11 citations · 19 across the 11 of their papers we have counts for
8 papers · 1 filter
The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT $\unicode{x2013}$ Multitracer Multicenter Generalization
Jakob Dexl, Katharina Jeblick, Andreas Mittermeier +27
We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body PET/CT under a compositional generaliza…
FL-MedSegBench: A Comprehensive Benchmark for Federated Learning on Medical Image Segmentation
Meilu Zhu, Zhiwei Wang, Axiu Mao +4
Federated learning (FL) offers a privacy-preserving paradigm for collaborative medical image analysis without sharing raw data. However, the absence of standardized benchmarks for…
MedPruner: Training-Free Hierarchical Token Pruning for Efficient 3D Medical Image Understanding in Vision-Language Models
Shengyuan Liu, Zanting Ye, Yunrui Lin +6
While specialized Medical Vision-Language Models (VLMs) have achieved remarkable success in interpreting 2D and 3D medical modalities, their deployment for 3D volumetric data remai…
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
Shengyuan Liu, Liuxin Bao, Qi Yang +6
Medical image segmentation is evolving from task-specific models toward generalizable frameworks. Recent research leverages Multi-modal Large Language Models (MLLMs) as autonomous…
EndoBench: A Comprehensive Evaluation of Multi-Modal Large Language Models for Endoscopy Analysis
Shengyuan Liu, Boyun Zheng, Wenting Chen +5
Endoscopic procedures are essential for diagnosing and treating internal diseases, and multi-modal large language models (MLLMs) are increasingly applied to assist in endoscopy ana…
Spatial-temporal Hierarchical Reinforcement Learning for Interpretable Pathology Image Super-Resolution
Wenting Chen, Jie Liu, Tommy W. S. Chow +1
Pathology image are essential for accurately interpreting lesion cells in cytopathology screening, but acquiring high-resolution digital slides requires specialized equipment and l…
Medical Image Synthesis via Fine-Grained Image-Text Alignment and Anatomy-Pathology Prompting
Wenting Chen, Pengyu Wang, Hui Ren +4
Data scarcity and privacy concerns limit the availability of high-quality medical images for public use, which can be mitigated through medical image synthesis. However, current me…
Fine-Grained Image-Text Alignment in Medical Imaging Enables Explainable Cyclic Image-Report Generation
Wenting Chen, Linlin Shen, Jingyang Lin +3
To address these issues, we propose a novel Adaptive patch-word Matching (AdaMatch) model to correlate chest X-ray (CXR) image regions with words in medical reports and apply it to…