collaborators

8 papers

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…

eess.IV2025

Segment-and-Classify: ROI-Guided Generalizable Contrast Phase Classification in CT Using XGBoost

Benjamin Hou, Tejas Sudharshan Mathai, Pritam Mukherjee +3

Purpose: To automate contrast phase classification in CT using organ-specific features extracted from a widely used segmentation tool with a lightweight decision tree classifier. M…

cs.CV2025

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.…

eess.IV2025

Longitudinal Assessment of Lung Lesion Burden in CT

Tejas Sudharshan Mathai, Benjamin Hou, Ronald M. Summers

In the U.S., lung cancer is the second major cause of death. Early detection of suspicious lung nodules is crucial for patient treatment planning, management, and improving outcome…

eess.IV2025

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…

eess.IV2025

Leveraging Multiphase CT for Quality Enhancement of Portal Venous CT: Utility for Pancreas Segmentation

Xinya Wang, Tejas Sudharshan Mathai, Boah Kim +1

Multiphase CT studies are routinely obtained in clinical practice for diagnosis and management of various diseases, such as cancer. However, the CT studies can be acquired with low…