collaborators

15 papers

cs.CV2026

A Unified 2D Framework for DeepLesion Detection, Segmentation and Short Report Generation

Ruida Cheng, Tejas S. Mathai, Benjamin Hou +4

In previous work, we integrated large language models (LLMs) into the lesion segmentation model based on the ULS23 DeepLesion dataset, using short-form findings from the reports. I…

cs.CV2026

CT-Bench: A Benchmark for Multimodal Lesion Understanding in Computed Tomography

Qingqing Zhu, Qiao Jin, Tejas S. Mathai +10

Artificial intelligence (AI) can automatically delineate lesions on computed tomography (CT) and generate radiology report content, yet progress is limited by the scarcity of publi…

cs.CV2025

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…

cs.CV2025

Utility of Pancreas Surface Lobularity as a CT Biomarker for Opportunistic Screening of Type 2 Diabetes

Tejas Sudharshan Mathai, Anisa V. Prasad, Xinya Wang +6

Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disease that affects millions of people worldwide. Early detection is crucial as it can alter pancreas function through morph…

eess.IV2025

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…

eess.IV2025

Classification of Multi-Parametric Body MRI Series Using Deep Learning

Boah Kim, Tejas Sudharshan Mathai, Kimberly Helm +2

Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrec…