Profile Detail

Dooman Arefan, PhD

Research Assistant Professor
E-Mail:

Interest (in 3 to 10 words): Research

Education

Medical / Graduate School	B.Sc. in Electrical/Computer Engineering M.Sc. in Medical Imaging Engineering (Radiation Medicine) Ph.D. in Medical Imaging Engineering (Radiation Medicine)
Residency
Clinical / Post-doctoral Fellowship	Postdoctoral Associate, Department of Radiology, University of Pittsburgh
Current	Radiological Society of North America (2017 - Present)
Specialties & Programs	MR CT Ultrasound Nuclear Medicine Clinical Translational Digital Imaging
Clinical Interest	Artificial Intelligence (AI), Machine learning (ML), and Deep learning in medical imaging
Research Interest	Deep learning for predicting breast cancer risk using normal mammograms. Machine leaning/Radiomics analysis in breast cancer to predict Oncotype DX gene test outcomes using breast MRI scans. Radiomics/Radiogenomics analysis in predicting cell line invasion in breast tumor micro-environment (TME). Automatic breast tumor segmentation in DCE-MRI. Automatic breast density classification. Deep learning to predict outcomes in severe traumatic brain injury patients using head CT/MRI scans.
Selected Publications	1.Matthew Pease, Dooman Arefan, Jason Barber, Esther Yuh, Ava Puccio, Kerri Hochberger, Enyinna Nwachuku, Souvik Roy, Stephanie Casillo, Nancy Temkin, David Okonkwo, Shandong Wu, Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans, Radiology, Feb. 23, 2022. (* equal first-authorship). 2.Dooman Arefan, Ryan M. Hausler, Jules H. Sumkin, Min Sun, and Shandong Wu. "Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes." BMC cancer 21, no. 1 (2021): 1-9. 3.Dooman Arefan, Ruimei Chai, Min Sun, Margarita L. Zuley, and Shandong Wu. "Machine learning prediction of axillary lymph node metastasis in breast cancer: 2D versus 3D radiomic features." Medical Physics 47, no. 12 (2020): 6334-6342. 4.Dooman Arefan, Aly A. Mohamed, Wendie A. Berg, Margarita L. Zuley, Jules H. Sumkin, and Shandong Wu. "Deep learning modeling using normal mammograms for predicting breast cancer risk." Medical physics 47, no. 1 (2020): 110-118. (An Editors Choice article).
Honors and Awards	The RSNA Trainee Research Prize, Recipient of the Dr Tapan K. Chaudhuri Trainee Research Prize In memory of Tandra R. Chaudhuri, PhD, and Tamasa R. Mallik, BA, (2019). Awarded a "Georg Forster Research Fellowship", by the Selection Committee, Germany (2017).
PubMed Publications	See a listing of publications on PubMed, a service of the National Library of medicine.