activity
20242026
most citedWeakly Supervised Lymph Nodes Segmentation Based on Partial Instance Annotations with Pre-trained Dual-branch Network and Pseudo Label Learning

3 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2026

SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Jia Fu, Litingyu Wang, He Li +27

Accurate delineation of Gross Tumor Volume (GTV), Lymph Node Clinical Target Volume (LN CTV), and Organ-at-Risk (OAR) from Computed Tomography (CT) scans is essential for precise r…

cs.CV2025

OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models

Lanfeng Zhong, Xin Liao, Shichuan Zhang +2

Pathology image classification plays a crucial role in accurate medical diagnosis and treatment planning. Training high-performance models for this task typically requires large-sc…

cs.CV2025

Dynamic Gradient Sparsification Training for Few-Shot Fine-tuning of CT Lymph Node Segmentation Foundation Model

Zihao Luo, Zijun Gao, Wenjun Liao +3

Accurate lymph node (LN) segmentation is critical in radiotherapy treatment and prognosis analysis, but is limited by the need for large annotated datasets. While deep learning-bas…

cs.CV2025

CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation

Xiaochuan Ma, Jia Fu, Wenjun Liao +2

Brain tumor segmentation is important for diagnosis of the tumor, and current deep-learning methods rely on a large set of annotated images for training, with high annotation costs…

eess.IV2024

Head and Neck Tumor Segmentation of MRI from Pre- and Mid-radiotherapy with Pre-training, Data Augmentation and Dual Flow UNet

Litingyu Wang, Wenjun Liao, Shichuan Zhang +1

Head and neck tumors and metastatic lymph nodes are crucial for treatment planning and prognostic analysis. Accurate segmentation and quantitative analysis of these structures requ…

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…

cs.CV2024

VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Annotation-Free Pathological Image Classification

Lanfeng Zhong, Zongyao Huang, Yang Liu +4

Classification of pathological images is the basis for automatic cancer diagnosis. Despite that deep learning methods have achieved remarkable performance, they heavily rely on lab…