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 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
- Incubation Awards to Assist Seven Innovative Research Projects Move Toward the Market (Nov 25, 2019 | Innovation and Entrepreneurship)
Representative Publications
- Draelos, RL; Dov, D; Mazurowski, MA; Lo, JY; Henao, R; Rubin, GD; Carin, L, Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes., Med Image Anal, vol 67 (2021) [10.1016/j.media.2020.101857] [abs].
- 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].