Publication

Unsupervised Connectivity-Based Thresholding Segmentation of Midsagittal Brain MR Images

Michaël Unser
1998
Journal Articles

Abstract

In this paper, we propose an algorithm for automated segmentation of midsagittal brain MR images. First, we apply thresholding to obtain binary images. From the binary images, we locate some landmarks. Based on the landmarks and anatomical information, we preprocess the binary images, which substantially simplifies the subsequent operations. To separate regions that are incorrectly merged after this initial segmentation, a new connectivity-based threshold algorithm is proposed. Assuming that some prior information about the general shape and location of objects is available, the algorithm finds a boundary between two regions using the path connection algorithm and changing the threshold adaptively. In order to test the robustness of the proposed algorithm, we applied the algorithm to 120 midsagittal brain images and obtained satisfactory results.

Official source

https://infoscience.epfl.ch/entities/publication/bdcb94ab-6b1c-42cf-a911-92328c01b121

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Michaël Unser
1998
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/bdcb94ab-6b1c-42cf-a911-92328c01b121

About this result

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Unsupervised Connectivity-Based Thresholding Segmentation of Midsagittal Brain MR Images

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