About me[My CV]

• I am a 4th-year PhD student in the School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, co-advised by Prof. Guotai Wang and Prof. Shaoting Zhang.
• My research mainly focuses on medical image analysis, particularly in data-efficient learning for medical image computing, such as semi-supervised learning, weakly-supervised learning and human-in-the-loop, and extending them for practical clinical applications.
• I received my Bachelor’s Degree in the School of Mechanical and Electrical Engineering at University of Electronic Science and Technology of China on July 1, 2018.
• I am looking for collaborators on AI for oncology radiotherapy (OARs, GTV and CTV delineation; prognosis prediction, etc.). We have collected several large-scale datasets to develop AI models and research benchmarks (more than 3000 patients with ~ 80 organ/tissue/tumor and clinical informations from multi-center have been collected and annotated manually). If you have any interest, please feel free to contact me.

Recent News

• May 19, 2023, A clinical paper about automatic organs at risk segmentation on heterogeneous computed tomography images for abdominal radiotherapy was accepted by International Journal of Radiation Oncology*Biology*Physics (also named RedJournal, one of the top-tier journals in the radiation and oncology field, double-blind review), congratulate M.D. Wenjun Liao.
• Apr. 10, 2023, We will host an automatic segmentation challenge SegRap2023 at MICCAI2023 focusing on GTVnx, GTVnd, and 45 OARs segmentation for nasopharyngeal carcinoma radiotherapy planning. Welcome to participate in it.
• Mar. 23, 2023, Our paper Towards Multi-Center Cross Tissues Histopathological Cell Segmentation via Target-Specific Finetuning was accepted by IEEE Transaction on Medical Imaging, congrats to Dr. Zhongyu Li.
• Jan. 9, 2023, Our paper Deep learning-based accurate and robust delineation of primary gross tumor volumes of nasopharyngeal carcinoma on heterogeneous magnetic resonance imaging: a large-scale and multi-center study was accepted by Radiation and Oncology (also named GreenJournal, one of the top-tier journals in the radiation and oncology field), thanks to all co-authors, code and paper are available.
• Sep. 20, 2022, Our paper WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image was accepted by Medical Image Analysis, thanks to all co-authors, dataset and paper are available.
• July 12, 2022, Our project SSL4MIS received the 1000th star, a milestone moment for us; keep going!!!
• Jun 30, 2022, Our MICCAI2022 paper (WSL4MIS) was selected to receive a MICCAI2022 Student Travel Award.
• Jun 10, 2022, Our paper Semi-Supervised Medical Image Segmentation via Uncertainty Rectified Pyramid Consistency was accepted by Medical Image Analysis, thanks to all co-authors, code and paper are available.
• May 5, 2022, Our paper Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision was provisionally accepted by MICCAI2022 (top 13% in total 1825 submissions), thanks to all co-authors, code and paper are available.
• Mar. 25, 2022, A clinical paper about semi-supervised Gross Target Volume (GTVnx and GTVnd) of Nasopharyngeal Carcinoma (NPC) segmentation was accepted by International Journal of Radiation Oncology*Biology*Physics (also named RedJournal, one of the top-tier journals in the radiation and oncology field, double-blind review), this work is a clinical applicable study of our work MICCAI2021, congratulate M.D. Wenjun Liao.
• Mar. 8, 2022, We have done a comprehensive study about scribble-supervised medical image segmentation based on the ACDC dataset, where more than ten weakly-/semi-supervised methods are tested on the same setting (five-fold cross-validation). The tech report and Code are available.
• Mar. 1, 2022, Our paper Semi-Supervised Medical Image Segmentation via Cross Teaching between CNN and Transformer was accepted by MIDL2022, thanks to all co-authors, code and paper are available.
• Oct. 21, 2021, Our paper SCPM-Net:An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching was accepted by Medical Image Analysis, thanks to all co-authors, code and paper are available.
• Aug. 29, 2021, We released a 2D inference code and GUI of MIDeepSeg (published in MedIA2021), the repo at MIDeepSeg.
• Jun. 21, 2021, I have joined Shanghai AI Lab as a research intern.
• Jun. 12, 2021, Two co-authors papers were accepted by MICCAI 2021 (~33% acceptance rate) after the rebuttal, congratulate all collaborators.
• May 14, 2021, Our paper Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency was early accepted by MICCAI2021 (top 13% in total 1630 submissions), thanks to all co-authors.
• May 06, 2021, Our paper MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning was accepted by Medical Image Analysis, thanks to all co-authors, code and paper.
• April 29, 2021, One co-author paper Medical Image Segmentation using Squeeze-and-Expansion Transformers was accepted by IJCAI2021 (~13% acceptance rate), congratulate Dr. Shaohua Li.
• Jan. 25, 2021, We released a code base and some 2D examples for weakly-supervised medical image segmentation research, the repo at WSL4MIS, any advices and suggestions are welcomed.
• Jan. 08, 2021, Our paper Deep Elastica for Image Segmentation was accepted by ISBI 2021.
• Dec. 01, 2020. Our paper Semi-supervised Medical Image Segmentation through Dual-task Consistency was accepted by AAAI 2021 (~21% acceptance rate).
• Oct. 07, 2020. We released a code base and some examples (both 2D and 3D) for semi-supervised medical image segmentation research, the repo at SSL4MIS, any advices and suggestions are welcomed.