7 papers
UNIStainNet: Foundation-Model-Guided Virtual Staining of H&E to IHC
Jillur Rahman Saurav, Thuong Le Hoai Pham, Pritam Mukherjee +3
Virtual immunohistochemistry (IHC) staining from hematoxylin and eosin (H&E) images can accelerate diagnostics by providing preliminary molecular insight directly from routine sect…
Text Embedded Swin-UMamba for DeepLesion Segmentation
Ruida Cheng, Tejas Sudharshan Mathai, Pritam Mukherjee +5
Segmentation of lesions on CT enables automatic measurement for clinical assessment of chronic diseases (e.g., lymphoma). Integrating large language models (LLMs) into the lesion s…
A Study of Anatomical Priors for Deep Learning-Based Segmentation of Pheochromocytoma in Abdominal CT
Tanjin Taher Toma, Tejas Sudharshan Mathai, Bikash Santra +11
Accurate segmentation of pheochromocytoma (PCC) in abdominal CT scans is essential for tumor burden estimation, prognosis, and treatment planning. It may also help infer genetic cl…
Benchmarking Multi-Organ Segmentation Tools for Multi-Parametric T1-weighted Abdominal MRI
Nicole Tran, Anisa Prasad, Yan Zhuang +6
The segmentation of multiple organs in multi-parametric MRI studies is critical for many applications in radiology, such as correlating imaging biomarkers with disease status (e.g.…
Leveraging Anatomical Priors for Automated Pancreas Segmentation on Abdominal CT
Anisa V. Prasad, Tejas Sudharshan Mathai, Pritam Mukherjee +2
An accurate segmentation of the pancreas on CT is crucial to identify pancreatic pathologies and extract imaging-based biomarkers. However, prior research on pancreas segmentation…
LEAVS: An LLM-based Labeler for Abdominal CT Supervision
Ricardo Bigolin Lanfredi, Yan Zhuang, Mark Finkelstein +7
Extracting structured labels from radiology reports has been employed to create vision models to simultaneously detect several types of abnormalities. However, existing works focus…