Xiangde Luo

Xiangde Luo

I am a researcher focused on medical image analysis

Xiangde Luo

About me

  • I am a research assistant at West China Hospital of Sichuan University for developing clinical target volume delineation tools for oncology radiation therapy, working with Prof.Kang Li.
  • I received PhD and Bachelor’s Degrees in the School of Mechanical and Electrical Engineering at University of Electronic Science and Technology of China in 2024 and 2018 respectively.

Recent News

  • On June 17, 2024, Three papers were accepted to MICCAI2024 (two early acceptances), one about the robustness segmentation of abdominal organs (RAOS) and two about source-free active domain adaptation (SFADA-UWF-SLO and UGTST), congrats to Hongqiu, Zihao, Zihan.
  • June 6, 2024, A paper about source-free active domain adaptation for NPC GTVp segmentation across multiple hospitals (ArXiv) was accepted by IEEE Transaction on Medical Imaging, congrats to Mr. Hongqiu Wang.
  • I passed my PhD defence on May 28, 2024!
  • 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. 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 advice 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 advice and suggestions are welcomed.