Functional Tumor Volume by Fast Dynamic<scp>Contrast‐Enhanced MRI</scp>for Predicting Neoadjuvant Systemic Therapy Response in<scp>Triple‐Negative</scp>Breast CancerBenjamin C. Musall, Jingfei Ma, Jong Bum Son et al.|Journal of Magnetic Resonance Imaging|2021Cited by 30
Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRIBikash Panthi, Gaiane M. Rauch, Beatriz E. Adrada et al.|Cancers|2023Cited by 25
Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC)Abeer H. Abdelhafez, Gaiane M. Rauch, Benjamin C. Musall et al.|Breast Cancer Research and Treatment|2020Cited by 15
Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast CancerZhan Xu, Jingfei Ma, David E Rauch et al.|Cancers|2023Cited by 9
A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture AnalysisHai Shu, Olena Weaver, Ting-Yu D. Chiang et al.|Radiology Artificial Intelligence|2021Cited by 7