Multi-channeled MR brain image segmentation: A novel double optimization approach combined with clustering technique for tumor identification and tissue segmentation

• Autorzy: Narayanan Anitha , Rajasekaran M. Pallikonda , Zhang Yudong , Govindaraj Vishnuvarthanan , Thiyagarajan Arunprasath

Identyfikatory

DOI

10.1016/j.bbe.2018.12.003

• Języki publikacji: EN

Abstrakty

EN

Growth of cancer cells within the human body is a major outcome of the manipulation of cells and it has resulted in the deterioration of the life span of humans. The impact of cancer cells is irretrievable and it has paved the way to the formation of tumors within the human body. For achieving and developing a single-structured framework to prominently identify the tumor regions and segmenting the tissue structures specifically in human brain, a novel combinational algorithm is proposed through this paper. The algorithm has been embodied with two optimization techniques namely particle swarm optimization (PSO) and bacteria foraging optimization (BFO), wherein, PSO helps in finding the best position of global bacterium for BFO, consecutively, BFO supports the modified fuzzy c means (MFCM) algorithm by providing optimized cluster heads. Finally, MFCM segments the tissue regions and identifies the tumor portion, thereby reducing the interaction and complication experienced by a radiologist during patient diagnosis. The strength of the proposed algorithm is proven by comparing it with the state-of-the-art techniques by means of evaluation parameters like mean squared error (MSE), peak signal to noise ratio (PSNR), sensitivity, specificity, etc., Data sets used in this paper were exclusively obtained from hospital, Brain web simulator and BRATS-2013 challenge. The sensitivity and specificity values for 115 MR brain slice images.

Słowa kluczowe

EN

tumor identification; tissue segmentation; particle swarm optimization (PSO); bacteria foraging optimization; modified fuzzy c-means algorithm

PL

rozpoznanie guza; segmentacja tkanki; optymalizacja roju cząstek; algorytm rozmytych k-średnich

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 2
• Strony: 350--381
• Opis fizyczny: Bibliogr, 81 poz., rys., tab., wykr.

Twórcy

autor

Narayanan Anitha

• Department of Electronics and Communication Engineering, Kalasalingam University (Kalasalingam Academy of Research and Education), Anand Nagar, Krishnankoil, Srivilliputur, Virudhunagar District, Tamilnadu 626126, India

autor

Rajasekaran M. Pallikonda

• Department of Electronics and Communication Engineering, Kalasalingam University (Kalasalingam Academy of Research and Education), Tamilnadu, India

autor

Zhang Yudong

• Department of Informatics, University of Leicester, Leicester, United Kingdom

autor

Govindaraj Vishnuvarthanan

• Department of Biomedical Engineering, Kalasalingam University (Kalasalingam Academy of Research and Education), Tamilnadu, India

autor

Thiyagarajan Arunprasath

• Department of Electrical & Electronics Engineering, Kalasalingam University (Kalasalingam Academy of Research and Education), Tamilnadu, India

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).

PL

W opisie bibliograficznym brak poz. 62, 63, 66, 67, 69.