1 citations · 1 across the 4 of their papers we have counts for
4 papers
Adapting Foundation Models for Annotation-Efficient Adnexal Mass Segmentation in Cine Images
Francesca Fati, Alberto Rota, Adriana V. Gregory +9
Adnexal mass evaluation via ultrasound is a challenging clinical task, often hindered by subjective interpretation and significant inter-observer variability. While automated segme…
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…