An Advanced Automatic Fuzzy Rule-Based Algorithm for 3D Vessel Segmentation

Fuzzy Logic has played an important role in medical image (MI) segmentation in the last decade. Automatic blood vessel segmentation from 3D medical images is an emerging area where segmentation algorithms could be combined with evolutionary computation methods for better diagnosis and higher decision accuracy. This paper introduces an automatic blood vessel segmentation algorithm from 3D images using Fuzzy logic. The proposed fuzzy system decides degree of Vesselness according to Eigen values of Hessian matrix. 3D synthetic and real CTA clinical image database are used to test the proposed algorithm and show a correct voxel classification. The proposed method shows better segmentation results compared to manual and swarm intelligence methods. Furthermore, fuzzy has led to better time improvement.

Abstract licence: CC BY-NC-ND

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