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Fast semi-automatic segmentation based on reduced basis
Damiano Lombardi, Yvon Maday, Lydie Uro

Fast semi-automatic segmentation based on reduced basis

Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

This note adresses the following segmentation problem in medical imaging : minimize expert intervention for semi-automatic segmentation process. Using a reduced basis, we have an a priori knowledge of the objet we want to identify on the images, like a muscle on a CT-Scan. We just have to identify the coefficients associated to the object of interest in the reduced basis, by solving a linear system taking as input the coordinates of some selected points in the image. An example implemented in 2D is shown. This method is independent of the grayscale of the image, and can therefore be applied to all objects and images. To cite this article: Y. Maday, D. Lombardi, L. Uro, C. R. Acad. Sci. Paris, Ser. I 340 (2019).

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Document Information

Document Title Fast semi-automatic segmentation based on reduced basis
Author / Organization Damiano Lombardi, Yvon Maday, Lydie Uro
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-192338
Original Source Link Visit Source Page on hal.science »