Seminario sobre Imágenes por Resonancia Magnética del Cerebro – 10 de Diciembre 2014


Seminario sobre Imágenes por Resonancia Magnética del Cerebro – 10 de Diciembre 2014

Seminario 10 Diciembre 2014_Image Segmentation

Efficient Image Segmentation and Classification for Automatic Disease Detection from Brain Magnetic Resonance Imaging by Dr. Baidya Nath Saha

Abstract: Magnetic Resonance Imaging has been a successful non-invasive and non-radiative diagnostic tool for several neurologic diseases such as Brain Tumor, White Matter Lesion and Alzheimer for several decades. Quantification of the amount of damaged cerebral tissues or atrophy from Brain MRI is an important diagnostic and prognostic factor for these diseases. We propose a hierarchical level set based efficient image segmentation technique for automatically delineating of the cerebral tissues from MRI. However, the accuracy of the segmentation technique can be increased if it is applied locally within a bounding box. We also propose two fast line search methods in horizontal and vertical directions on brain MRI which can localize the brain tumor within a bounding box. Unfortunately, segmentation algorithms often produce under- and over- segmentation. We implement a novel regularized Adaboost based classification algorithm to deal with the under- and over-segmentation problem. They are computationally less expensive, more accurate and robust. The newly developed algorithms have been successfully implemented in several automatic disease detection from brain MRI such as, brain tumor and edema detection, white matter lesion segmentation, pediatric brain age prediction, and Alzheimer disease detection.

About the Speaker – Baidya Nath Saha is a Research Associate at CIMAT, Monterrey. Prior to that, he completed his postdoctoral research at University of Calgary, Canada (2013), and Wake Forest School of Medicine, USA (2012). He received his PhD from University of Alberta, Canada (2011) and received M. Tech. in Computer Science (2006), Quality, Reliability and Operations Research (2004) from Indian Statistical Institute, Kolkata, India. He completed Bachelor of Mechanical Engineering from Jadavpur University, Kolkata (2002). He earned several industrial internship experiences in major Indian software industries like Cognizant Technology Solutions, ITC Infotech India Limited, Robert Bosch India Limited; Manufacturing industries like Usha Martin India Limited and AQL Management Consulting Inc., Canada. His research interests include Computer Vision, Image Processing, Machine Learning, Artificial Intelligence and Software Engineering.

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