40 citations · 47 across the 11 of their papers we have counts for
6 papers · 1 filter
OrganLens: Organ-Specific Representation Learning for CT Foundation Models
Zhixuan Ge, Anqi Li, Sadeer Al-Kindi +2
A CT examination captures multiple organs, but many biomedical questions concern abnormalities, prognosis, or longitudinal change in a specific organ. These questions require a sep…
GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis
Naoto Usuyama, Jeya Maria Jose Valanarasu, Sicong Yao +27
Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatment selection by learning trans…
A multi-agent system for spine MRI report generation from multi-sequence imaging
Zhiping Xiao, Junwei Yang, Gongbo Sun +12
Spinal pathology is a leading cause of pain and disability worldwide. Spine MRI is central to clinical evaluation, yet its interpretation remains complex and time-consuming, requir…
MicroDiffuse3D: A Foundation Model for 3D Microscopy Imaging Restoration
Yongkang Li, Brian Wong, King Wai Chiu +5
Chemical imaging enables label-free visualization of cells, tissues and living systems while providing direct biochemical information that is difficult to obtain with conventional…
PathReasoning: A multimodal reasoning agent for query-based ROI navigation on whole-slide images
Kunpeng Zhang, Hanwen Xu, Sheng Wang
Deciphering tumor microenvironment from Whole Slide Images (WSIs) is intriguing as it is key to cancer diagnosis, prognosis and treatment response. While these gigapixel images on…
When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology
Wenhui Wang, Shuming Ma, Hanwen Xu +4
This technical report presents LongViT, a vision Transformer that can process gigapixel images in an end-to-end manner. Specifically, we split the gigapixel image into a sequence o…