|
Dakai Jin
Staff Algorithm Engineer
@ Alibaba DAMO Academy
Email: dakai.jin at gmail dot com
GoogleScholar, LinkedIn
|
Brief Bio
Since 2021, I have been working as a staff algorithm engineer at Alibaba DAMO Academy, where I lead a team focused on projects such as radiotherapy target volume segmentation, volumetric image registration, cancer screening and diagnosis, as well as treatment response and prognostic analysis. It is a blessing to work with extraordinarily talented colleagues and physicians!
Before that, I was a staff scientist at PAII Inc, which was directed by Dr. Le Lu. I was a visiting research fellow at National Institutes of Health (NIH) working on pulmonary image analysis, including the lung, lobe and airway tree segmentation and the interstitial lung disease detection. I received my Ph.D. at University of Iowa in 2016 under the supervision of Prof. Punam Saha and Prof. Eric Hoffman.
We are looking for highly motivated interns with strong research experience in medical image analysis or computer vision. If you're interested, please send your resume.
Updates
[07/2024] Four abstracts are accepted by RSNA 2024. (Two oral presentations! Congrats to Qinji, Haoshen, Yirui, Hongxi, Zi, Hexuan, Dazhou!)
[07/2024] One paper on lymph node detection is accepted by ECCV 2024. (Congrats to Qinji and Yirui!)
[06/2024] One paper on airway segmentation is accepted by IEEE TMI 2024. (Congrats to Puyang!)
[06/2024] Four papers are accepted by MICCAI 2024. (Congrats to Hongxi, Qinji, Haoshen, Charley, Hanqing, Hexuan, Dazhou, Yirui!)
[05/2024] Invited to serve as Senior Program Committee (SPC) for AAAI 2025.
[03/2024] One paper is accepted by CVPR 2024. (Congrats to Zi and Tony!)
[02/2024] Invited to serve as Area Chair for MICCAI 2024
[10/2023] We win the 1st place at 2023 Learn2Reg Challenge: ThoraxCBCT (the new task of lung images registration between CBCT and FBCT from multiple time points). (Congrats to Zi Li!)
[07/2023] Invited to serve as Senior Program Committee (SPC) for AAAI 2024.
[07/2023] One paper is accepted by ICCV 2023. (Congrats to Hexuan, Dazhou and Puyang!)
[07/2023] Three abstracts are accepted by RSNA 2023. (Congrats to Yirui, Zi, Yixiao and Dazhou!)
[06/2023] One paper is accepted by IEEE TMI 2023. (Congrats to Zihan!)
[06/2023] One paper is accepted by MICCAI 2023. (Congrats to Zi Li and Lin Tian and Tony!)
[05/2023] Three abstracts are accepted by ASTRO 2023. (one oral presentation (203 out of 2500+ submissions), congrats to Yirui, Puyang, Yixiao and Dazhou!)
[03/2023] One abstract is accepted by AHNS 2023. (oral presentation, congrats to Yirui!)
[12/2022] One invaited reviewing paper is accepted by Journal of the National Cancer Center.
[10/2022] One paper is accepted by Nature Communications.
[09/2022] We win the "Best Geometry Award" at ATM Challenge of MICCAI 2022. (Congrats to Puyang!)
[07/2022] Five abstracts are accepted by RSNA 2022. (four oral presentations)
[07/2022] Invited to serve as Associate Editor for the journal of Frontiers in Nuclear Medicine (Radiomics and Artificial Intelligence Section)
[06/2022] Three abstracts are accepted by ASTRO 2022.
[06/2022] Two papers are accepted by MICCAI 2022. (One for lymph node segmentation and one for esophageal cancer screening, Congrats to Dazhou and Jiawen!)
[04/2022] One paper titled "SAM "on self-supervised anatomical embeddings is accepted by IEEE TMI. (Congrats to Ke!)
[12/2021] One paper on deep statistical shape modeling is accepted by AAAI 2022. (Congrats to Ashwim and Adam!)
[10/2021] One paper on multi-institutional validation of esophageal GTV segmentation is accepted by Frontiers in Oncology.
[09/2021] One paper on kidney cancer differentiation is accepted by Clinical Imaging.
[08/2021] Invited to serve as Senior Program Committee (SPC) Member for AAAI 2022.
[06/2021] Invited to serve as Associate Editor for the journal of Frontiers in Oncology (Cancer Imaging and Image-directed Interventions Section)
[06/2021] CVPR 2021 Outstanding Reviewer Award. (3 years in a row!)
[06/2021] Two papers are accepted by MICCAI 2021. (One for 12 lymph node station and 22 chest OAR parsing, one for unsupervised deformable registration)
[05/2021] Three abstracts are accepted by American Society for Radiation Oncology (ASTRO) 2021.
[02/2021] Guest Associate Editor for a special issue "Machine Learning for Quantitative Neuroimaging Analysis" in Frontiers in Neuroscience.
[12/2020] Invited to serve as Associate Editor for the journal of The Visual Computer.
[09/2020] One paper titled "DeepTarget" is accepted by Medical Image Analysis. (Special Issue of MICCAI-2019 Best Papers)
[08/2020] Three abstracts are accepted by RSNA 2020. (Two oral presentation)
[06/2020] Invited talk at the Medical Computer Vision Workshop @ CVPR 2020.
[05/2020] Three papers are accepted by MICCAI 2020. (All early accepts, one won MICCAI-2020 NIH Award)
[02/2020] One paper on 42 head & neck organs at risk segmentation is accepted by CVPR 2020.
[06/2019] Three papers are accepted by MICCAI 2019. (All early accepts, one for oral presentation)
[06/2019] One paper collaborated with NIAID is accepted by Science Translational Medicine. (IF:19.99; Highlighted on cover)
|
Publications
2024
[ECCV] Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer. Qinji Yu^, Yirui Wang^, Ke Yan, Haoshen Li, Dazhou Guo, Li Zhang, Le Lu, Na Shen, Qifeng Wang, Xiaowei Ding, Xianghua Ye,
Dakai Jin.
[IEE TMI] Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning. Puyang Wang, Dazhou Guo, Dandan Zheng, Minghui Zhang, Haogang Yu, Xin Sun, Jia Ge, Yun Gu, Le Lu, Xianghua Ye,
Dakai Jin.
[MICCAI] Slice-Consistent Lymph Nodes Detection Transformer in CT Scans via Cross-slice Query Contrastive Learning. Qinji Yu, Yirui Wang, Ke Yan, Le Lu, Na Shen, Xianghua Ye, Xiaowei Ding,
Dakai Jin.
[MICCAI] Semi-supervised Lymph Node Metastasis Classification with Pathology-guided Label Sharpening and Two-streamed Multi-scale Fusion. Haoshen Li, Yirui Wang, Jie Zhu, Dazhou Guo, Qinji Yu, Ke Yan, Le Lu, Xianghua Ye, Li Zhang, Qifeng Wang,
Dakai Jin.
[MICCAI] Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation. Vince Zhu, Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Yingda Xia, Le Lu, Xianghua Ye, Wei Zhu,
Dakai Jin.
[MICCAI] IHCSurv: Effective Immunohistochemistry Priors for Cancer Survival Analysis in Gigapixel Multi-stain Whole Slide Images. Yejia Zhang^, Hanqing Chao^, Zhongwei Qiu, Wenbin Liu, Yixuan Shen, Nishchal Sapkota, Pengfei Gu, Danny Z Chen, Le Lu, Ke Yan,
Dakai Jin, Yun Bian, Hui Jiang.
[Annals of American Thoracic Society] Vessel and Airway Characteristics in One-Year Computed Tomography–defined Rapid Emphysema Progression: SPIROMICS. Sarah Gerard^, Timothy Dougherty^,
Dakai Jin, MeiLan Han, John Newell Jr, Punam Saha, Alejandro Comellas, Christopher Cooper, David Couper, Spyridon Fortis, Junfeng Guo, Nadia Hansel, Richard Kanner, Ella Kazeroni, Fernando Martinez, Amin Motahari, Robert Paine, Stephen Rennard, Joyce Schroeder, Prescott Woodruff, Graham Barr, Benjamin Smith, Eric Hoffman.
2023
[ICCV] Continual segment: Towards a single, unified and non-forgetting continual segmentation model of 143 whole-body organs in ct scans. Zhanghexuan Ji^, Dazhou Guo^, Puyang Wang, Ke Yan, Le Lu, Minfeng Xu, Jingren Zhou, Qifeng Wang, Jia Ge, Mingchen Gao, Xianghua Ye,
Dakai Jin.
[IEE TMI] LViT: Language meets Vision Transformer in Medical Image Segmentation. Zihan Li, Yunxiang Li, Qingde Li, Puyang Wang, Dazhou Guo, Le Lu,
Dakai Jin, You Zhang, Qingqi Hong.
[MICCAI] SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid. Zi Li^, Lin Tian^, Tony C. W. Mok, Xiaoyu Bai, Puyang Wang, Jia Ge, Jingren Zhou, Le Lu, Xianghua Ye, Ke Yan,
Dakai Jin.
[MICCAI MLMI] Automated Coarse-to-fine Segmentation of Thoracic Duct using Anatomy Priors and Topology-guided Curved Planar Reformation. Puyang Wang, Panwen Hu, Jiali Liu, Hang Yu, Xianghua Ye, Jinliang Zhang, Hui Li, Li Yang, Le Lu,
Dakai Jin*, Fengming Kong*.
[MICCAI MMM] Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification. Ke Yan,
Dakai Jin, Dazhou Guo, Minfeng Xu, Na Shen, Xian-Sheng Hua, Xianghua Ye, Le Lu.
2022
[Nature Communications] Comprehensive and Clinically Accurate Head and Neck Cancer Organs-at-Risk Delineation on a Multi-Institutional Study. Xianghua Ye^, Dazhou Guo^, Jia Ge^, Senxiang Yan, Yi Xin, Yuchen Song, Yongheng Yan, Bing-shen Huang, Tsung-Min Hung, Zhuotun Zhu, Ling Peng, Yanping Ren, Rui Liu, Gong Zhang, Mengyuan Mao, Xiaohua Chen, Zhongjie Lu, Wenxiang Li, Yuzhen Chen, Lingyun Huang, Jing Xiao, Adam Harrison, Le Lu, Chien-Yu Lin*,
Dakai Jin*, Tsung-Ying Ho*.
[JNCC] Towards Automated Organs at Risk and Target Volumes Contouring: Defining Precision Radiation Therapy in the Modern Era. Dakai Jin, Dazhou Guo, Jia Ge, Xianghua Ye, Le Lu. (Invited reviewing article)
[MICCAI] Thoracic Lymph Node Segmentation in CT imaging via Lymph Node Station Stratification and Size Encoding. Dazhou Guo, Jia Ge, Ke Yan, Puyang Wang, Zhuotun Zhu, Dandan Zheng, Xiansheng Hua, Le Lu, Tsung-Ying Ho, Xianghua Ye,
Dakai Jin.
[MICCAI] Effective Opportunistic Esophageal Cancer Screening using Noncontrast CT Imaging. Jiawen Yao, Xianghua Ye, Yingda Xia, Jian Zhou, Yu Shi, Ke Yan, Fang Wang, Lisha Lin, Haogang Yu, Xiansheng Hua, Le Lu,
Dakai Jin, Ling Zhang.
[IEE TMI] SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images. Ke Yan, Jinzheng Cai,
Dakai Jin, Shun Miao, Adam P Harrison, Dazhou Guo, Youbao Tang, Jing Xiao, Jingjing Lu, Le Lu.
[pdf]
[AAAI] Deep implicit statistical shape models for 3d medical image delineation. Ashwin Raju, Shun Miao,
Dakai Jin, Le Lu, Junzhou Huang, Adam P Harrison.
[pdf]
2021
[Frontiers in Oncology] Multi-Institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume Using Planning CT and FDG-PET/CT. Xianghua Ye^, Dazhou Guo^, Chen-kan Tseng, Jia Ge, Tsung-Min Hung, Ping-Ching Pai, Yanping Ren, Lu Zheng, Xinli Zhu, Ling Peng, Ying Chen, Xiaohua Chen, Chen-Yu Chou, Danni Chen, Jiaze Yu, Yuzhen Chen, Feiran Jiao, Yi Xin, Lingyun Huang, Guotong Xie, Jing Xiao, Le Lu, Senxiang Yan,
Dakai Jin*, Tsung-Ying Ho*.
[pdf]
[Clinical Imaging] A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI. M. Nikpanah*, Z. Xu*,
D. Jin, F. Farhadi, A. Shafei, U. Hoang, M. Nikpanah, W. M. Linehan, E. C. Jones, D. J. Mollura, A. A. Malayeri.
[MICCAI] SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings. Fengze Liu*, Ke Yan*, Adam Harrison, Dazhou Guo, Le Lu, Alan Yuille, Lingyun Huang, Guotong Xie, Jing Xiao, Xianghua Ye,
Dakai Jin.
[MICCAI] DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search. Dazhou Guo*, Xianghua Ye*, Jia Ge, Xing Di, Le Lu, Lingyun Huang, Guotong Xie, Jing Xiao, Zhongjie Lu, Ling Peng, Senxiang Yan,
Dakai Jin.
[Frontiers in Radiology] CT-based risk factors for mortality of patients with COVID-19 Pneumonia in Wuhan, China: a retrospective study. Xiang Li*, Nannan Li*, Zhen Chen*, Ling Zhang*, Ling Ye*,
Dakai Jin, Liangxin Gao, Xinhui Liu, Bolin Lai, Jiawen Yao, Dazhou Guo, Hua Zhang, Le Lu, Jing Xiao, Lingyun Huang, Fen Ai, Xiang Wang.
[IEEE TMI] Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT. Ke Yan, Jinzheng Cai, Youjing Zheng, Adam P. Harrison,
Dakai Jin, You-Bao Tang, Yu-Xing Tang, Lingyun Huang, Jing Xiao, Le Lu.
[pdf]
2020
[Medical Image Analysis] DeepTarget: Gross Tumor and Clinical Target Volume Segmentation in Esophageal Cancer Radiotherapy. Dakai Jin*, Dazhou Guo*, Tsung-Ying Ho, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu.
[pdf] (MICCAI-2019 Best Papers Selection)
[Artificial Intelligence in Medicine: Technical Basis and Clinical Applications] Chapter 14: Artificial Intelligence in Radiology. Dakai Jin, Adam P. Harrison, Ling Zhang, Ke Yan, Yirui Wang, Jinzheng Cai, Shun Miao, Le Lu.
[pdf]
[European Radiology] From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans. Zhang Li*, Zheng Zhong*, Yang Li, Tianyu Zhang, Liangxin Gao,
Dakai Jin, Yue Sun, Xianghua Ye, Li Yu, Zheyu Hu, Jing Xiao, Lingyun Huang, Yuling Tang.
[pdf]
[MICCAI] Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy. Zhuotun Zhu,
Dakai Jin, Ke Yan, Tsung-Ying Ho, Xianghua Ye, Dazhou Guo, Chun-Hung Chao, Jing Xiao, Alan Yuille, Le Lu.
[pdf] (Early accept, MICCAI NIH-Award)
[MICCAI] Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network. Chun-Hung Chao, Zhuotun Zhu*, Dazhou Guo*, Ke Yan*, Tsung-Ying Ho, Jinzheng Cai, Adam P Harrison, Xianghua Ye, Jing Xiao, Alan Yuille, Min Sun, Le Lu,
Dakai Jin.
[pdf] (Early accept)
[MICCAI] Robust Pancreatic Ductal Adenocarcinoma Segmentation with Multi-institutional Multi-phase Partially-Annotated CT Scans. Ling Zhang, Yu Shi, Jiawen Yao, Yun Bian, Kai Cao,
Dakai Jin, Jing Xiao, Le Lu.
[pdf] (Early accept)
[ECCV] JSSR: A Joint Synthesis, Segmentation, and Registration System for 3D Multi-Modal Image Alignment of Large-scale Pathological CT Scans. Fengze Liu, Jinzheng Cai, Yuankai Huo, Chi-Tung Cheng, Ashwin Raju,
Dakai Jin, Jing Xiao, Alan Yuille, Le Lu, ChienHung Liao, Adam P Harrison.
[pdf]
[CVPR] Organ at Risk Segmentation for Head and Neck Cancer using Stratified Learning and Neural Architecture Search. Dazhou Guo,
Dakai Jin, Zhuotun Zhu, Tsung-Ying Ho, Adam P Harrison, Chun-Hung Chao, Jing Xiao, Le Lu.
[pdf]
2019
[MICCAI] Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT Using Two-Stream Chained 3D Deep Network Fusion. Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu.
[pdf] (Early accept and oral presentation)
[MICCAI] Deep Esophageal Clinical Target Volume Delineation Using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk. Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu.
[pdf] (Early accept)
[MICCAI] Weakly Supervised Universal Fracture Detection in Pelvic X-Rays. Yirui Wang, Le Lu, Chi-Tung Cheng,
Dakai Jin, Adam P Harrison, Jing Xiao, Chien-Hung Liao, Shun Miao.
[pdf] (Early accept)
[IEEE TMI] Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge. Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser, Rutger Heinen, Simon Andermatt, Mariana Bento, Matt Berseth, Mikhail Belyaev, M. Jorge Cardoso, Adrià Casamitjana, D. Louis Collins, Mahsa Dadar, Achilleas Georgiou, Mohsen Ghafoorian,
Dakai Jin, April Khademi, Jesse Knight, Hongwei Li, Xavier Lladó, Miguel Luna, Qaiser Mahmood, Richard McKinley, Alireza Mehrtash, Sébastien Ourselin, Bo-yong Park, Hyunjin Park, Sang Hyun Park, Simon Pezold, Elodie Puybareau, Leticia Rittner, Carole H. Sudre, Sergi Valverde, Verónica Vilaplana, Roland Wiest, Yongchao Xu, Ziyue Xu, Guodong Zeng, Jianguo Zhang, Guoyan Zheng, Christopher Chen, Wiesje van der Flier, Frederik Barkhof, Max A. Viergever, Geert Jan Biessels.
[pdf]
[JMI] Fully automated prostate whole gland and central gland segmentation on MRI using holistically nested networks with short connections . Ruida Cheng, Nathan Lay, Holger R Roth, Baris Turkbey,
Dakai Jin, William Gandler, Evan S McCreedy, Tom Pohida, Peter Pinto, Peter Choyke, Matthew J McAuliffe, Ronald M Summers.
[pdf]
[Science Translational Medicine] Lymphocyte-driven regional immunopathology in pneumonitis caused by impaired central immune tolerance. Elise MN Ferré, Timothy J Break, Peter D Burbelo, Michael Allgäuer, David E Kleiner,
Dakai Jin, Ziyue Xu, Les R Folio, Daniel J Mollura, Muthulekha Swamydas, Wenjuan Gu, Sally Hunsberger, Chyi-Chia R Lee, Anamaria Bondici, Kevin W Hoffman, Jean K Lim, Kerry Dobbs, Julie E Niemela, Thomas A Fleisher, Amy P Hsu, Laquita N Snow, Dirk N Darnell, Samar Ojaimi, Megan A Cooper, Martin Bozzola, Gary I Kleiner, Juan C Martinez, Robin R Deterding, Douglas B Kuhns, Theo Heller, Karen K Winer, Arun Rajan, Steven M Holland, Luigi D Notarangelo, Kevin P Fennelly, Kenneth N Olivier, Michail S Lionakis.
[pdf] (IF:19.99; Highlighted on cover)
2018
[MICCAI] CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation. Dakai Jin, Ziyue Xu, Youbao Tang, Adam P Harrison, Daniel J Mollura.
[pdf] (MICCAI 2018 top 10 highly cited paper)
[ISBI] White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections. Dakai Jin, Ziyue Xu, Adam P Harrison, Daniel J Mollura.
[pdf]
[IEEE TVCG] Fuzzy Object Skeletonization: Theory, Algorithms, and Applications. Punam K Saha (PhD advisor),
Dakai Jin, Yinxiao Liu, Gary E Christensen, Cheng Chen.
(One of the two major skeletonization algorithms I developed in my PhD. The top journal in the field of visualization and computer graphics)
[Medical Physics] Quantitative imaging of peripheral trabecular bone microarchitecture using MDCT. Cheng Chen, Xiaoliu Zhang, Junfeng Guo,
Dakai Jin, Elena M Letuchy, Trudy L Burns, Steven M Levy, Eric A Hoffman, Punam K Saha.
[pdf]
2017
[MLMI] 3D Convolutional Neural Networks with Graph Refinement for Airway Segmentation Using Incomplete Data Labels. Dakai Jin, Ziyue Xu, Adam P. Harrison, Kevin George, Daniel J. Mollura.
[pdf] (The first 3D deep learning algorithm on airway tree segmentation, and without the need of manual annotation)
[DLMIA] Pathological Pulmonary Lobe Segmentation from CT Images using Progressive Holistically Nested Neural Networks and Random Walker. Kevin George, Adam P. Harrison,
Dakai Jin, Ziyue Xu, Daniel J Mollura.
[pdf] (The first deep learning algorithm on the challenging lung lobe segmentation problem)
[Skeletonization: Theory, Methods and Applications] Chapter 6: Curve skeletonization using minimum-cost path. Dakai Jin, Cheng Chen, Eric A Hoffman, Punam K Saha.
[pdf]
2016
[Pattern Recognition Letters] A robust and efficient curve skeletonization algorithm for tree-like objects using minimum cost paths. Dakai Jin, Krishna S Iyer, Cheng Chen, Eric A Hoffman, Punam K Saha.
[pdf] (A very accurate and robust algorithm to extract the centerline/curve skeleton in 3D elongated structures!)
[American Journal of Respiratory and Critical Care Medicine] Quantitative Dual-Energy Computed Tomography Supports a Vascular Etiology of Smoking-induced Inflammatory Lung Disease . Krishna S Iyer, John D Newell,
Dakai Jin, Matthew K Fuld, Punam K Saha, Sif Hansdottir, Eric A Hoffman.
[pdf] (Top journal in Pulmonology, IF:30.5; Highlighted on cover)
[Physics in Medicine & Biology] Trabecular bone characterization on the continuum of plates and rods using in vivo MR imaging and volumetric topological analysis. Cheng Chen,
Dakai Jin, Yinxiao Liu , Felix W Wehrli, Gregory Chang, Peter J Snyder, Ravinder R Regatte, Punam K Saha.
[pdf]
[Medical Physics] A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS). Junfeng Guo, Chao Wang, Kung‐Sik Chan,
Dakai Jin, Punam K Saha, Jered P Sieren, R Graham Barr, MeiLan K Han, Ella Kazerooni, Christopher B Cooper, David Couper, John D Newell Jr, Eric A Hoffman, SPIROMICS Research Group.
[pdf]
2015
[Medical Physics] Automated cortical bone segmentation for multirow detector CT imaging with validation and application to human studies. Cheng Li,
Dakai Jin, Cheng Chen, Elena M Letuchy, Kathleen F Janz, Trudy L Burns, James C Torner, Steven M Levy, Punam K Saha.
[pdf]
[Medical Physics] Characterization of trabecular bone plate‐rod microarchitecture using multirow detector CT and the tensor scale: Algorithms, validation, and applications to pilot human studies. Punam K Saha, Yinxiao Liu, Cheng Chen,
Dakai Jin, Elena M Letuchy, Ziyue Xu, Ryan E Amelon, Trudy L Burns, James C Torner, Steven M Levy, Chadi A Calarge.
[pdf]
[ICIAP] Filtering Non-Significant Quench Points Using Collision Impact in Grassfire Propagation. Dakai Jin, Cheng Chen, Punam K Saha.
[pdf]
[ISVC] Fuzzy Skeletonization Improves the Performance of Characterizing Trabecular Bone Micro-architecture. Cheng Chen,
Dakai Jin, Punam K Saha.
2014
[IEEE TBME] A Robust Algorithm for Thickness Computation at Low Resolution and Its Application to In Vivo Trabecular Bone CT Imaging. Yinxiao Liu,
Dakai Jin, Cheng Li, Kathleen F Janz, Trudy L Burns, James C Torner, Steven M Levy, Punam K Saha.
[pdf]
[ICPR] A new approach of arc skeletonization for tree-like objects using minimum cost path. Dakai Jin, Krishna S Iyer, Eric A Hoffman, Punam K Saha.
[pdf]
[International Symposium on Visual Computing (ISVC)] Automated Assessment of Pulmonary Arterial Morphology in Multi-row Detector CT Imaging Using Correspondence with Anatomic Airway Branches. Dakai Jin, Krishna S Iyer, Eric A Hoffman, Punam K Saha.
[pdf] (Oral presentation)
2013
[International Conference on Image Analysis and Processing (ICIAP)] A New Fuzzy Skeletonization Algorithm and Its Applications to Medical Imaging. Dakai Jin and Punam K. Saha.
[pdf]
[ICIAP] A New Algorithm for Cortical Bone Segmentation with Its Validation and Applications to In Vivo Imaging. Cheng Li,
Dakai Jin, Trudy L Burns, James C Torner, Steven M Levy, Punam K Saha.
[pdf]
[ISBI] A new algorithm for trabecular bone thickness computation at low resolution achieved under in vivo condition. Yinxiao Liu,
Dakai Jin, Punam K Saha.
[pdf]
Editorial Services
Associate Editor
Guest Editor
Conference Area Chair or Senior Program Committee
-
AAAI 2022, AAAI 2024, AAAI 2025
Journal Reviewer
-
Nature Machine Intelligence, Nature Cardiovascular Research, IEEE T-PAMI, IEEE TMI, IEEE TBME, MedIA, IEEE JBHI, PR, PRL, Medical Physics, European Radiology
Conference Reviewer
-
ICML 2023, NeurIPS 2022, ICLR 2022/2023, CVPR 2019-2022, ECCV 2020, ICCV 2019/2021/2023, AAAI 2020/2022, ICIP 2017/2018, ICPR 2018, ICIAP 2017, DGCI 2016
-
MICCAI 2017-2024, ISBI 2017-2020, EMBC 2017
Awards
Invited Talks
-
Recent developments in deep learning based pulmonary image analysis, National Library of Medicine, Bethesda, MD. August 2018
-
Digital topology & geometry approaches in medical image analysis and deep learning, Radiology Department, National Institutes of Health, Bethesda, MD. January 2018
-
Deep learning and recently development s in medical image analysis and computer aided diagnosis, Computer Science Colloquium, Georgetown University, Washington, DC. April 2017
-
Machine learning in medical image analysis: basics and recent developments, Integrated Research Facility Department, National Institute of Allergy and Infectious Diseases, Frederick, MD. February 2017
-
Morphometric approaches for CT based characterization of airway and pulmonary vascular, ECE Graduate Seminar, University of Iowa, Iowa City, IA. September 2016
-
Fuzzy digital topology and geometry for quantitative structural analysis in medical imaging, IIBI Seminar, University of Iowa, Iowa City, IA. April 2014