Relevance vector machine for automatic detection of clustered microcalcifications. - Liyang Wei; Yongyi Yang; Robert M. Nishikawa; Miles N. Wernick; Alexandra Edwards (IEEE Trans. Medical Imaging, 2005)

Evaluation of a 3D lesion segmentation algorithm on DBT and breast CT images. - Ingrid S. Reiser; S. P. Joseph; Robert M. Nishikawa; Maryellen L. Giger; John M. Boone; Karen K. Lindfors; Alexandra Edwards; Nathan J. Packard; Richard H. Moore; Daniel B. Kopans (Computer-Aided Diagnosis, 2010)

Level Set Breast Mass Segmentation in Contrast-Enhanced and Non-Contrast-Enhanced Breast CT. - Hsien-Chi Kuo; Maryellen L. Giger; Ingrid S. Reiser; John M. Boone; Karen K. Lindfors; Kai Yang; Alexandra Edwards (Digital Mammography / IWDM, 2012)

Evaluation of stopping criteria for level set segmentation of breast masses in contrast-enhanced dedicated breast CT. - H. Kuo; Maryellen L. Giger; Ingrid S. Reiser; John M. Boone; Karen K. Lindfors; K. Yang; Alexandra Edwards (Computer-Aided Diagnosis, 2012)

Automatic 3D lesion segmentation on breast ultrasound images. - Hsien-Chi Kuo; Maryellen L. Giger; Ingrid S. Reiser; Karen Drukker; Alexandra Edwards; Charlene A. Sennett (Computer-Aided Diagnosis, 2013)

Level Set Segmentation of Breast Masses in Contrast-Enhanced Dedicated Breast CT and Evaluation of Stopping Criteria. - Hsien-Chi Kuo; Maryellen L. Giger; Ingrid S. Reiser; John M. Boone; Karen K. Lindfors; Kai Yang; Alexandra Edwards (J. Digit. Imaging, 2014)

Effect of biopsy on the MRI radiomics classification of benign lesions and luminal A cancers. - Heather M. Whitney; Karen Drukker; Alexandra Edwards; John Papaioannou; Maryellen L. Giger (IWBI, 2018)

Radiomics for ultrafast dynamic contrast-enhanced breast MRI in the diagnosis of breast cancer: a pilot study. - Karen Drukker; Rachel Anderson; Alexandra Edwards; John Papaioannou; Fred Pineda; Hiroyuki Abe; Gregory Karzcmar; Maryellen L. Giger (Computer-Aided Diagnosis, 2018)

Robustness of radiomic breast features of benign lesions and luminal A cancers across MR magnet strengths. - Heather M. Whitney; Karen Drukker; Alexandra Edwards; John Papaioannou; Maryellen L. Giger (Computer-Aided Diagnosis, 2018)

Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. - Karen Drukker; Iman El-Bawab; Alexandra Edwards; Christopher Doyle; John Papaioannou; Kirti Kulkarni; Maryellen L. Giger (Computer-Aided Diagnosis, 2019)

Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancer. - Qiyuan Hu; Heather M. Whitney; Alexandra Edwards; John Papaioannou; Maryellen L. Giger (Computer-Aided Diagnosis, 2019)

Effect of diversity of patient population and acquisition systems on the use of radiomics and machine learning for classification of 2, 397 breast lesions. - Heather M. Whitney; Yu Ji; Hui Li 024; Alexandra Edwards; John Papaioannou; Peifang Liu; Maryellen L. Giger (Computer-Aided Diagnosis, 2019)

Deep learning predicts breast cancer recurrence in analysis of consecutive MRIs acquired during the course of neoadjuvant chemotherapy. - Karen Drukker; Alexandra Edwards; John Papaioannou; Maryellen L. Giger (Computer-Aided Diagnosis, 2020)

Association between DCE MRI background parenchymal enhancement and mammographic texture features. - Natalie M. Baughan; Lindsay Douglas; Maya Ballard; Esther Seoyeon Lee; Alexandra Edwards; Li Lan; Hui Li 024; Maryellen L. Giger (Computer-Aided Diagnosis, 2022)

Influence of magnet strength on background parenchymal enhancement evaluation. - Lindsay Douglas; Trisha Mondal; Alexandra Edwards; Maryellen L. Giger (Image Perception, Observer Performance, and Technology Assessment, 2023)