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ORCIDJinman Kim
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- affiliation: University of Sydney, School of Computer Science, Sydney, Australia
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2020 – today
- 2024
[j107]Lei Bi
, Ulrich Buehner, Xiaohang Fu, Tom M. Williamson, Peter Choong, Jinman Kim:
Hybrid CNN-transformer network for interactive learning of challenging musculoskeletal images. Comput. Methods Programs Biomed. 243: 107875 (2024)- [j106]Younhyun Jung, Jim Kong, Bin Sheng, Jinman Kim:
A Transfer Function Design for Medical Volume Data Using a Knowledge Database Based on Deep Image and Primitive Intensity Profile Features Retrieval. J. Comput. Sci. Technol. 39(2): 320-335 (2024) - [j105]Ziyi Qi, Tingyao Li, Jun Chen, Jason C. Yam, Yang Wen, Gengyou Huang, Hua Zhong, Mingguang He, Dan Zhu, Rongping Dai, Bo Qian, Jingjing Wang, Chaoxu Qian, Wei Wang, Yanfei Zheng, Jian Zhang, Xianglong Yi, Zheyuan Wang, Bo Zhang, Chunyu Liu, Tianyu Cheng, Xiaokang Yang, Jun Li, Yan-Ting Pan, Xiaohu Ding, Ruilin Xiong, Yan Wang, Yan Zhou, Dagan Feng, Sichen Liu, Linlin Du, Jinliuxing Yang, Zhuoting Zhu, Lei Bi, Jinman Kim, Fangyao Tang, Yuzhou Zhang, Xiujuan Zhang, Haidong Zou, Marcus Ang, Clement C. Tham, Carol Y. Cheung, Chi Pui Pang, Bin Sheng, Xiangui He, Xun Xu:
A deep learning system for myopia onset prediction and intervention effectiveness evaluation in children. npj Digit. Medicine 7(1) (2024) - [j104]Hao Wang, Euijoon Ahn, Jinman Kim:
A multi-resolution self-supervised learning framework for semantic segmentation in histopathology. Pattern Recognit. 155: 110621 (2024) - [j103]Jianan Liu, Hao Li, Tao Huang, Euijoon Ahn, Kang Han, Adeel Razi, Wei Xiang, Jinman Kim, David Dagan Feng:
Unsupervised Representation Learning for 3-D Magnetic Resonance Imaging Superresolution With Degradation Adaptation. IEEE Trans. Artif. Intell. 5(9): 4660-4674 (2024) - [j102]Usman Naseem, Matloob Khushi, Jinman Kim, Adam G. Dunn:
Hybrid Text Representation for Explainable Suicide Risk Identification on Social Media. IEEE Trans. Comput. Soc. Syst. 11(4): 4663-4672 (2024) - [j101]Usman Naseem, Matloob Khushi, Adam G. Dunn, Jinman Kim:
K-PathVQA: Knowledge-Aware Multimodal Representation for Pathology Visual Question Answering. IEEE J. Biomed. Health Informatics 28(4): 1886-1895 (2024) - [j100]Ahmad Karambakhsh, Bin Sheng, Ping Li, Huating Li, Jinman Kim, Younhyun Jung, C. L. Philip Chen:
SparseVoxNet: 3-D Object Recognition With Sparsely Aggregation of 3-D Dense Blocks. IEEE Trans. Neural Networks Learn. Syst. 35(1): 532-546 (2024) - [j99]Saleha Masood, Saba Ghazanfar Ali, Xiangning Wang, Afifa Masood, Ping Li, Huating Li, Younhyun Jung, Bin Sheng, Jinman Kim:
Deep choroid layer segmentation using hybrid features extraction from OCT images. Vis. Comput. 40(4): 2775-2792 (2024) - [j98]Mingjian Li, Younhyun Jung, Michael J. Fulham, Jinman Kim:
Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study. Virtual Real. Intell. Hardw. 6(1): 71-81 (2024) - [c107]Mingyuan Meng, Dagan Feng, Lei Bi, Jinman Kim:
Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration. CVPR 2024: 9645-9654 - [c106]Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn:
A Linguistic Grounding-Infused Contrastive Learning Approach for Health Mention Classification on Social Media. WSDM 2024: 529-537 - [e8]Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann:
Advances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 - September 1, 2023, Proceedings, Part I. Lecture Notes in Computer Science 14495, Springer 2024, ISBN 978-3-031-50068-8 [contents] - [e7]Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann:
Advances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 - September 1, 2023, Proceedings, Part II. Lecture Notes in Computer Science 14496, Springer 2024, ISBN 978-3-031-50071-8 [contents] - [e6]Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann:
Advances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 - September 1, 2023, Proceedings, Part III. Lecture Notes in Computer Science 14497, Springer 2024, ISBN 978-3-031-50074-9 [contents] - [e5]Bin Sheng, Lei Bi, Jinman Kim, Nadia Magnenat-Thalmann, Daniel Thalmann:
Advances in Computer Graphics - 40th Computer Graphics International Conference, CGI 2023, Shanghai, China, August 28 - September 1, 2023, Proceedings, Part IV. Lecture Notes in Computer Science 14498, Springer 2024, ISBN 978-3-031-50077-0 [contents] - [i53]Mingjian Li, Mingyuan Meng, Michael J. Fulham, David Dagan Feng, Lei Bi, Jinman Kim:
Enhancing medical vision-language contrastive learning via inter-matching relation modelling. CoRR abs/2401.10501 (2024) - [i52]Shuchang Ye, Mingyuan Meng, Mingjian Li, Dagan Feng, Jinman Kim:
Dual-modal Dynamic Traceback Learning for Medical Report Generation. CoRR abs/2401.13267 (2024) - [i51]Mingyuan Meng, Dagan Feng, Lei Bi, Jinman Kim:
Correlation-aware Coarse-to-fine MLPs for Deformable Medical Image Registration. CoRR abs/2406.00123 (2024) - [i50]Hao Wang, Euijoon Ahn, Jinman Kim:
GVT2RPM: An Empirical Study for General Video Transformer Adaptation to Remote Physiological Measurement. CoRR abs/2406.13136 (2024) - [i49]Xiaoshuang Li, Mingyuan Meng, Zimo Huang, Lei Bi, Eduardo Delamare, Dagan Feng, Bin Sheng, Jinman Kim:
3DPX: Progressive 2D-to-3D Oral Image Reconstruction with Hybrid MLP-CNN Networks. CoRR abs/2408.01292 (2024) - 2023
- [j97]Xiaohang Fu, Ellis Patrick, Jean Y. H. Yang, David Dagan Feng, Jinman Kim:
Deep multimodal graph-based network for survival prediction from highly multiplexed images and patient variables. Comput. Biol. Medicine 154: 106576 (2023) - [j96]Lei Bi, M. Emre Celebi, Hitoshi Iyatomi, Pablo Fernandez-Penas, Jinman Kim:
Image analysis in advanced skin imaging technology. Comput. Methods Programs Biomed. 238: 107599 (2023) - [j95]Haill An, Jinman Kim, Bin Sheng, Ping Li, Younhyun Jung:
A transfer function optimization using visual saliency for region of interest-based direct volume rendering. Displays 80: 102531 (2023) - [j94]Wei-Chien Wang, Euijoon Ahn, David Feng, Jinman Kim:
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images. Mach. Intell. Res. 20(4): 483-513 (2023) - [j93]Tian Xia, Xiaohang Fu, Michael J. Fulham, Yue Wang, David Feng, Jinman Kim:
CT-based Radiogenomics Framework for COVID-19 Using ACE2 Imaging Representations. J. Digit. Imaging 36(6): 2356-2366 (2023) - [j92]Yannik Kalbas, Hoijoon Jung, John Ricklin, Ge Jin, Mingjian Li, Thomas Rauer, Shervin Dehghani, Nassir Navab, Jinman Kim, Hans-Christoph Pape, Sandro-Michael Heining:
Remote Interactive Surgery Platform (RISP): Proof of Concept for an Augmented-Reality-Based Platform for Surgical Telementoring. J. Imaging 9(3): 56 (2023) - [j91]Jinman Kim, George Papagiannakis, Bin Sheng, Daniel Thalmann:
Editorial. Comput. Animat. Virtual Worlds 34(1) (2023) - [j90]Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn:
Robust Identification of Figurative Language in Personal Health Mentions on Twitter. IEEE Trans. Artif. Intell. 4(2): 362-372 (2023) - [j89]Usman Naseem, Matloob Khushi, Jinman Kim, Adam G. Dunn:
RHMD: A Real-World Dataset for Health Mention Classification on Reddit. IEEE Trans. Comput. Soc. Syst. 10(5): 2325-2334 (2023) - [j88]Yuyu Guo, Lei Bi, Dongming Wei, Liyun Chen, Zhengbin Zhu, Dagan Feng, Ruiyan Zhang, Qian Wang, Jinman Kim:
Unsupervised Landmark Detection-Based Spatiotemporal Motion Estimation for 4-D Dynamic Medical Images. IEEE Trans. Cybern. 53(6): 3532-3545 (2023) - [j87]Usman Naseem, Matloob Khushi, Jinman Kim:
Vision-Language Transformer for Interpretable Pathology Visual Question Answering. IEEE J. Biomed. Health Informatics 27(4): 1681-1690 (2023) - [j86]Wenxiang Ding, Qiaoqiao Ding, Kewei Chen, Miao Zhang, Li Lv, David Dagan Feng, Lei Bi, Jinman Kim, Qiu Huang:
A Shortened Model for Logan Reference Plot Implemented via the Self-Supervised Neural Network for Parametric PET Imaging. IEEE Trans. Medical Imaging 42(10): 2842-2852 (2023) - [j85]Abdulrhman H. Al-Jebrni, Saba Ghazanfar Ali, Huating Li, Xiao Lin, Ping Li, Younhyun Jung, Jinman Kim, David Dagan Feng, Bin Sheng, Lixin Jiang, Jing Du:
SThy-Net: a feature fusion-enhanced dense-branched modules network for small thyroid nodule classification from ultrasound images. Vis. Comput. 39(8): 3675-3689 (2023) - [c105]Ge Jin, Younhyun Jung, Jinman Kim:
Challenges and Constraints in Deformation-Based Medical Mesh Representation. CGI (4) 2023: 146-156 - [c104]Shuchang Ye, Mingyuan Meng, David Dagan Feng, Jinman Kim:
Semantic-Driven Global-Local Cooperative Contrastive Learning for Medical Report Generation. DICTA 2023: 251-257 - [c103]Lei Bi, Michael J. Fulham, Shaoli Song, David Dagan Feng, Jinman Kim:
Hyper-Connected Transformer Network for Multi-Modality PET-CT Segmentation. EMBC 2023: 1-4 - [c102]Yuan Yuan, Euijoon Ahn, Dagan Feng, Mohamed Khadra, Jinman Kim:
SSPT-bpMRI: A Self-supervised Pre-training Scheme for Improving Prostate Cancer Detection and Diagnosis in Bi-parametric MRI. EMBC 2023: 1-4 - [c101]Anum Masood, Usman Naseem, Jinman Kim:
Multi-Level Swin Transformer Enabled Automatic Segmentation and Classification of Breast Metastases. EMBC 2023: 1-4 - [c100]Mingxiao Tu, Hoijoon Jung, Alireza Moghadam, Jineel Raythatha, Jeremy Hsu, Jinman Kim:
Exploring the Performance of Geometry-Based Markerless Registration in a Simulated Surgical Environment: A Comparative Study of Registration Algorithms in Medical Augmented Reality. EMBC 2023: 1-4 - [c99]Yuxin Xue, Yige Peng, Lei Bi, Dagan Feng, Jinman Kim:
CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images. EMBC 2023: 1-4 - [c98]Shijia Zhou, Pradeeba Sridar, Narelle June Kennedy, Ann Quinton, Euijoon Ahn, Ralph Nanan, Jinman Kim:
A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm. EMBC 2023: 1-5 - [c97]Ye Cai, Na Liu, Robin Huang, Kamal Sud, Jinman Kim:
Predicting Remote Monitoring Patients' Non-compliance Behavior Through App-mediated Communications. HICSS 2023: 3101-3110 - [c96]Shijia Zhou, Euijoon Ahn, Hao Wang, Ann Quinton, Narelle Kennedy, Pradeeba Sridar, Ralph Nanan, Jinman Kim:
Improving Automatic Fetal Biometry Measurement with Swoosh Activation Function. MICCAI (7) 2023: 283-292 - [c95]Mingyuan Meng, Lei Bi, Michael J. Fulham, David Feng, Jinman Kim:
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer. MICCAI (6) 2023: 400-410 - [c94]Mingyuan Meng, Lei Bi, Michael J. Fulham, David Dagan Feng, Jinman Kim:
Non-iterative Coarse-to-Fine Transformer Networks for Joint Affine and Deformable Image Registration. MICCAI (10) 2023: 750-760 - [c93]Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn:
A Multimodal Framework for the Identification of Vaccine Critical Memes on Twitter. WSDM 2023: 706-714 - [c92]Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn:
Graph-Based Hierarchical Attention Network for Suicide Risk Detection on Social Media. WWW (Companion Volume) 2023: 995-1003 - [i48]Wei-Chien Wang, Euijoon Ahn, Dagan Feng, Jinman Kim:
A Review of Predictive and Contrastive Self-supervised Learning for Medical Images. CoRR abs/2302.05043 (2023) - [i47]Hao Wang, Euijoon Ahn, Jinman Kim:
A Dual-branch Self-supervised Representation Learning Framework for Tumour Segmentation in Whole Slide Images. CoRR abs/2303.11019 (2023) - [i46]Yuxin Xue, Yige Peng, Lei Bi, Dagan Feng, Jinman Kim:
CG-3DSRGAN: A classification guided 3D generative adversarial network for image quality recovery from low-dose PET images. CoRR abs/2304.00725 (2023) - [i45]Mingyuan Meng, Bingxin Gu, Michael J. Fulham, Shaoli Song, Dagan Feng, Lei Bi, Jinman Kim:
DeepMSS: Deep Multi-Modality Segmentation-to-Survival Learning for Survival Outcome Prediction from PET/CT Images. CoRR abs/2305.09946 (2023) - [i44]Mingyuan Meng, Lei Bi, Michael J. Fulham, Dagan Feng, Jinman Kim:
Non-iterative Coarse-to-fine Transformer Networks for Joint Affine and Deformable Image Registration. CoRR abs/2307.03421 (2023) - [i43]Mingyuan Meng, Lei Bi, Michael J. Fulham, Dagan Feng, Jinman Kim:
Merging-Diverging Hybrid Transformer Networks for Survival Prediction in Head and Neck Cancer. CoRR abs/2307.03427 (2023) - [i42]Mingyuan Meng, Michael J. Fulham, Dagan Feng, Lei Bi, Jinman Kim:
AutoFuse: Automatic Fusion Networks for Deformable Medical Image Registration. CoRR abs/2309.05271 (2023) - [i41]Yuxin Xue, Lei Bi, Yige Peng, Michael J. Fulham, David Dagan Feng, Jinman Kim:
PET Synthesis via Self-supervised Adaptive Residual Estimation Generative Adversarial Network. CoRR abs/2310.15550 (2023) - [i40]Hao Wang, Euijoon Ahn, Lei Bi, Jinman Kim:
Self-Supervised Multi-Modality Learning for Multi-Label Skin Lesion Classification. CoRR abs/2310.18583 (2023) - [i39]Mingyuan Meng, Yuxin Xue, David Dagan Feng, Lei Bi, Jinman Kim:
Full-resolution MLPs Empower Medical Dense Prediction. CoRR abs/2311.16707 (2023) - 2022
- [j84]Lei Bi, Jinman Kim, Tingwei Su, Michael J. Fulham, David Dagan Feng, Guang Ning:
Deep multi-scale resemblance network for the sub-class differentiation of adrenal masses on computed tomography images. Artif. Intell. Medicine 132: 102374 (2022) - [j83]Usman Naseem, Adam G. Dunn, Matloob Khushi, Jinman Kim:
Benchmarking for biomedical natural language processing tasks with a domain specific ALBERT. BMC Bioinform. 23(1): 144 (2022) - [j82]Joyce Zhanzi Wang, Jonathon Lillia, Ashnil Kumar, Paula Bray, Jinman Kim, Joshua Burns, Tegan L. Cheng:
Clinical applications of machine learning in predicting 3D shapes of the human body: a systematic review. BMC Bioinform. 23(1): 431 (2022) - [j81]Saba Ghazanfar Ali, Riaz Ali, Bin Sheng, Yan Chen, Huating Li, Po Yang, Ping Li, Younhyun Jung, Fang Zhu, Ping Lu, Jinman Kim:
Experimental protocol designed to employ Nd: YAG laser surgery for anterior chamber glaucoma detection via UBM. IET Image Process. 16(8): 2171-2179 (2022) - [j80]Jinman Kim, George Papagiannakis, Bin Sheng, Daniel Thalmann:
Special issue on computer graphics international 2022 part 1. Comput. Animat. Virtual Worlds 33(5) (2022) - [j79]Jinman Kim, George Papagiannakis, Bin Sheng, Daniel Thalmann:
Editorial. Comput. Animat. Virtual Worlds 33(6) (2022) - [j78]Lei Bi, Michael J. Fulham, Jinman Kim:
Hyper-fusion network for semi-automatic segmentation of skin lesions. Medical Image Anal. 76: 102334 (2022) - [j77]Mingyuan Meng, Lei Bi, Michael J. Fulham, David Dagan Feng, Jinman Kim:
Enhancing medical image registration via appearance adjustment networks. NeuroImage 259: 119444 (2022) - [j76]Genevieve Coorey, Gemma A. Figtree, David F. Fletcher, Victoria J. Snelson, Stephen T. Vernon, David S. Winlaw, Stuart M. Grieve, Alistair Lee McEwan, Jean Yee Hwa Yang, Pierre Qian, Kieran O'Brien, Jessica Orchard, Jinman Kim, Sanjay Patel, Julie Redfern:
The health digital twin to tackle cardiovascular disease - a review of an emerging interdisciplinary field. npj Digit. Medicine 5 (2022) - [j75]Ke Yan, Xiuying Wang, Jinman Kim, Wangmeng Zuo, Dagan Feng:
Deep Cognitive Gate: Resembling Human Cognition for Saliency Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4776-4792 (2022) - [j74]Xiaohang Fu, Lei Bi, Ashnil Kumar, Michael J. Fulham, Jinman Kim:
An attention-enhanced cross-task network to analyse lung nodule attributes in CT images. Pattern Recognit. 126: 108576 (2022) - [j73]Anam Nazir, Muhammad Nadeem Cheema, Bin Sheng, Ping Li, Huating Li, Guangtao Xue, Jing Qin, Jinman Kim, David Dagan Feng:
ECSU-Net: An Embedded Clustering Sliced U-Net Coupled With Fusing Strategy for Efficient Intervertebral Disc Segmentation and Classification. IEEE Trans. Image Process. 31: 880-893 (2022) - [j72]Xiaoya Qiao, Chunjuan Jiang, Panli Li, Yuan Yuan, Qinglong Zeng, Lei Bi, Shaoli Song, Jinman Kim, David Dagan Feng, Qiu Huang:
Improving Breast Tumor Segmentation in PET via Attentive Transformation Based Normalization. IEEE J. Biomed. Health Informatics 26(7): 3261-3271 (2022) - [j71]Mingyuan Meng, Bingxin Gu, Lei Bi, Shaoli Song, David Dagan Feng, Jinman Kim:
DeepMTS: Deep Multi-Task Learning for Survival Prediction in Patients With Advanced Nasopharyngeal Carcinoma Using Pretreatment PET/CT. IEEE J. Biomed. Health Informatics 26(9): 4497-4507 (2022) - [j70]Xiaohang Fu, Lei Bi, Ashnil Kumar, Michael J. Fulham, Jinman Kim:
Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images. IEEE Trans. Medical Imaging 41(11): 3266-3277 (2022) - [j69]Sofiane Zeghoud, Saba Ghazanfar Ali, Egemen Ertugrul, Aouaidjia Kamel, Bin Sheng, Ping Li, Xiaoyu Chi, Jinman Kim, Lijuan Mao:
Real-time spatial normalization for dynamic gesture classification. Vis. Comput. 38(4): 1345-1357 (2022) - [j68]Nadia Magnenat-Thalmann, Jinman Kim, George Papagiannakis, Daniel Thalmann, Bin Sheng:
Computer graphics for metaverse. Virtual Real. Intell. Hardw. 4(5): ii-iv (2022) - [c91]Hao Wang, Euijoon Ahn, Jinman Kim:
Self-Supervised Representation Learning Framework for Remote Physiological Measurement Using Spatiotemporal Augmentation Loss. AAAI 2022: 2431-2439 - [c90]Mingyuan Meng, Lei Bi, David Feng, Jinman Kim:
Brain Tumor Sequence Registration with Non-iterative Coarse-To-Fine Networks and Dual Deep Supervision. BrainLes@MICCAI 2022: 273-282 - [c89]Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim:
Non-iterative Coarse-to-Fine Registration Based on Single-Pass Deep Cumulative Learning. MICCAI (6) 2022: 88-97 - [c88]Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim:
Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer. HECKTOR@MICCAI 2022: 135-143 - [c87]Hoijoon Jung, Younhyun Jung, Jinman Kim:
Understanding the Capabilities of the HoloLens 1 and 2 in a Mixed Reality Environment for Direct Volume Rendering with a Ray-casting Algorithm. VR Workshops 2022: 698-699 - [c86]Usman Naseem, Adam G. Dunn, Jinman Kim, Matloob Khushi:
Early Identification of Depression Severity Levels on Reddit Using Ordinal Classification. WWW 2022: 2563-2572 - [c85]Usman Naseem, Jinman Kim, Matloob Khushi, Adam G. Dunn:
Identification of Disease or Symptom terms in Reddit to Improve Health Mention Classification. WWW 2022: 2573-2581 - [e4]Nadia Magnenat-Thalmann, Jian Zhang, Jinman Kim, George Papagiannakis, Bin Sheng, Daniel Thalmann, Marina L. Gavrilova:
Advances in Computer Graphics - 39th Computer Graphics International Conference, CGI 2022, Virtual Event, September 12-16, 2022, Proceedings. Lecture Notes in Computer Science 13443, Springer 2022, ISBN 978-3-031-23472-9 [contents] - [i38]Hoijoon Jung, Younhyun Jung, Michael J. Fulham, Jinman Kim:
Mixed reality hologram slicer (mxdR-HS): a marker-less tangible user interface for interactive holographic volume visualization. CoRR abs/2201.10704 (2022) - [i37]Usman Naseem, Byoung-Chan Lee, Matloob Khushi, Jinman Kim, Adam G. Dunn:
Benchmarking for Public Health Surveillance tasks on Social Media with a Domain-Specific Pretrained Language Model. CoRR abs/2204.04521 (2022) - [i36]Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim:
Non-iterative Coarse-to-fine Registration based on Single-pass Deep Cumulative Learning. CoRR abs/2206.12596 (2022) - [i35]Younhyun Jung, Jim Kong, Jinman Kim:
A Transfer Function Design Using A Knowledge Database based on Deep Image and Primitive Intensity Profile Features Retrieval. CoRR abs/2209.06421 (2022) - [i34]Yige Peng, Jinman Kim, Dagan Feng, Lei Bi:
Automatic Tumor Segmentation via False Positive Reduction Network for Whole-Body Multi-Modal PET/CT Images. CoRR abs/2209.07705 (2022) - [i33]Lei Bi, Xiaohang Fu, Qiufang Liu, Shaoli Song, David Dagan Feng, Michael J. Fulham, Jinman Kim:
Hyper-Connected Transformer Network for Co-Learning Multi-Modality PET-CT Features. CoRR abs/2210.15808 (2022) - [i32]Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim:
Radiomics-enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer. CoRR abs/2211.05409 (2022) - [i31]Mingyuan Meng, Lei Bi, Dagan Feng, Jinman Kim:
Brain Tumor Sequence Registration with Non-iterative Coarse-to-fine Networks and Dual Deep Supervision. CoRR abs/2211.07876 (2022) - [i30]Yuan Yuan, Euijoon Ahn, Dagan Feng, Mohamed Khadra, Jinman Kim:
Z-SSMNet: A Zonal-aware Self-Supervised Mesh Network for Prostate Cancer Detection and Diagnosis in bpMRI. CoRR abs/2212.05808 (2022) - 2021
- [j67]Vishal Singh, Pradeeba Sridar, Jinman Kim, Ralph Nanan, N. Poornima, Shanmuga Priya, G. Sameera Reddy, Sathyabama Chandrasekaran, Ramarathnam Krishna Kumar:
Semantic Segmentation of Cerebellum in 2D Fetal Ultrasound Brain Images Using Convolutional Neural Networks. IEEE Access 9: 85864-85873 (2021) - [j66]Ruicong Zhang, Li Zhuo, Hui Zhang, Yan Zhang, Jinman Kim, Hongxia Yin, Pengfei Zhao, Zhenchang Wang:
Vestibule segmentation from CT images with integration of multiple deep feature fusion strategies. Comput. Medical Imaging Graph. 89: 101872 (2021) - [j65]Yuyu Guo, Lei Bi, Zhengbin Zhu, David Dagan Feng, Ruiyan Zhang, Qian Wang, Jinman Kim:
Automatic left ventricular cavity segmentation via deep spatial sequential network in 4D computed tomography. Comput. Medical Imaging Graph. 91: 101952 (2021) - [j64]Lei Bi, Michael J. Fulham, Nan Li, Qiufang Liu, Shaoli Song, David Dagan Feng, Jinman Kim:
Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation. Comput. Methods Programs Biomed. 203: 106043 (2021) - [j63]Mingyuan Meng, Xingyu Yang, Lei Bi, Jinman Kim, Shanlin Xiao, Zhiyi Yu:
High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning. Neurocomputing 441: 92-104 (2021) - [j62]Xinheng Wu, Lei Bi, Michael J. Fulham, David Dagan Feng, Luping Zhou, Jinman Kim:
Unsupervised brain tumor segmentation using a symmetric-driven adversarial network. Neurocomputing 455: 242-254 (2021) - [j61]Yu Zhou, Zhihua Chen, Bin Sheng, Ping Li, Jinman Kim, Enhua Wu:
AFF-Dehazing: Attention-based feature fusion network for low-light image Dehazing. Comput. Animat. Virtual Worlds 32(3-4) (2021) - [j60]Anam Nazir, Muhammad Nadeem Cheema, Bin Sheng, Ping Li, Jinman Kim, Tong-Yee Lee:
Living Donor-Recipient Pair Matching for Liver Transplant via Ternary Tree Representation With Cascade Incremental Learning. IEEE Trans. Biomed. Eng. 68(8): 2540-2551 (2021) - [j59]Usman Naseem, Imran Razzak, Matloob Khushi, Peter W. Eklund, Jinman Kim:
COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis. IEEE Trans. Comput. Soc. Syst. 8(4): 1003-1015 (2021) - [j58]Ke Yan, Xiuying Wang, Jinman Kim, Dagan Feng:
A New Aggregation of DNN Sparse and Dense Labeling for Saliency Detection. IEEE Trans. Cybern. 51(12): 5907-5920 (2021) - [j57]Riaz Ali, Bin Sheng, Ping Li