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Image Segmentation Based on the Local Center of Mass

version 1.1.1 (7.32 KB) by Iman Aganj
Matlab codes for unsupervised 2D and 3D image segmentation, using a local-center-of-mass approach.

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Updated 29 Sep 2020

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These are codes for unsupervised 2D and 3D image segmentation, using an approach based on the local center of mass of regions, described in:

I. Aganj, M. G. Harisinghani, R. Weissleder, and B. Fischl, “Unsupervised medical image segmentation based on the local center of mass,” Scientific Reports, vol. 8, Article no. 13012, 2018.
www.nature.com/articles/s41598-018-31333-5

See EXAMPLE.m for a short tutorial. If available, a GPU can be used to speed up the segmentation.

Cite As

Iman Aganj (2021). Image Segmentation Based on the Local Center of Mass (https://www.mathworks.com/matlabcentral/fileexchange/68561-image-segmentation-based-on-the-local-center-of-mass), MATLAB Central File Exchange. Retrieved .

I. Aganj, M. G. Harisinghani, R. Weissleder, and B. Fischl, “Unsupervised medical image segmentation based on the local center of mass,” Scientific Reports, vol. 8, Article no. 13012, 2018. www.nature.com/articles/s41598-018-31333-5

MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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