Contributions to Image Processing in the Perspective of Medical Applications: From CAD to Embedded Systems for In Situ Diagnosis
Résumé
For the last decade, Medical Image Analysis for Computer-Aided-Diagnosis (CAD) has been thecentral motivation of my research activity. With the constant increase of the imaging capabilities ofmedical devices and the huge amount of produced digital information, physicians are in real need for semiautomaticimage processing tools making possible fast, precise and robust analysis, including restoration,segmentation, pattern detection and recognition, quantitative analysis, etc. In this particular applicationarea, from an image processing perspective, my research work has mainly focused for the last 8 yearson two main tracks: (i) The study of the variational approach framework for image restoration andsegmentation which common point is the formalization of the related optimization problem under theform of a Partial Differential Equation (PDE); (ii) The development of embeddable pattern detectionand recognition methods based on statistical learning process for real-time in situ diagnosis.The main scientific contributions of my research activities have been since 2006: In image restoration:(i) The study of the stochastic resonance phenomenon in non-linear PDE for image restoration and (ii)The study of double-well potential functions for Gradient-Oriented-PDE in image restoration. In imagesegmentation: (i) An Active contour segmentation approach with learning-based shape prior information;(ii) An Alpha-divergence-based active contour image segmentation approach; (iii) A Fractional-entropybasedactive contour image segmentation approach. And finally in pattern recognition: The proposal of acomplete embeddable image processing scheme for in situ polyp detection in Wireless Capsule Endoscopyfor early colorectal cancer diagnosis.This manuscript proposes a detailed overview of these contributions as well as elements for my futureresearch activities.
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