activity
20182022
most citedA deep learning-based framework for segmenting invisible clinical target volumes with estimated uncertainties for post-operative prostate cancer radiotherapy

12 citations · 22 across the 7 of their papers we have counts for

collaborators

11 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…

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…

physics.med-ph2021

Dosimetric impact of physician style variations in contouring CTV for post-operative prostate cancer: A deep learning-based simulation study

Anjali Balagopal, Dan Nguyen, Maryam Mashayekhi +6

Inter-observer variation is a significant problem in clinical target volume(CTV) segmentation in postoperative settings, where there is no gross tumor present. In this scenario, th…

physics.med-ph20203 cited

A comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks

Dan Nguyen, Azar Sadeghnejad Barkousaraie, Gyanendra Bohara +4

Recently, artificial intelligence technologies and algorithms have become a major focus for advancements in treatment planning for radiation therapy. As these are starting to becom…

physics.med-ph20203 cited

Dose Prediction with Deep Learning for Prostate Cancer Radiation Therapy: Model Adaptation to Different Treatment Planning Practices

Roya Norouzi Kandalan, Dan Nguyen, Nima Hassan Rezaeian +5

This work aims to study the generalizability of a pre-developed deep learning (DL) dose prediction model for volumetric modulated arc therapy (VMAT) for prostate cancer and to adap…