Automated object and image level classification of TB images using support vector neural network classifier

• Autorzy: Priya E. , Srinivasan S.

Identyfikatory

DOI

10.1016/j.bbe.2016.06.008

• Języki publikacji: EN

Abstrakty

EN

In this work, digital Tuberculosis (TB) images have been considered for object and image level classification using Multi Layer Perceptron (MLP) neural network activated by Support Vector Machine (SVM) learning algorithm. The sputum smear images are recorded under standard image acquisition protocol. The TB objects which include bacilli and outliers in the considered images are segmented using active contour method. The boundary of the segmented objects is described by fifteen Fourier Descriptors (FDs). The prominent FDs are selected using fuzzy entropy measures. These selected FDs of the TB objects are fed as input to the SVM learning algorithm of the MLP Neural Network (SVNN) and the result is compared with the state-of-the-art approach, Back Propagation Neural Network (BPNN). Results show that the segmentation method identifies the bacilli which retain their shape in-spite of artifacts present in the images. The methodology adopted has significantly enhanced the SVNN accuracy to 91.3% for object and 92.5% for image level classification than BPNN.

Słowa kluczowe

EN

tuberculosis; sputum smear images; Fourier descriptors; fuzzy entropy measures; support vector neural network; back propagation neural network

PL

gruźlica; obraz rozmazu; deskryptory Fouriera; sieć neuronowa; metoda wektorów nośnych

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2016
• Tom: Vol. 36, no. 4
• Strony: 670--678
• Opis fizyczny: Bibliogr, 28 poz., rys., tab., wykr.

Twórcy

autor

Priya E.

• Department of Electronics and Communication Engineering, Sri Sairam Engineering College, West Tambaram, Chennai 600044, India

autor

Srinivasan S.

• Department of Instrumentation Engineering, Madras Institute of Technology, Anna University, Chrompet, Chennai, India

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.