Matthew B. Morgan
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Matthew B. Morgan, MD, MS

Languages spoken: English, Spanish

Clinical Locations

Primary Location

Huntsman Cancer Institute - Cancer Hospital North

2K, Gynecology and Mammography
1950 Circle of Hope
Salt Lake City , UT 84112
801-581-5496
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I specialize in breast imaging. I use mammography, ultrasound, MRI, and PET/CT to detect cancer and other breast conditions. The goal of screening is to find cancer early, when treatment options are broader and long-term outcomes are better.

My patients include women coming in for a routine screening mammogram, women with a family history who need closer surveillance, women already diagnosed who are being staged or monitored through treatment, and women with benign conditions such as infections or masses that need follow-up.

Often I am the first cancer specialist a patient meets, and that influences my approach. I explain what I see on the images and what the next steps are, which may include referral to genetic counseling or oncology. If something on an exam looks suspicious, I perform a biopsy. When cancer is present, I map its full extent for the surgical team and place the markers that show exactly where it sits, so it can be removed precisely.

At the University of Utah/Huntsman Cancer Hospital, we offer the latest technologies to all our patients. This includes digital breast tomosynthesis, an advanced three-dimensional technology that helps improve our ability to detect breast cancer. We also use breast MRI to screen high-risk women and to evaluate how much disease is present in patients with cancer.

I teach medical students, residents, and fellows. My research is on artificial intelligence in breast cancer risk and detection, and how to use it to screen women according to their individual risk rather than a single schedule for everyone. I serve as Medical Director of Breast Imaging IT and Innovation.

Specialties

Board Certification

American Board of Radiology (Diagnostic Radiology)

I specialize in breast imaging. I use mammography, ultrasound, MRI, and PET/CT to detect cancer and other breast conditions. The goal of screening is to find cancer early, when treatment options are broader and long-term outcomes are better.

My patients include women coming in for a routine screening mammogram, women with a family history who need closer surveillance, women already diagnosed who are being staged or monitored through treatment, and women with benign conditions such as infections or masses that need follow-up.

Often I am the first cancer specialist a patient meets, and that influences my approach. I explain what I see on the images and what the next steps are, which may include referral to genetic counseling or oncology. If something on an exam looks suspicious, I perform a biopsy. When cancer is present, I map its full extent for the surgical team and place the markers that show exactly where it sits, so it can be removed precisely.

At the University of Utah/Huntsman Cancer Hospital, we offer the latest technologies to all our patients. This includes digital breast tomosynthesis, an advanced three-dimensional technology that helps improve our ability to detect breast cancer. We also use breast MRI to screen high-risk women and to evaluate how much disease is present in patients with cancer.

I teach medical students, residents, and fellows. My research is on artificial intelligence in breast cancer risk and detection, and how to use it to screen women according to their individual risk rather than a single schedule for everyone. I serve as Medical Director of Breast Imaging IT and Innovation.

Board Certification and Academic Information

Academic Departments Radiology & Imaging Sciences -Associate Professor (Clinical)
Biomedical Informatics -Adjunct Assistant Professor
Board Certification
American Board of Radiology (Diagnostic Radiology)

Education history

Fellowship Breast Imaging - UPMC Magee-Women's Hospital Fellow
Residency Radiology - University of Pittsburgh Medical Center (UPMC) Resident
Fellowship Imaging Informatics - University of Pittsburgh Medical Center (UPMC) Fellow
Internship Transitional Internship - Sacred Heart Medical Center Intern
Professional Medical Medicine - University of Utah M.D.
Graduate Training Medical Informatics - University of Utah M.S.
Undergraduate Business Management/Information Systems - Brigham Young University B.S.

Selected Publications

Journal Article

  1. Kitamura F, Kline T, Warren D, Moy L, Daneshjou R, Maleki F, Santos I, Gichoya J, Wiggins W, Bialecki B, ODonnell K, Flanders AE, Morgan M, Safdar N, Andriole KP, Geis R, Allen B, Dreyer K, Lungren M, Wood MJ, Kohli M, Langer S, Shih G, Farina E, Kahn CE Jr, Reiser I, Giger M, Wald C, Mongan J, Cook T, Tenenholtz N (2025). Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM. Radiol Artif Intell, 7(6), e250137.
  2. Kitamura F, Kline T, Warren D, Moy L, Daneshjou R, Maleki F, Santos I, Gichoya J, Wiggins W, Bialecki B, ODonnell K, Flanders AE, Morgan M, Safdar N, Andriole KP, Geis R, Allen B, Dreyer K, Lungren M, Wood MJ, Kohli M, Langer S, Shih G, Farina E, Kahn CE Jr, Reiser I, Giger M, Wald C, Mongan J, Cook T, Tenenholtz N (2025). Teaching AI for Radiology Applications: a Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM. J Imaging Inform Med.
  3. Kitamura F, Kline T, Warren D, Moy L, Daneshjou R, Maleki F, Santos I, Gichoya J, Wiggins W, Bialecki B, ODonnell K, Flanders AE, Morgan M, Safdar N, Andriole KP, Geis R, Allen B, Dreyer K, Lungren M, Wood MJ, Kohli M, Langer S, Shih G, Farina E, Kahn CE Jr, Reiser I, Giger M, Wald C, Mongan J, Cook T, Tenenholtz N (2025). Teaching AI for Radiology Applications: A Multisociety‑Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM. Med Phys, 52(10), e17779.
  4. Morgan MB, Mates JL (2022). Ethics of Artificial Intelligence in Breast Imaging. J Breast Imaging, 5(2), 195-200.
  5. Winkler N, Braden S, Al-Dulaimi R, Morgan M, Walczak C, Freer P (2021). Perceptions Regarding Optimal Breast Imaging Education for Radiology Residents: Results of a National Survey. Curr Probl Diagn Radiol, 51(4), 454-459.
  6. Morgan MB, Mates JL (2020). Applications of Artificial Intelligence in Breast Imaging. Radiol Clin North Am, 59(1), 139-148.
  7. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, Langer SG, Borondy Kitts A, Birch J, Shields WF, van den Hoven van Genderen R, Kotter E, Wawira Gichoya J, Cook TS, Morgan MB, Tang A, Safdar NM, Kohli M (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. Radiology, 293(2), 436-440.
  8. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, Langer SG, Kitts AB, Birch J, Shields WF, van den Hoven van Genderen R, Kotter E, Gichoya JW, Cook TS, Morgan MB, Tang A, Safdar NM, Kohli M (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. J Am Coll Radiol, 16(11), 1516-1521.
  9. Geis JR, Brady AP, Wu CC, Spencer J, Ranschaert E, Jaremko JL, Langer SG, Kitts AB, Birch J, Shields WF, van den Hoven van Genderen R, Kotter E, Gichoya JW, Cook TS, Morgan MB, Tang A, Safdar NM, Kohli M (2019). Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement. Can Assoc Radiol J, 70(4), 329-334.
  10. Geis JR, Brady A, Wu CC, Spencer J, Ranschaert E, Jaremko JL, Langer SG, Kitts AB, Birch J, Shields WF, van den Hoven van Genderen R, Kotter E, Gichoya JW, Cook TS, Morgan MB, Tang A, Safdar NM, Kohli M (2019). Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement. Insights Imaging, 10(1), 101.
  11. Haider I, Morgan M, McGow A, Stein M, Rezvani M, Freer P, Hu N, Fajardo L, Winkler N (2018). Comparison of Breast Density Between Synthesized Versus Standard Digital Mammography. J Am Coll Radiol, 15(10), 1430-1436.
  12. Kohli M, Morrison JJ, Wawira J, Morgan MB, Hostetter J, Genereaux B, Hussain M, Langer SG (2017). Creation and Curation of the Society of Imaging Informatics in Medicine Hackathon Dataset. J Digit Imaging, 31(1), 9-12.
  13. Morgan MB, Young E, Harada S, Winkler N, Riegert J, Jones T, Hu N, Stein M (2017). Ditching the Disc: The Effects of Cloud-Based Image Sharing on Department Efficiency and Report Turnaround Times in Mammography. J Am Coll Radiol, 14(12), 1560-1565.
  14. Morgan MB, Meenan CD, Safdar NM, Nagy P, Flanders AE (2014). Informatics leaders in radiology: who they are and why you need them. J Am Coll Radiol, 11(12 Pt B), 1241-50.
  15. Morgan MB, Branstetter BF 4th, Clark C, House J, Baker D, Harnsberger HR (2011). Just-in-time radiologist decision support: the importance of PACS-integrated workflow. J Am Coll Radiol, 8(7), 497-500.
  16. Morgan MB, Branstetter BF 4th, Lionetti DM, Richardson JS, Chang PJ (2008). The radiology digital dashboard: effects on report turnaround time. J Digit Imaging, 21(1), 50-8.
  17. Mates J, Branstetter BF, Morgan MB, Lionetti DM, Chang PJ (2007). 'Wet Reads' in the age of PACS: technical and workflow considerations for a preliminary report system. J Digit Imaging, 20(3), 296-306.
  18. Branstetter BF 4th, Morgan MB, Nesbit CE, Phillips JA, Lionetti DM, Chang PJ, Towers JD (2006). Preliminary reports in the emergency department: is a subspecialist radiologist more accurate than a radiology resident? Acad Radiol, 14(2), 201-6.
  19. Morgan MB, Branstetter BF 4th, Mates J, Chang PJ (2006). Flying blind: using a digital dashboard to navigate a complex PACS environment. J Digit Imaging, 19(1), 69-75.
  20. Morgan M, Mates J, Chang P (2006). Toward a user-driven approach to radiology software solutions: Putting the wag back in the dog. J Digit Imaging.

Book Chapter

  1. Morgan MB, Branstetter BF (2021). Quality Improvement and Workflow Engineering. In Barton F. Branstetter, IV (Eds.), Practical Imaging Informatics (2nd Edition, pp. 409-424). New York: Springer.
  2. Morgan MB (2019). Breast Carcinoma. In Shabaan AM (Ed.), Diagnostic Imaging: Oncology (2nd Edition). Elsevier.

Letter

  1. Factor RE, Schmidt RL, Chadwick BE, Witt BJ, Morgan M, Neumayer LA, Layfield LJ (2015). Axillary lymph node FNA in women with breast cancer is a highly accurate procedure, so why are core biopsies being done? [Letter to the editor]. Diagn Cytopathol, 43(6), 510-2.
  2. Branstetter BF, Morgan MB (2008). Letter to the editor re: "The radiology digital dashboard: effects on report turnaround time.". [Letter to the editor]. J Digit Imaging, 22(2), 103.