., Feng, D. (2016). Transfer Learning of a Convolutional Neural Network for HEp-2 Cell Image Classification. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Ahn, E., Kumar, A., Kim, J., Li, C., Feng, D., Fulham, M. (2016). X-Ray Image Classification using Domain Transferred Convolutional Neural Networks and Local Sparse Spatial Pyramid. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2015

• Huang, R., Bi, L., Li, C., Jung, Y., Kim, J., Fulham, M., Feng, D. (2015). A Locally Constrained Random Walk Approach for Airway Segmentation on Low-Contrast Computed Tomography (CT) Images. 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2015), Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Nette, F., Klein, K., Fulham, M., Kim, J. (2015). A Visual Analytics Approach Using the Exploration of Multidimensional Feature Spaces for Content-Based Medical Image Retrieval. IEEE Journal of Biomedical and Health Informatics, 19(5), 1734-1746. [More Information]
• Bi, L., Kim, J., Feng, D., Fulham, M. (2015). AUTOMATED REGIONSOF INTEREST (ROIS) TRACKINGFOR PET-CT IMAGE SERIES USING CELLULAR AUTOMATA SEGMENTATION. International Journal of Computer Assisted Radiology and Surgery, 10(suppl 1), 21-22.
• Ahn, E., Bi, L., Jung, Y., Kim, J., Li, C., Fulham, M., Feng, D. (2015). Automated Saliency-Based Lesion Segmentation in Dermoscopic Images. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2015), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Wen, L., Feng, D., Fulham, M. (2015). Automated thresholded region classification using a robust feature selection method for PET-CT. 12th IEEE International Symposium on Biomedical Imaging (ISBI 2015), Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Sridar, P., Li, C., Kumar, A., Quinton, A., Benzie, R., Peek, M., Kumar, R., Kim, J., Nanan, R. (2015). Automatic measurement of thalamic diameter in 2D fetal US brain images using shape prior constrained regularized level sets. 2nd Annual Congress of the DOHaD Society of Australia and New Zealand (DOHaD 2015 Conference), Melbourne: DOHAD Society of Australia & New Zealand.
• De Ridder, M., Klein, K., Kim, J. (2015). CereVA: Visual analysis of functional brain connectivity. 6th International Conference on Information Visualization Theory and Applications (IVAPP 2015), Berlin: SciTePress.
• Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Medical Clustering. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.
• Lyndon, D., Kumar, A., Kim, J., Leong, P., Feng, D. (2015). Convolutional Neural Networks for Subfigure Classification. CLEF 2015 Conference and Labs of the Evaluation Forum, Toulouse: CEUR-WS.
• De Ridder, M., Jung, Y., Huang, R., Kim, J., Feng, D. (2015). Exploration of Virtual and Augmented Reality for Visual Analytics and 3D Volume Rendering of Functional Magnetic Resonance Imaging (fMRI) Data. 2015 Big Data Visual Analytics (BDVA), Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Feng, D., Kim, J., Khadra, M., Hudson, D., Roux, C. (2015). Guest-Editorial: Telehealth Systems and Applications. IEEE Journal of Biomedical and Health Informatics, 19(1), 81-81. [More Information]
• Jung, Y., Kim, J., Fulham, M., Feng, D. (2015). Volume rendering augmentation on slice of interest (SOI) for visualisation of thoracic PET-CT. International Journal of Computer Assisted Radiology and Surgery, Vol 10(suppl 1), 194-195.

2014

• Kumar, A., Kim, J., Wen, L., Fulham, M., Feng, D. (2014). A graph-based approach for the retrieval of multi-modality medical images. Medical Image Analysis, 18(2), 330-342. [More Information]
• Tripp, N., Hainey, K., Liu, A., Poulton, A., Peek, M., Kim, J., Nanan, R. (2014). An emerging model of maternity care: Smartphone, midwife, doctor? Women and Birth, 27(1), 64-67. [More Information]
• Kumar, A., Dyer, S., Li, C., Leong, P., Kim, J. (2014). Automatic annotation of liver CT images: the submission of the BMET group to ImageCLEFmed. CLEF 2014 Conference and Labs of the Evaluation Forum, United Kingdom: CEUR-WS.
• Bi, L., Kim, J., Feng, D., Fulham, M. (2014). Classification of thresholded regions based on selective use of PET, CT and PET-CT image features. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), : IEEE Computer Society. [More Information]
• Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Creating graph abstractions for the interpretation of combined functional and anatomical medical images. The First International Workshop on Graph Visualization in Practice, Melbourne: CEUR-WS.
• Kim, J., Thalmann, D., Zhou, J., Feng, D., Rushmeier, H. (2014). Editorial. The Visual Computer, 30(6-8), 565-567. [More Information]
• Kumar, A., Kim, J., Fulham, M., Feng, D. (2014). Efficient PET-CT image retrieval using graphs embedded into a vector space. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), : IEEE Computer Society. [More Information]
• Shah, M., Kim, J., Khadra, M., Feng, D. (2014). Enhancing home area networks to facilitate telehealth services: Test-bed scenario with video-consultation-calls (VCC). 2014 IEEE International Conference on Orange Technologies, ICOT 2014, Xian, China: Curran Associates, Inc. [More Information]
• Shah, M., Kim, J., Khadra, M., Feng, D. (2014). Home area network for optimizing telehealth services- empirical simulation analysis. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), : IEEE Computer Society. [More Information]
• Bi, L., Kim, J., Feng, D., Fulham, M. (2014). Multi-stage Thresholded Region Classification for Whole-Body PET-CT Lymphoma Studies. 17th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, Cham, Switzerland: Springer. [More Information]
• Jung, Y., Kim, J., Fulham, M., Feng, D. (2014). Opacity-driven volume clipping for slice of interest (SOI) visualisation of multi-modality PET-CT volumes. 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2014), : IEEE Computer Society. [More Information]

2013

• Constantinescu, L., Kim, J., Kumar, A., Haraguchi, D., Wen, L., Feng, D. (2013). A patient-centric distribution architecture for medical image sharing. Health Information Science and Systems, 1(3), 1-14. [More Information]
• De Ridder, M., Constantinescu, L., Bi, L., Jung, Y., Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). A web-based medical multimedia visualisation interface for personal health records. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Wen, L., Kumar, A., Fulham, M., Feng, D. (2013). Cellular automata and anisotropic diffusion filter based interactive tumor segmentation for positron emission tomography. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Kim, J., Cai, W., Fulham, M., Feng, D. (2013). Content-Based Medical Image Retrieval: A Survey of Applications to Multidimensional and Multimodality Data. Journal of Digital Imaging, 26(6), 1025-1039. [More Information]
• De Ridder, M., Bi, L., Constantinescu, L., Kim, J., Feng, D. (2013). Data processing and presentation for a personalised, image-driven medical graphical avatar. 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2013), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Kim, J., Bi, L., Fulham, M., Feng, D. (2013). Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images. International Journal of Computer Assisted Radiology and Surgery, 8(6), 1003-1014. [More Information]
• Kumar, A., Kim, J., Feng, D., Fulham, M. (2013). Graph-based retrieval of PET-CT images using vector space embedding. 26th IEEE International Symposium on Computer-Based Medical Systems (CBMS), Porto: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Shah, M., Kim, J., Feng, D. (2013). Impact of wireless devices over real-time applications: An empirical test-bed analysis. 38th Annual IEEE Conference on Local Computer Networks (LCN 2013), Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Jung, Y., Kim, J., Eberl, S., Fulham, M., Feng, D. (2013). Visibility-driven PET-CT visualisation with region of interest (ROI) segmentation. The Visual Computer, 29(6-8), 805-815. [More Information]

2012

• Kumar, A., Kim, J., Wen, L., Feng, D. (2012). A Graph-Based Approach to the Retrieval of Volumetric PET-CT Lung Images. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Song, Y., Cai, W., Kim, J., Feng, D. (2012). A multistage discriminative model for tumor and lymph node detection in thoracic images. IEEE Transactions on Medical Imaging, 31(5), 1061-1075. [More Information]
• Kumar, A., Kim, J., Bi, L., Feng, D. (2012). An image retrieval interface for volumetric multi-modal medical data: application to PET-CT content-based image retrieval. International Journal of Computer Assisted Radiology and Surgery, 7(1 (Suppl)), 475-477. [More Information]
• Bi, L., Kim, J., Wen, L., Feng, D. (2012). Automated and Robust PERCIST-based Thresholding framework for whole body PET-CT studies. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Nyirenda, G., Kim, J., Wen, L., Feng, D. (2012). Automated segmentation of tumour changes in temporal PET-CT data. 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2012), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Bi, L., Kim, J., Wen, L., Feng, D. (2012). Automatic Descending Aorta Segmentation in Whole-Body PET-CT Studies for PERCIST-Based Thresholding. 2012 International Conference on Digital Image Computing Techniques and Applications (DICTA), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Jung, Y., Kim, J., Feng, D. (2012). Dual-Modal Visibility Metrics for Interactive PET-CT Visualization. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kumar, A., Kim, J., Feng, D., Fulham, M. (2012). Graph-Based Retrieval of Multi-Modality Medical Images: A Comparison of Representations Using Simulated Images. The 25th International Symposium on Computer-Based Medical Systems (CBMS 2012), Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Wang, C., Kim, J., Jin, C., Leong, P., McEwan, A. (2012). Near infrared spectroscopy in optical coherence tomography. Journal of Near Infrared Spectroscopy, 20(1), 237-247. [More Information]
• Constantinescu, L., Kim, J., Feng, D. (2012). SparkMed: A Framework for Dynamic Integration of Multimedia Medical Data Into Distributed m-Health Systems. IEEE Transactions on Information Technology in Biomedicine, 16(1), 40-52. [More Information]

2011

• Kumar, A., Kim, J., Haraguchi, D., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). A query and visualisation interface for a PET-CT image retrieval system. International Journal of Computer Assisted Radiology and Surgery, 6(Supplement 1), 68-69.
• Haraguchi, D., Kim, J., Kumar, A., Constantinescu, L., Wen, L., Feng, D. (2011). A Web-based Image Viewer for Multiple PET-CT Follow-Up Studies. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2011), Piscataway, USA: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kim, J., Kumar, A., Cai, W., Feng, D. (2011). Multi-modal Content Based Image Retrieval in Healthcare: Current Applications and Future Challenges. In Joseph Tan (Eds.), New Technologies for Advancing Healthcare and Clinical Practices, (pp. 44-59). Pennsylvania, USA: Medical Information Science Reference.
• Kim, J. (2011). VacTube: an Embedded Radiological Scan Viewer for Referring Clinicians, Personal Health Records and eHealth 2.0. 96th Scientific Assembly and Annual Meeting of the Radiological Society of North America RSNA 2010, United States: Radiological Society of North America, Inc.
• Kim, J., Kumar, A., Wen, L., Eberl, S., Fulham, M., Feng, D. (2011). Visual Tracking of Treatment Response in PET-CT Image Sequences. International Journal of Computer Assisted Radiology and Surgery, , 17-18.

2010

• Han, S., Nijdam, N., Schmid, J., Kim, J., Magnenat-Thalmann, N. (2010). Collaborative Telemedicine for Interactive Multiuser Segmentation of Volumetric Medical Images. The Visual Computer, 26(6-8), 639-648. [More Information]
• Schmid, J., Kim, J., Magnenat-Thalmann, N. (2010). Coupled Registration-Segmentation: Application to Femur Analysis with Intra-subject Multiple Levels of Detail MRI Data. 13th International Conference on Medical Imaging and Computer Assisted Intervention (MICCAI 2010), Beijing: Springer. [More Information]
• Schmid, J., Kim, J., Magnenat-Thalmann, N. (2010). Extreme Leg Motion Analysis of Professional Ballet Dancers via MRI Segmentation of Multiple Leg Postures. International Journal of Computer Assisted Radiology and Surgery, 6(1), 47-57. [More Information]
• Schmid, J., Kim, J., Magnenat-Thalmann, N. (2010). Robust Statisical Shape Models for MRI Bone Segmentation in Presence of Small Image Field of View. Medical Image Analysis, 15(1), 155-168. [More Information]

2009

• Kim, J. (2009). A web-based method to remotely review diagnostic PET- CT data with internet-capable devices. The Journal of Nuclear Medicine, 50(Supplement 2).
• Kim, J. (2009). Automated Identification of Lesion Changes in Serial Whole-body PET-CT in NSCLC. The Journal of Nuclear Medicine, 50(Supplement 2).
• Kim, J., Cai, W., Feng, D. (2009). Bridging the Feature Gaps for Retrieval of Multi-Dimensional Images. International Journal of Healthcare Information Systems and Informatics, 4(1), 34-46. [More Information]
• Kim, J. (2009). Content-Based Retrieval of PET-CT Lung Cancer Data Using Spatial Features. The Journal of Nuclear Medicine.
• Constantinescu, L., Kim, J., Feng, D. (2009). Integration of Interactive Biomedical Image Data Visualisation to Internet-Based Personal Health Records for Handheld Devices. 11th IEEE International Conference on e-Health Networking, Applications & Services HEALTHCOM 2009, United States: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
• Kim, J. (2009). PET-CT Visualisation with Integrated Maximum Intensity Projection and Direct Volume Rendering. The Journal of Nuclear Medicine, 50(Supplement 2), 47.
• Kim, J. (2009). Rapid interactive smartphone access to PET-CT data for improved patient care. The Journal of Nuclear Medicine, 50(Supplement 2).
• Constantinescu, L., Pradana, R., Kim, J., Gong, P., Fulham, M., Feng, D. (2009). Rich Internet Application System for Patient-Centric Healthcare Data Management Using Handheld Devices. 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2009, Piscataway, New Jersey: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2008

• Kumar, A., Kim, J., Cai, W., Eberl, S., Feng, D. (2008). A Graph-Based Approach to the Retrieval of Dual-Modality Biomedical Images Using Spatial Relationships. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 08), USA: Institute of Electrical and Electronics Engineers (IEEE).
• Cai, W., Kim, J., Feng, D. (2008). Content-Based Medical Image Retrieval. In D Feng (Eds.), Biomedical Information Technology, (pp. 83-113). San Diego, USA: Academic Press. [More Information]
• Kim, J., Cai, W., Fulham, M., Eberl, S., Feng, D. (2008). Data Visualization and Display. In D Feng (Eds.), Biomedical Information Technology, (pp. 211-227). San Diego, USA: Academic Press. [More Information]
• Kim, J., Kumar, A., Eberl, S., Fulham, M., Feng, D. (2008). Interactive Point-of-Interest Volume Rendering Visualization of PET-CT Data. 2008 IEEE Nuclear Science Symposium, Medical Imaging Conference and 16th International Workshop on Room-temperature Semiconductor X- and Gamma-Ray Detectors (RTSD), CD-Rom: Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Wang, Z., Cai, W., Feng, D. (2008). Multimedia for Future Health - Smart Medical Home. In D Feng (Eds.), Biomedical Information Technology, (pp. 497-512). San Diego, USA: Academic Press. [More Information]

2007

• Constantinescu, L., Kim, J., Chan, C., Feng, D. (2007). Automatic Mobile Device Synchronization and Remote Control System for High-Performance Medical Applications. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), USA: Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Constantinescu, L., Cai, W., Feng, D. (2007). Content-based Dual-Modality Biomedical Data Retrieval Using Co-Aligned Functional and Anatomical Features. 10th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2007) (2nd publication record for this conference). MICCAI 2007.
• Kim, J., Hu, Y., Chan, C., Eberl, S., Cai, W., Feng, D., Fulham, M. (2007). Maximum intensity projection (MIP) visualisation and navigation of fused PET/CT with automated bed/linen removal. The Journal of Nuclear Medicine, 48 (Suppl 2)(5), 414.
• Kim, J., Hu, Y., Chan, C., Eberl, S., Cai, W., Feng, D., Fulham, M. (2007). Maximum intensity projection (MIP) visualization and navigation of fused PET/CT with automated bed/linen removal. The Journal of Nuclear Medicine, Volume 48(5 Supplement 2), 414-414.
• Kim, J., Cai, W., Eberl, S., Feng, D. (2007). Real time volume rendering visualization. IEEE Transactions on Information Technology in Biomedicine, 11(2), 161-169.
• Kim, J., Cai, W., Eberl, S., Feng, D. (2007). Real-time volume rendering visualization of dual-modality PET/CT images with interactive fuzzy thresholding segmentation. IEEE Transactions on Information Technology in Biomedicine, 11(2), 161-169. [More Information]
• Kim, J., Wen, L., Eberl, S., Fulton, R., Feng, D. (2007). Use of Anatomical Priors in the Segmentation of PET Lung Tumor Images. 2007 IEEE Nuclear Science Symposium & medical Imaging Conference, USA: Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Eberl, S., Feng, D. (2007). Visualizing dual-modality rendered volumes using a dual-lookup table transfer function. Computing in Science and Engineering, 9(1), 20-25. [More Information]

2006

• Kim, J., Cai, W., Feng, D., Wu, H. (2006). A new way for multidimensional medical data management: Volume of interest (VOI)-based retrieval of medical images with visual and functional features. IEEE Transactions on Information Technology in Biomedicine, 10(3), 598-607. [More Information]
• Macready, H., Kim, J., Feng, D., Cai, W. (2006). Interactive Dual-volume Rendering Visualization with Real-time Fusion and Transfer Function Enhancement. SPIE Medical Imaging 2006. SPIE - International Society for Optical Engineering.
• Kim, J., Cai, W., Feng, D., Eberl, S. (2006). Segmentation of VOI from multidimensional dynamic PET images by integrating spatial and temporal features. IEEE Transactions on Information Technology in Biomedicine, 10(4), 637-646. [More Information]

2005

• Kim, J., Cai, W., Feng, D. (2005). Dual-Modality PET-CT Visualisation using Real-Time Volume Rendering and Image Fusion with Interactive 3D Segmentation of Anatomical Structures. 27th Annual International Conference IEEE Engineering in Medicine and Biology Society (EMBS) 2005, USA: Institute of Electrical and Electronics Engineers (IEEE).
• Chan, C., Kim, J., Feng, D., Cai, W. (2005). Interactive Fusion and Contrast Enhancement for Whole Body PET-CT Using Multi-Image Pixel Composting. 2005 IEEE Medical Imaging Conference 2005. Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Cai, W., Feng, D., Eberl, S. (2005). Interactive Fuzzy Temporal Thresholding for the Segmentation Dynamic Brain PET Images. Journal of Cerebral Blood Flow and Metabolism, 25, S620.
• Kim, J., Cai, W., Feng, D., Eberl, S. (2005). Interactive Multi-Volume Visualization of Segmented Structures within PET-CT Data Sets. The Journal of Nuclear Medicine, 46, 466P.

2004

• Kim, J., Cai, W., Feng, D., Eberl, S. (2004). An Objective Evaluation Framework For Segmentation Techniques Of Functional Positron Emission Tomography Studies. Nuclear Science Symposium, Medical Imaging Conference(NSS-MIC 2004), Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Cai, W., Feng, D., Fulton, R. (2004). Smoothing Of Reconstructed Dynamic Pet Images Using Fuzzy Temporal Kinetic Filtering. The Journal of Nuclear Medicine, 45, 469P.
• Wu, H., Kim, J., Cai, W., Feng, D. (2004). Volume Of Interest (Voi) Feature Representation And Retrieval Of Multi-Dimensional Positron Emission Tomography Images. International Symposium on Intelligent Multimedia, Video and Speech Processing: ISIMP 2004, Piscataway NJ: Institute of Electrical and Electronics Engineers (IEEE).

2003

• Kim, J., Feng, D., Cai, W. (2003). A quantitative evaluation measure for 3D biomedical image segmentation. Modelling and Control in Biomedical Systems 2003 (Including Biological Systems), UK: Pergamon. [More Information]
• Kim, J., Feng, D., Cai, W., Eberl, S. (2003). Automatic 3D Temporal Kinetics Segmentation of Dynamic Emission Tomography Image Using Adaptive Region Growing Cluster Analysis. 2002 IEEE Nuclear Science Symposium and Medical Imaging Conference, Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers (IEEE).
• Chan, C., Feng, D., Kim, J., Eberl, S. (2003). Online Interactive 3D Region of Interest (ROI) Visualization of Positron Emission Tomography (PET) Data. World Congress on Medical Physics and Biomedical Engineering incorporating the 21st International Conference on Medical & Biological Engineering & the 15th International Conference on Medical Physics, UK: Springer.
• Kim, J., Feng, D., Cai, W., Eberl, S. (2003). Three-dimensional multi-plane segmentation of dynamic PET data by optimized seeded region growing approach. Journal of Cerebral Blood Flow and Metabolism, 23, 617.
• Feng, D., Chan, K., Kim, J., Lim, Y. (2003). Web-based Electronic Patient Record System for Biomedical Data Based on User Analysis. World Congress on Medical Physics and Biomedical Engineering incorporating the 21st International Conference on Medical & Biological Engineering & the 15th International Conference on Medical Physics, UK: Springer.

2002

• Kim, J., Feng, D., Cai, W., Eberl, S. (2002). A solution to the distribution and standardisation of multimedia medical data in e-health. Visualisation 2001 - The pan-Sydney area workshop on visual information processing, Australia: ACS Inc.
• Kim, J., Feng, D., Cai, W., Eberl, S. (2002). Conent Access and Distribution of Multimedia Medial Data in E-Health. 2002 IEEE International Conference on Multimedia and Expo, Tampere, Finland: Institute of Electrical and Electronics Engineers (IEEE).
• Kim, J., Feng, D., Cai, W., Eberl, S. (2002). Integrated Multimedia Medical Data Agent in E-Health. The Pan-Sydney Area workshop on Visual Information Processing, Australia: Association for Computing Machinery (ACM).

2001

• Kim, J., Feng, D., Cai, W. (2001). A Web-based Medical Image Data Processing and Management System. Pan-Sydney Workshop on Visual Information Processing, Sydney: Australian Computer Society.