[Insight-users] New Submission: Fuzzy Clustering Algorithms for Image Segmentation

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A new submission has been added to the Insight Journal.

Title: Fuzzy Clustering Algorithms for Image Segmentation
Authors: Rey A., Castro A., Arcay B.
Abstract: In this document we present the implementation of three fuzzy clustering algorithms using the Insight Toolkit ITK. Firstly, we developed the conventional Fuzzy C-Means that will serve as the basis for the rest of the proposed algorithms. The next algorithms are the FCM with spatial constraints based on kernel-induced distance and the Modified Spatial Kernelized Fuzzy C-Means. Both of these introduce a Kernel function, replacing the Euclidean distance of the FCM, and spatial information into the membership function.

These algorithms have been implemented in a threaded version to take advantage of the multicore processors. Moreover, providing an useful implementation make it possible that classes work with 2D/3D images, different kernels and spatial shapes.

We included the source code as well as different 2D/3D examples, using several input parameters for the algorithms and obtaining the results generated on 2D/3D CT lung studies.

Download and review this publication at: http://hdl.handle.net/10380/3331

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