399 citations · 4.5k across the 84 of their papers we have counts for
84 papers
Segmentation by Test-Time Optimization (TTO) for CBCT-based Adaptive Radiation Therapy
Xiao Liang, Jaehee Chun, Howard Morgan +4
Online adaptive radiotherapy (ART) requires accurate and efficient auto-segmentation of target volumes and organs-at-risk (OARs) in mostly cone-beam computed tomography (CBCT) imag…
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…
Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks
Maryam Mashayekhi, Itzel Ramirez Tapia, Anjali Balagopal +6
Typically, the current dose prediction models are limited to small amounts of data and require re-training for a specific site, often leading to suboptimal performance. We propose…
Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy
Jaehee Chun, Justin C. Park, Sven Olberg +5
In this study, we propose a tailored DL framework for patient-specific performance that leverages the behavior of a model intentionally overfitted to a patient-specific training da…
Deep learning-based COVID-19 pneumonia classification using chest CT images: model generalizability
Dan Nguyen, Fernando Kay, Jun Tan +5
Since the outbreak of the COVID-19 pandemic, worldwide research efforts have focused on using artificial intelligence (AI) technologies on various medical data of COVID-19-positive…
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,…