8 citations · 9 across the 4 of their papers we have counts for
4 papers
Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging
Darryl E. Wright, Adriana V. Gregory, Deema Anaam +14
Uterine leiomyosarcoma (LMS) is a rare but aggressive malignancy. On imaging, it is difficult to differentiate LMS from, for example, degenerated leiomyoma (LM), a prevalent but be…
Role of Image Acquisition and Patient Phenotype Variations in Automatic Segmentation Model Generalization
Timothy L. Kline, Sumana Ramanathan, Harrison C. Gottlich +2
Purpose: This study evaluated the out-of-domain performance and generalization capabilities of automated medical image segmentation models, with a particular focus on adaptation to…
AI in the Loop -- Functionalizing Fold Performance Disagreement to Monitor Automated Medical Image Segmentation Pipelines
Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory +1
Methods for automatically flag poor performing-predictions are essential for safely implementing machine learning workflows into clinical practice and for identifying difficult cas…
Predicting 1p19q Chromosomal Deletion of Low-Grade Gliomas from MR Images using Deep Learning
Zeynettin Akkus, Issa Ali, Jiri Sedlar +5
Objective: Several studies have associated codeletion of chromosome arms 1p/19q in low-grade gliomas (LGG) with positive response to treatment and longer progression free survival.…