23 citations · 58 across the 9 of their papers we have counts for
9 papers
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…
Brain Foundation Models with Hypergraph Dynamic Adapter for Brain Disease Analysis
Zhongying Deng, Haoyu Wang, Ziyan Huang +6
Brain diseases, such as Alzheimer's disease and brain tumors, present profound challenges due to their complexity and societal impact. Recent advancements in brain foundation model…
Interactive Medical Image Segmentation: A Benchmark Dataset and Baseline
Junlong Cheng, Bin Fu, Jin Ye +10
Interactive Medical Image Segmentation (IMIS) has long been constrained by the limited availability of large-scale, diverse, and densely annotated datasets, which hinders model gen…
SegBook: A Simple Baseline and Cookbook for Volumetric Medical Image Segmentation
Jin Ye, Ying Chen, Yanjun Li +7
Computed Tomography (CT) is one of the most popular modalities for medical imaging. By far, CT images have contributed to the largest publicly available datasets for volumetric med…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
Enhancing Medical Task Performance in GPT-4V: A Comprehensive Study on Prompt Engineering Strategies
Pengcheng Chen, Ziyan Huang, Zhongying Deng +6
OpenAI's latest large vision-language model (LVLM), GPT-4V(ision), has piqued considerable interest for its potential in medical applications. Despite its promise, recent studies a…
SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks
Jin Ye, Junlong Cheng, Jianpin Chen +12
Segment Anything Model (SAM) has achieved impressive results for natural image segmentation with input prompts such as points and bounding boxes. Its success largely owes to massiv…
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
Haoyu Wang, Sizheng Guo, Jin Ye +11
Existing volumetric medical image segmentation models are typically task-specific, excelling at specific target but struggling to generalize across anatomical structures or modalit…
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
Ziyan Huang, Zhongying Deng, Jin Ye +11
Although deep learning have revolutionized abdominal multi-organ segmentation, models often struggle with generalization due to training on small, specific datasets. With the recen…