activity
20202025
most citedA Cascaded Residual UNET for Fully Automated Segmentation of Prostate and Peripheral Zone in T2-weighted 3D Fast Spin Echo Images

4 citations · 6 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2025

Context-aware deep learning using individualized prior information reduces false positives in disease risk prediction and longitudinal health assessment

Lavanya Umapathy, Patricia M Johnson, Tarun Dutt +4

Temporal context in medicine is valuable in assessing key changes in patient health over time. We developed a machine learning framework to integrate diverse context from prior vis…

cs.CV2022

Learning to segment with limited annotations: Self-supervised pretraining with regression and contrastive loss in MRI

Lavanya Umapathy, Zhiyang Fu, Rohit Philip +3

Obtaining manual annotations for large datasets for supervised training of deep learning (DL) models is challenging. The availability of large unlabeled datasets compared to labele…

cs.CV2020★ 4 cited

A Cascaded Residual UNET for Fully Automated Segmentation of Prostate and Peripheral Zone in T2-weighted 3D Fast Spin Echo Images

Lavanya Umapathy, Wyatt Unger, Faryal Shareef +4

Multi-parametric MR images have been shown to be effective in the non-invasive diagnosis of prostate cancer. Automated segmentation of the prostate eliminates the need for manual a…

eess.IV2020

White matter hyperintensities volume and cognition: Assessment of a deep learning based lesion detection and quantification algorithm on the Alzheimers Disease Neuroimaging Initiative

Lavanya Umapathy, Gloria Guzman Perez-Carillo, Blair Winegar +3

The relationship between cognition and white matter hyperintensities (WMH) volumes often depends on the accuracy of the lesion segmentation algorithm used. As such, accurate detect…

cs.LG2020

A Contrast Synthesized Thalamic Nuclei Segmentation Scheme using Convolutional Neural Networks

Lavanya Umapathy, Mahesh Bharath Keerthivasan, Natalie M. Zahr +2

Thalamic nuclei have been implicated in several neurological diseases. WMn-MPRAGE images have been shown to provide better intra-thalamic nuclear contrast compared to conventional…

eess.IV2020★ 2 cited

A Comparison of Deep Learning Convolution Neural Networks for Liver Segmentation in Radial Turbo Spin Echo Images

Lavanya Umapathy, Mahesh Bharath Keerthivasan, Jean-Phillipe Galons +4

Motion-robust 2D Radial Turbo Spin Echo (RADTSE) pulse sequence can provide a high-resolution composite image, T2-weighted images at multiple echo times (TEs), and a quantitative T…