1 citations · 2 across the 3 of their papers we have counts for
4 papers · 1 filter
ReXGroundingCT: A 3D Chest CT Dataset for Segmentation of Findings from Free-Text Reports
Mohammed Baharoon, Luyang Luo, Michael Moritz +22
We introduce ReXGroundingCT, the first publicly available dataset linking free-text findings to pixel-level 3D segmentations in chest CT scans. The dataset includes 3,142 non-contr…
Exploring the Design Space of 3D MLLMs for CT Report Generation
Mohammed Baharoon, Jun Ma, Congyu Fang +2
Multimodal Large Language Models (MLLMs) have emerged as a promising way to automate Radiology Report Generation (RRG). In this work, we systematically investigate the design space…
MedSAM2: Segment Anything in 3D Medical Images and Videos
Jun Ma, Zongxin Yang, Sumin Kim +6
Medical image and video segmentation is a critical task for precision medicine, which has witnessed considerable progress in developing task or modality-specific and generalist mod…
Segment Anything in Medical Images and Videos: Benchmark and Deployment
Jun Ma, Sumin Kim, Feifei Li +4
Recent advances in segmentation foundation models have enabled accurate and efficient segmentation across a wide range of natural images and videos, but their utility to medical da…