Maciej A Mazurowski

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 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
  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 899: Special Readings in Electrical Engineering
  • MEDPHY 762: Data Science

In the News

Representative Publications

  • Devalapalli, A; Thomas, S; Mazurowski, MA; Saha, A; Grimm, LJ, Performance of preoperative breast MRI based on breast cancer molecular subtype., Clin Imaging, vol 67 (2020), pp. 130-135 [10.1016/j.clinimag.2020.05.017] [abs].
  • Wildman-Tobriner, B; Ahmed, S; Erkanli, A; Mazurowski, MA; Hoang, JK, Using the American College of Radiology Thyroid Imaging Reporting and Data System at the Point of Care: Sonographer Performance and Interobserver Variability., Ultrasound Med Biol, vol 46 no. 8 (2020), pp. 1928-1933 [10.1016/j.ultrasmedbio.2020.04.019] [abs].
  • Hou, R; Mazurowski, MA; Grimm, LJ; Marks, JR; King, LM; Maley, CC; Hwang, E-SS; Lo, JY, Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation., Ieee Trans Biomed Eng, vol 67 no. 6 (2020), pp. 1565-1572 [10.1109/TBME.2019.2940195] [abs].
  • Buda, M; Wildman-Tobriner, B; Castor, K; Hoang, JK; Mazurowski, MA, Deep Learning-Based Segmentation of Nodules in Thyroid Ultrasound: Improving Performance by Utilizing Markers Present in the Images., Ultrasound Med Biol, vol 46 no. 2 (2020), pp. 415-421 [10.1016/j.ultrasmedbio.2019.10.003] [abs].
  • Swiecicki, A; Buda, M; Saha, A; Li, N; Ghate, SV; Walsh, R; Mazurowski, MA, Generative adversarial network-based image completion to identify abnormal locations in digital breast tomosynthesis images, Progress in Biomedical Optics and Imaging Proceedings of Spie, vol 11314 (2020) [10.1117/12.2551379] [abs].