Computerized analysis of sonograms for the detection of breast lesions. - Karen Drukker; Maryellen Lissak Giger; Karla Horsch; Carl J. Vyborny (Image Processing, 2002)

Computerized detection and classification of lesions on breast ultrasound. - Karen Drukker; Maryellen Lissak Giger; Carl J. Vyborny; Robert A. Schmidt; Ellen B. Mendelson; Michael Stern (Image Processing, 2003)

Computerized detection and 3-way classification of breast lesions on ultrasound images. - Karen Drukker; Darrin C. Edwards; Maryellen Lissak Giger; Robert M. Nishikawa; Charles E. Metz (Image Processing, 2004)

Character recognition and image manipulation for the clinical translation of CAD for breast ultrasound. - Nicholas Gruszauskas; Karen Drukker; Maryellen Lissak Giger (Image Processing, 2005)

Progress in Breast Cadx. - Maryellen L. Giger; Yading Yuan; Hui Li 024; Karen Drukker; Weijie Chen 007; Li Lan; Karla Horsch (ISBI, 2007)

The effect of image quality on the appearance of lesions on breast ultrasound: implications for CADx. - Karen Drukker; Charlene A. Sennett; Maryellen L. Giger (Computer-Aided Diagnosis, 2007)

An image database management system for conducting CAD research. - Nicholas Gruszauskas; Karen Drukker; Maryellen L. Giger (Computer-Aided Diagnosis, 2007)

Computerized self-assessment of automated lesion segmentation in breast ultrasound: implication for CADx applied to findings in the axilla. - Karen Drukker; Maryellen L. Giger (Computer-Aided Diagnosis, 2008)

A study of the effect of noise injection on the training of artificial neural networks. - Yulei Jiang; Richard M. Zur; Lorenzo L. Pesce; Karen Drukker (IJCNN, 2009)

Using three-class BANN classifier in the automated analysis of breast cancer lesions in DCE-MRI. - Neha Bhooshan; Maryellen L. Giger; Darrin C. Edwards; Karen Drukker; Sanaz Jansen; Hui Li 024; Li Lan; Gillian Newstead (Computer-Aided Diagnosis, 2009)

Principal component analysis, classifier complexity, and robustness of sonographic breast lesion classification. - Karen Drukker; Nicholas Gruszauskas; Maryellen L. Giger (Computer-Aided Diagnosis, 2009)

Automated Method for Improving System Performance of Computer-Aided Diagnosis in Breast Ultrasound. - Karen Drukker; Charlene A. Sennett; Maryellen L. Giger (IEEE Trans. Medical Imaging, 2009)

Performance of Triple-Modality CADx on Breast Cancer Diagnostic Classification. - Neha Bhooshan; Maryellen L. Giger; Karen Drukker; Yading Yuan; Hui Li 024; Stephanie McCann; Gillian Newstead; Charlene A. Sennett (Digital Mammography / IWDM, 2010)

Repeatability and classifier bias in computer-aided diagnosis for breast ultrasound. - Karen Drukker; Lorenzo L. Pesce; Maryellen L. Giger (Computer-Aided Diagnosis, 2010)

A Novel Hybrid Linear/Nonlinear Classifier for Two-Class Classification: Theory, Algorithm, and Applications. - Weijie Chen 007; Charles E. Metz; Maryellen L. Giger; Karen Drukker (IEEE Trans. Medical Imaging, 2010)

Breast image feature learning with adaptive deconvolutional networks. - Andrew R. Jamieson; Karen Drukker; Maryellen L. Giger (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)

Quantitative ultrasound image analysis of axillary lymph node status in breast cancer patients. - Karen Drukker; Maryellen L. Giger; Lina Arbash Meinel; Adam Starkey; Jyothi Janardanan; Hiroyuki Abe (Int. J. Comput. Assist. Radiol. Surg., 2013)

Compositional Three-Component Breast Imaging of Fibroadenoma and Invasive Cancer Lesions: Pilot Study. - Serghei Malkov; Fred Duewer; Karla Kerlikowske; Karen Drukker; Maryellen L. Giger; John Shepherd 002 (Digital Mammography / IWDM, 2014)

Roles of biologic breast tissue composition and quantitative image analysis of mammographic images in breast tumor characterization. - Karen Drukker; Maryellen L. Giger; Fred Duewer; Serghei Malkov; Christopher I. Flowers; Bonnie N. Joe; Karla Kerlikowske; Jennifer S. Drukteinis; John Shepherd 002 (Computer-Aided Diagnosis, 2014)

Energy Dependence of Water and Lipid Calibration Materials for Three-Compartment Breast Imaging. - Jesús Ávila; Serghei Malkov; Maryellen L. Giger; Karen Drukker; John A. Shepherd 002 (Digital Mammography / IWDM, 2016)

Calibration Procedure of Three Component Mammographic Breast Imaging. - Serghei Malkov; Jesús Ávila; Bo Fan 001; Bonnie N. Joe; Karla Kerlikowske; Maryellen L. Giger; Karen Drukker; Jennifer S. Drukteinis; Leila Kazemi; Malesa Pereira; John Shepherd 002 (Digital Mammography / IWDM, 2016)

Identification, segmentation, and characterization of microcalcifications on mammography. - Karen Drukker; Serghei Malkov; Jesús Ávila; Karla Kerlikowske; Bonnie N. Joe; Gregor Krings; Jennifer Creasman; Jennifer S. Drukteinis; Malesa M. Pereira; Leila Kazemi; John Shepherd 002; Maryellen L. Giger (Computer-Aided Diagnosis, 2016)

Deep learning and three-compartment breast imaging in breast cancer diagnosis. - Karen Drukker; Benjamin Q. Huynh; Maryellen L. Giger; Serghei Malkov; Jesús I. Ávila; Bo Fan 001; Bonnie N. Joe; Karla Kerlikowske; Jennifer S. Drukteinis; Leila Kazemi; Malesa M. Pereira; John Shepherd 002 (Computer-Aided Diagnosis, 2017)

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)

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)

Case-based repeatability of machine learning classification performance on breast MRI. - Michael Vieceli; Amy Van Dusen; Karen Drukker; Hiroyuki Abe; Maryellen L. Giger; Heather M. Whitney (Computer-Aided Diagnosis, 2020)

Repeatability profiles towards consistent sensitivity and specificity levels for machine learning on breast DCE-MRI. - Amy Van Dusen; Michael Vieceli; Karen Drukker; Hiroyuki Abe; Maryellen L. Giger; Heather M. Whitney (Image Perception, Observer Performance, and Technology Assessment, 2020)

Case-based diagnostic classification repeatability using radiomic features extracted from full-field digital mammography images of breast lesions. - Paul Amstutz; Karen Drukker; Hui Li 024; Hiroyuki Abe; Maryellen L. Giger; Heather M. Whitney (Computer-Aided Diagnosis, 2021)

Comparison of 2D and 3D U-Net breast lesion segmentations on DCE-MRI. - Roma Bhattacharjee; Lindsay Douglas; Karen Drukker; Qiyuan Hu; Jordan D. Fuhrman; Deepa Sheth; Maryellen L. Giger (Computer-Aided Diagnosis, 2021)

Role of standard and soft tissue chest radiography images in COVID-19 diagnosis using deep learning. - Qiyuan Hu; Karen Drukker; Maryellen L. Giger (Computer-Aided Diagnosis, 2021)

Comparison of diagnostic performances, case-based repeatability, and operating sensitivity and specificity in classification of breast lesions using DCE-MRI. - Michelle de Oliveira; Karen Drukker; Michael Vieceli; Hiroyuki Abe; Maryellen L. Giger; Heather M. Whitney (Image Perception, Observer Performance, and Technology Assessment, 2021)

Sequestration of imaging studies in MIDRC: a multi-institutional data commons. - Natalie M. Baughan; Heather M. Whitney; Karen Drukker; Berkman Sahiner; Tingting Hu; Hyun J. Grace Kim; Michael F. McNitt-Gray; Kyle J. Myers; Maryellen L. Giger (Image Perception, Observer Performance, and Technology Assessment, 2022)

Case-based repeatability and operating point variability of AI: breast lesion classification based on deep transfer learning. - Heather M. Whitney; Karen Drukker; Hiroyuki Abe; Maryellen L. Giger (Image Perception, Observer Performance, and Technology Assessment, 2022)

Longitudinal robustness of a thoracic radiographic AI model for COVID-19 severity prediction. - Karen Drukker; Hui Li 024; Maryellen L. Giger (Image Perception, Observer Performance, and Technology Assessment, 2023)

Assistance tools for the evaluation of machine learning algorithm performance: the decision tree-based tools developed by the Medical Imaging and Data Resource Center (MIDRC) Technology Development Project (TDP) 3c effort. - Karen Drukker; Berkman Sahiner; Tingting Hu; Hyun J. Grace Kim; Heather M. Whitney; Natalie M. Baughan; Kyle J. Myers; Maryellen L. Giger; Michael F. McNitt-Gray (Image Perception, Observer Performance, and Technology Assessment, 2023)

Investigation of demographic implicit discrimination and disparate impact in chest radiography image-based AI for COVID-19 severity prediction. - Heather M. Whitney; Hui Li 024; Karen Drukker; Michael Reeve; Maryellen L. Giger (Image Perception, Observer Performance, and Technology Assessment, 2023)

AI analysis of medical images at scale as a health disparities probe: a feasibility demonstration using chest radiographs. - Heather M. Whitney; Hui Li 024; Karen Drukker; Elbert Huang; Maryellen L. Giger (CoRR, 2025)