Semantic Instance Segmentation of Kidney Cysts in MR Images: A Fully Automated 3D Approach Developed Through Active Learning. - Adriana V. Gregory; Deema A. Anaam; Andrew J. Vercnocke; Marie E. Edwards; Vicente E. Torres; Peter C. Harris; Bradley J. Erickson; Timothy L. Kline (J. Digit. Imaging, 2021)

AI in the Loop - Functionalizing Fold Performance Disagreement to Monitor Automated Medical Image Segmentation Pipelines. - Harrison C. Gottlich; Panagiotis Korfiatis; Adriana V. Gregory; Timothy L. Kline (CoRR, 2023)

Role of Image Acquisition and Patient Phenotype Variations in Automatic Segmentation Model Generalization. - Timothy L. Kline; Sumana Ramanathan; Harrison C. Gottlich; Panagiotis Korfiatis; Adriana V. Gregory (CoRR, 2023)

Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging. - Darryl E. Wright; Adriana V. Gregory; Deema A. Anaam; Sepideh Yadollahi; Sumana Ramanathan; Kafayat A. Oyemade; Reem Alsibai; Heather Holmes; Harrison C. Gottlich; Cherie-Akilah G. Browne; Sarah L. Cohen Rassier; Isabel Green; et al. (CoRR, 2023)

Effect of Dataset Size and Medical Image Modality on Convolutional Neural Network Model Performance for Automated Segmentation: A CT and MR Renal Tumor Imaging Study. - Harrison C. Gottlich; Adriana V. Gregory; Vidit Sharma; Abhinav Khanna; Amr U. Moustafa; Christine M. Lohse; Theodora A. Potretzke; Panagiotis Korfiatis; Aaron M. Potretzke; Aleksandar Denic; Andrew D. Rule; Naoki Takahashi; et al. (J. Digit. Imaging, 2023)