Automatic Vessel Extraction Using Particle Swarming Optimization for 3D Medical Images

Ali, Eman; Abdou, Mohamed A.; Sayed, Ashraf El

doi:10.2174/1573405613666170102143248

Cited by 1 publication

(5 citation statements)

References 11 publications

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“…From this table it could be observed that the introduced fuzzy algorithm achieves less MSE when compared to Jin manual method 4 and when compared with PSO algorithm presented in Ref. 5. The reasons are that fuzzy logic could work as a better classifier when compared to PSO, and it surpasses manual methods that suffer physicians and hand errors.…”

Section: Comparison Criteriamentioning

confidence: 90%

“…3 . In our recent work 5 , we used swarm intelligence methods to find optimum solutions and reached encouraging results. However, we had a serious problem regarding time complexity added by the PSO.…”

Section: Problem Definitionmentioning

confidence: 99%

“…In this work, we use a segmentation method based on level set introduced by Osher and Sethian 11 and applied in a previous work 5 . It is to start with the regularized version of Heaviside function and the one-dimensional Dirac, and respectively are defined in Eq.…”

Section: Chan-vese Segmentation Algorithmmentioning

confidence: 99%

“…The proposed fuzzy-rule based algorithm results will be compared with two methods: manual Jin's algorithm 4 and the automatic PSO-based algorithm 5 .…”

Section: Comparison Criteriamentioning

confidence: 99%

“…Evolutionary computational methods have succeeded to solve this problem using particle-swarm optimization (PSO) as in Ref. 5. In our previous work5, PSO was used to optimize parameters of Frangi filter3.…”

Section: Introductionmentioning

confidence: 99%

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

Abdou¹,

Elsayed²,

Ali³

2018

IJCIS

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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.

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Section: Comparison Criteriamentioning

confidence: 90%

Section: Problem Definitionmentioning

confidence: 99%

Section: Chan-vese Segmentation Algorithmmentioning

confidence: 99%

“…The proposed fuzzy-rule based algorithm results will be compared with two methods: manual Jin's algorithm 4 and the automatic PSO-based algorithm 5 .…”

Section: Comparison Criteriamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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