activity
20202022
most citedA deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy

12 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20221 cited

Prior Guided Deep Difference Meta-Learner for Fast Adaptation to Stylized Segmentation

Anjali Balagopal, Dan Nguyen, Ti Bai +3

When a pre-trained general auto-segmentation model is deployed at a new institution, a support framework in the proposed Prior-guided DDL network will learn the systematic differen…

cs.LG20223 cited

Uncertainty estimations methods for a deep learning model to aid in clinical decision-making -- a clinician's perspective

Michael Dohopolski, Kai Wang, Biling Wang +5

Prediction uncertainty estimation has clinical significance as it can potentially quantify prediction reliability. Clinicians may trust 'blackbox' models more if robust reliability…

eess.IV2022

Region Specific Optimization (RSO)-based Deep Interactive Registration

Ti Bai, Muhan Lin, Xiao Liang +5

Medical image registration is a fundamental and vital task which will affect the efficacy of many downstream clinical tasks. Deep learning (DL)-based deformable image registration…

cs.CV20211 cited

A Proof-of-Concept Study of Artificial Intelligence Assisted Contour Revision

Ti Bai, Anjali Balagopal, Michael Dohopolski +7

Automatic segmentation of anatomical structures is critical for many medical applications. However, the results are not always clinically acceptable and require tedious manual revi…

cs.CV20211 cited

PSA-Net: Deep Learning based Physician Style-Aware Segmentation Network for Post-Operative Prostate Cancer Clinical Target Volume

Anjali Balagopal, Howard Morgan, Michael Dohopoloski +9

Automatic segmentation of medical images with DL algorithms has proven to be highly successful. With most of these algorithms, inter-observer variation is an acknowledged problem,…

eess.IV202012 cited

A deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy

Anjali Balagopal, Dan Nguyen, Howard Morgan +9

In post-operative radiotherapy for prostate cancer, the cancerous prostate gland has been surgically removed, so the clinical target volume (CTV) to be irradiated encompasses the m…