Maciej A Mazurowski
Associate Professor in Radiology
Appointments and Affiliations
- Associate Professor in Radiology
- Associate Professor in the Department of Electrical and Computer Engineering
- Associate Professor in the Department of Electrical and Computer Engineering
- Associate Professor in Biostatistics and Bioinformatics
- Member of the Duke Cancer Institute
Contact Information
- Office Location: Dept Of Radiology, Durham, NC 27710
- Office Phone: (919) 684-1440
- Email Address: maciej.mazurowski@duke.edu
Education
- Ph.D. University of Louisville, 2008
Courses Taught
- BIOSTAT 824: Case Studies in Biomedical Data Science
- MEDPHY 762: Data Science
Representative Publications
- Zhang, J; Saha, A; Zhu, Z; Mazurowski, MA, Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics., Ieee Transactions on Medical Imaging, vol 38 no. 2 (2019), pp. 435-447 [10.1109/tmi.2018.2865671] [abs].
- Mazurowski, MA; Saha, A; Harowicz, MR; Cain, EH; Marks, JR; Marcom, PK, Association of distant recurrence-free survival with algorithmically extracted MRI characteristics in breast cancer., Journal of Magnetic Resonance Imaging : Jmri (2019) [10.1002/jmri.26648] [abs].
- Saha, A; Grimm, LJ; Ghate, SV; Kim, CE; Soo, MS; Yoon, SC; Mazurowski, MA, Machine learning-based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high-risk screening MRI., Journal of Magnetic Resonance Imaging : Jmri (2019) [10.1002/jmri.26636] [abs].
- Grimm, LJ; Saha, A; Ghate, SV; Kim, C; Soo, MS; Yoon, SC; Mazurowski, MA, Relationship between Background Parenchymal Enhancement on High-risk Screening MRI and Future Breast Cancer Risk., Academic Radiology, vol 26 no. 1 (2019), pp. 69-75 [10.1016/j.acra.2018.03.013] [abs].
- Cain, EH; Saha, A; Harowicz, MR; Marks, JR; Marcom, PK; Mazurowski, MA, Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set., Breast Cancer Research and Treatment (2018) [10.1007/s10549-018-4990-9] [abs].