Estimation of tissue deformation in medical images

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We have seen a significant increase in the use of computers in medicine in the past decade. Extensive use of medical image analysis techniques has helped clinicians transcend many limitations of conventional medicine. The focus of my research lies in the same paradigm: to develop novel medical image analysis techniques that are reliable for clinical use. More specifically, my research program involves the development of novel computing techniques for ultrasound (US) elastography and fusion/registration of US images to magnetic resonance (MR) and computed tomography (CT).******US is an easy-to-use, inexpensive, real-time and safe imaging modality. This relatively young medical imaging modality is also one of the most frequently used, and is rapidly growing. In fact, numerous new research projects have recently been translated into commercial products. This research proposal has two thrusts that further improve the capabilities of US. First, we will develop novel image processing techniques that accurately track tissue deformation with US to create new images that show tissue mechanical properties. This is of significant clinical impact since pathologic changes in tissue, such as cancer tumours, are highly correlated with tissue mechanical properties. Second, we will develop robust and accurate techniques for automatic deformable registration of US to MR and CT. Image registration involve aligning two images that are obtained from the same tissue, so that they can be compared or combined. Registration of US with MR and CT has numerous applications in both diagnosis and therapy/interventions, and is an active field of research. Our approach in both thrusts is to cast the problem as optimization of a cost function that incorporates image similarity and prior information. To achieve widespread clinical use, a critical requirement in both elastography and registration is real-time performance. The proposed research program will achieve this goal by developing novel computationally efficient image analysis techniques.******The proposed interdisciplinary research program will train two PhD and four MASc students in an exciting environment at the Department of Electrical and Computer Engineering and the PERFORM Centre at Concordia University.