Automatic segmentation of lesion from breast DCE-MR image using artificial fish swarm optimization algorithm

• Autorzy: Janaki S. D. , Geetha K.

Identyfikatory

DOI

10.1515/pjmpe-2017-0006

• Języki publikacji: EN

Abstrakty

EN

Interpreting Dynamic Contrast-Enhanced (DCE) MR images for signs of breast cancer is time consuming and complex, since the amount of data that needs to be examined by a radiologist in breast DCE-MRI to locate suspicious lesions is huge. Misclassifications can arise from either overlooking a suspicious region or from incorrectly interpreting a suspicious region. The segmentation of breast DCE-MRI for suspicious lesions in detection is thus attractive, because it drastically decreases the amount of data that needs to be examined. The new segmentation method for detection of suspicious lesions in DCE-MRI of the breast tissues is based on artificial fishes swarm clustering algorithm is presented in this paper. Artificial fish swarm optimization algorithm is a swarm intelligence algorithm, which performs a search based on population and neighborhood search combined with random search. The major criteria for segmentation are based on the image voxel values and the parameters of an empirical parametric model of segmentation algorithms. The experimental results show considerable impact on the performance of the segmentation algorithm, which can assist the physician with the task of locating suspicious regions at minimal time.

Słowa kluczowe

EN

breast DCE-MRI; segmentation; artificial fishes swarm optimization algorithm

• Wydawca: Polskie Towarzystwo Fizyki Medycznej ; De Gruyter
• Czasopismo: Polish Journal of Medical Physics and Engineering
• Rocznik: 2017
• Tom: Vol. 23, Iss. 2
• Strony: 29--36
• Opis fizyczny: Bibliogr. 35 poz., rys., tab.

Twórcy

autor

Janaki S. D.

• Department of Electrical & Electronics Engineering, PSG College of Technology, Coimbatore, India

autor

Geetha K.

• Department of Electrical & Electronics Engineering, Karpagam Institute of Technology, Coimbatore, India

Bibliografia

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