Perelman School of Medicine at the University of Pennsylvania

Section for Biomedical Image Analysis (SBIA)

participating with CBICA

Hamed Akbari, MD, PhD

Research Scientist

Section of Biomedical Image Analysis
Center for Biomedical Image Computing & Analytics
Department of Radiology
Perelman School of Medicine
University of Pennsylvania

Richards Medical Research Laboratories, Floor 7
3700 Hamilton Walk
Philadelphia, PA 19104
fax: (001) 215.573.1811

Educational Background

Ph.D. in Mechano-Micro Engineering (Robotic surgery),   - Tokyo Institute of Technology, Tokyo, Japan
M.D. in Medicine- Tehran University of Medical sciences, Tehran, Iran

Research Summary

I currently work on radiogenomics and multi-parametric imaging pattern analysis to predict tumor infiltration and subsequent location of recurrence of glioblastoma. I extract imaging phenotypes of glioblastoma from multiple MRI modalities to determine the molecular tumor characteristics.

Short Bio

Over the past several years, my research efforts have focused on medical image processing and image guided medical procedures. I received my PhD in Mechano-Micro Engineering with focus on Robotic surgery from the Tokyo Institute of Technology after graduation from the medical school at the Tehran University of Medical Sciences. I have worked on MRI, CT scans, ultrasound and laparoscopic images and also hyperspectral images in human and animal subjects to detect different abnormal tissues, mainly cancerous and ischemic tissues and blood vessels. I currently work as a Research Scientist in Department of Radiology at University of Pennsylvania. I work on multi-parametric imaging pattern analysis and radiogenomics in brain tumors to define tumor infiltration and patients’ prognosis.

Representative Publications

  • Akbari H, Macyszyn L, Da X, Bilello M, Wolf RL, Martinez-Lage M, Biros G, Alonso-Basanta M, O'Rourke DM, Davatzikos C. Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma. Neurosurgery. 2016 Apr 1;78(4):572-80.
  • Akbari H, Macyszyn L, Da X, Wolf RL, Bilello M, Verma R, O’Rourke DM, Davatzikos C. Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity. Radiology. 2014 Jun 19;273(2):502-10.
  • Macyszyn L, Akbari H, Pisapia JM, Da X, Attiah M, Pigrish V, Bi Y, Pal S, Davuluri RV, Roccograndi L, Dahmane N. Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques. Neuro-oncology. 2016 Mar 1;18(3):417-25.
  • Akbari H, Halig LV, Schuster DM, Osunkoya A, Master V, Nieh PT, Chen GZ, Fei B. Hyperspectral imaging and quantitative analysis for prostate cancer detection. Journal of biomedical optics. 2012 Jul 1;17(7):0760051-0.
  • Akbari H, Fei B. 3D ultrasound image segmentation using wavelet support vector machines. Medical Physics. 2012 Jun 1;39(6):2972-84.
  • Akbari H, Uto K, Kosugi Y, Kojima K, Tanaka N. Cancer detection using infrared hyperspectral imaging. Cancer science. 2011 Apr 1;102(4):852-7.
  • Akbari H, Kosugi Y, Kojima K, Tanaka N. Detection and analysis of the intestinal ischemia using visible and invisible hyperspectral imaging. IEEE Transactions on Biomedical Engineering. 2010 Aug;57(8):2011-7.

For a full list of publications you can go to: