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:


  • Ph.D. University of Louisville, 2008

Courses Taught

  • BIOSTAT 824: Case Studies in Biomedical Data Science
  • MEDPHY 762: Data Science

Representative Publications

  • Mazurowski, MA; Buda, M; Saha, A; Bashir, MR, Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI., Journal of Magnetic Resonance Imaging : Jmri, vol 49 no. 4 (2019), pp. 939-954 [10.1002/jmri.26534] [abs].
  • Euler, A; Solomon, J; Mazurowski, MA; Samei, E; Nelson, RC, How accurate and precise are CT based measurements of iodine concentration? A comparison of the minimum detectable concentration difference among single source and dual source dual energy CT in a phantom study., European Radiology, vol 29 no. 4 (2019), pp. 2069-2078 [10.1007/s00330-018-5736-0] [abs].
  • Ho, LM; Samei, E; Mazurowski, MA; Zheng, Y; Allen, BC; Nelson, RC; Marin, D, Can Texture Analysis Be Used to Distinguish Benign From Malignant Adrenal Nodules on Unenhanced CT, Contrast-Enhanced CT, or In-Phase and Opposed-Phase MRI?, Ajr. American Journal of Roentgenology, vol 212 no. 3 (2019), pp. 554-561 [10.2214/ajr.18.20097] [abs].
  • 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].