Hatef Mehrabian, PhD
Postdoctoral Research Fellow
Sunnybrook Research Institute
University of Toronto
Research Interests and Experiences
I have been working in the field of imaging and image processing since
final year of my B.Sc program. I am mostly interested in combining the physics of the imaged phenomenon with mathematical
image processing techniques to better understand and analyze the image.
My current research field is factor analysis of dynamic contrast enhanced
images. Factor analysis tries to extract functional information about the images by breaking down the image into a few
segments (Factor images) and extracting their corresponding behavior curves (Factor curves). I have developed a factor
analysis algorithm that incorporates the a priori information about the physics of contrast enhancement (Pharmacokinetic
modeling of the organ of interest) with a purely data driven factor analysis technique (Independent Component Analysis) to
generate physiologically meaningful images and curves which as the same time carry maximum amount of information about the
image. Applying this new constrained ICA algorithm shows better results compared to either purely data driven or purely model
based analyses. For more information please refer to my talk
at the Sunnybrook Health Sciences Centre.
I worked on Elastography during my master's program. Elastography is imaging
mechanical properties of soft tissues in order to detect any abnormality in the body and also to diagnose type of the
abnormality. I worked on modeling the tissue using non-linear (Hyperelastic) models, which provide more realistic models of
the imaged soft tissue compared to the classical Elastography techniques that assume a linear model for the tissue[PDF]. I
demonstrated the feasibility of using non-linear models of soft tissues for abnormality detection and diagnosis[PDF]. I also
developed an optical flow based large motion estimation technique for soft tissue displacement measurement via taking
advantage of the mechanical model of the tissue[PDF]. For more information you can refer to my
master's thesis or check my
thesis defense talk at University of Western Ontario.
My undergraduate thesis was on Iris Recognition which is one of the most
accurate and non-duplicable personal identification techniques. I developed a feature extraction algorithm based on
orientations of Gabor filter and Daubechies2 wavelet transform[PDF]. This feature is used in a matching algorithm to recognize
identity of the person based on his/her eye scan. I developed a Graph Cut based segmentation technique for segmenting pupil
area from the rest of the eye[PDF]. I also developed a robust segmentation technique for segmenting Iris region from the rest of
the eye[PDF]. For more information please refer to my publication or if you can read Persian, you may check my B.Sc thesis
(University of Tehran).