output
20202025
most citedWORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

176 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

7 papers

physics.med-ph2025★ 17 cited

TrackRAD2025 challenge dataset: Real-time tumor tracking for MRI-guided radiotherapy

Yiling Wang, Elia Lombardo, Adrian Thummerer +25

Purpose: Magnetic resonance imaging (MRI) to visualize anatomical motion is becoming increasingly important when treating cancer patients with radiotherapy. Hybrid MRI-linear accel…

cs.LG2025★ 2 cited

Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer Prognosis

Yonghao Zhao, Changtao Li, Chi Shu +7

Survival prognosis is crucial for medical informatics. Practitioners often confront small-sized clinical data, especially cancer patient cases, which can be insufficient to induce…

cs.CV2024★ 3 cited

Weakly Supervised Lymph Nodes Segmentation Based on Partial Instance Annotations with Pre-trained Dual-branch Network and Pseudo Label Learning

Litingyu Wang, Yijie Qu, Xiangde Luo +3

Assessing the presence of potentially malignant lymph nodes aids in estimating cancer progression, and identifying surrounding benign lymph nodes can assist in determining potentia…

eess.IV2021★ 176 cited

WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image

Xiangde Luo, Wenjun Liao, Jianghong Xiao +7

Whole abdominal organ segmentation is important in diagnosing abdomen lesions, radiotherapy, and follow-up. However, oncologists' delineating all abdominal organs from 3D volumes i…

eess.IV2021★ 4 cited

Automatic Segmentation of Organs-at-Risk from Head-and-Neck CT using Separable Convolutional Neural Network with Hard-Region-Weighted Loss

Wenhui Lei, Haochen Mei, Zhengwentai Sun +7

Nasopharyngeal Carcinoma (NPC) is a leading form of Head-and-Neck (HAN) cancer in the Arctic, China, Southeast Asia, and the Middle East/North Africa. Accurate segmentation of Orga…

eess.IV2021

Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention

Haochen Mei, Wenhui Lei, Ran Gu +4

Radiotherapy is the main treatment modality for nasopharynx cancer. Delineation of Gross Target Volume (GTV) from medical images such as CT and MRI images is a prerequisite for rad…

cs.CV2020★ 24 cited

Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency

Xiangde Luo, Wenjun Liao, Jieneng Chen +6

Gross Target Volume (GTV) segmentation plays an irreplaceable role in radiotherapy planning for Nasopharyngeal Carcinoma (NPC). Despite that Convolutional Neural Networks (CNN) hav…