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Mauritanian Project

Key Investigators

Presenter location: In-person

Project Description

The Mauritanian approach aims to make 3D Slicer accessible to a broader audience of users and researchers in the medical field. Various projects have been completed, initiated, or are currently under consideration, including:


Approach and Plan

Progress and Next Steps


We have developed an extension for 3D Slicer to perform medical image (volume) segmentation using the K-Means algorithm. Specifically, we have implemented an adaptive version of K-Means, which allows segmentation based on pixel intensity.

We encountered several challenges during volume processing and rendering, as well as in finding alternatives to libraries like scikit-learn, NumPy, and OpenCV to integrate them into the 3D Slicer API.

Ultimately, we successfully segmented the images using both the adaptive K-Means and the classic K-Means methods. However, these results still require improvement and testing on various types of medical images to ensure their reliability

Adaptive Algorithm Result

Image 1 Image 2 Image 3

Classic Algorithm Result

Image 1 Image 2 Image 3 Image 4 Image 5 Image 6 Image 7 Image 8

Background and References

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