activity
20172026
most citedThe Medical Segmentation Decathlon

1.3k citations · 2k across the 59 of their papers we have counts for

collaborators
Showing 2026Show all

7 papers · 1 filter

cs.CV2026

Semi-Supervised Virtual Staining via Morphology Preservation and Histopathological Realism Constraints

Baoshun Wang, Weiping Lin, Linwu Wang +3

Virtual staining aims to computationally generate target-stained histopathological images while reducing the cost and time associated with conventional staining procedures. However…

cs.AI2026

PathView-Bench: Can Multimodal Large Language Models Achieve Fine-grained Multiscale Understanding of Pathology Images?

Zongyi Chen, Yu Liang, Jie Lin +1

Multimodal large language models (MLLMs) are increasingly used to analyze pathology images. However, dominant multimodal benchmarks in pathology mainly score final diagnostic answe…

cs.CV2026

Evaluating Agentic Harness Systems for Autonomous Computational Pathology

Jie Lin, Zongyi Chen, Qiaoling Zheng +6

Autonomous computational pathology (ACP) converts high-level pathology analysis goals into executable, traceable and clinically bounded workflows. Realizing this capability require…

cs.CV2026

Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development

Zhongying Deng, Cheng Tang, Ziyan Huang +124

Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…

cs.CV2026★ 4 cited

Federated Modality-specific Encoders and Partially Personalized Fusion Decoder for Multimodal Brain Tumor Segmentation

Hong Liu, Dong Wei, Qian Dai +3

Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to multimodal imaging applications.…

cs.CV2026

Structure Observation Driven Image-Text Contrastive Learning for Computed Tomography Report Generation

Hong Liu, Dong Wei, Qiong Peng +4

Computed Tomography Report Generation (CTRG) aims to automate the clinical radiology reporting process, thereby reducing the workload of report writing and facilitating patient car…

cs.CV2026

A multi-center analysis of deep learning methods for video polyp detection and segmentation

Noha Ghatwary, Pedro Chavarias Solano, Mohamed Ramzy Ibrahim +24

Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during colonoscopy. However, the variability in appearance, location, and size of these…