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Fast semi-automatic segmentation based on reduced basis

Abstract : 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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https://hal.inria.fr/hal-03013545
Contributor : Damiano Lombardi <>
Submitted on : Thursday, November 19, 2020 - 8:20:49 AM
Last modification on : Monday, November 23, 2020 - 8:40:46 AM

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  • HAL Id : hal-03013545, version 1

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Damiano Lombardi, Yvon Maday, Lydie Uro. Fast semi-automatic segmentation based on reduced basis. Comptes Rendus Mathématique, Elsevier Masson, 2020. ⟨hal-03013545⟩

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