activity
20202026
most citedTransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

4k citations · 4.5k across the 31 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

eess.IV2023★ 10 cited

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Xiangde Luo, Jia Fu, Yunxin Zhong +39

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is c…

cs.CV2023

Dual-Reference Source-Free Active Domain Adaptation for Nasopharyngeal Carcinoma Tumor Segmentation across Multiple Hospitals

Hongqiu Wang, Jian Chen, Shichen Zhang +6

Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that predominantly impacts the head and neck area. Precise delineation of the Gross Tumor Volume…

cs.CV2023

Scribble-based 3D Multiple Abdominal Organ Segmentation via Triple-branch Multi-dilated Network with Pixel- and Class-wise Consistency

Meng Han, Xiangde Luo, Wenjun Liao +3

Multi-organ segmentation in abdominal Computed Tomography (CT) images is of great importance for diagnosis of abdominal lesions and subsequent treatment planning. Though deep learn…

cs.CV2023★ 1 cited

ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding

Zihan Li, Yuan Zheng, Xiangde Luo +2

Medical image segmentation plays a critical role in clinical decision-making, treatment planning, and disease monitoring. However, accurate segmentation of medical images is challe…

cs.CV2023★ 23 cited

MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset

Guotai Wang, Jianghao Wu, Xiangde Luo +3

Pretraining with large-scale 3D volumes has a potential for improving the segmentation performance on a target medical image dataset where the training images and annotations are l…