Image Segmentation Based on the Local Center of Mass

版本 1.1.1 (7.3 KB) 作者: Iman Aganj
Matlab codes for unsupervised 2D and 3D image segmentation, using a local-center-of-mass approach.
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更新时间 2020/9/29

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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.

引用格式

Iman Aganj (2024). 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. 检索时间: .

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

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版本 已发布 发行说明
1.1.1

Minor update.
1.1

In findCMs.m, the dimension through which the center of mass is computed is now adjustable and defaults to 1.
1.0.3

Minor update.
1.0.2

Minor update.
1.0.1

Minor update.
1.0.0