Journal of Innovative Optical Health Sciences, Volume. 4, Issue 1, 59(2011)

BINARY TISSUE CLASSIFICATION STUDIESON RESECTED HUMAN BREAST TISSUES USING OPTICAL COHERENCE TOMOGRAPHY IMAGES

M. BHATTACHARJEE, P. C. ASHOK, K. DIVAKAR RAO*, S. K. MAJUMDER, Y. VERMA, and P. K. GUPTA
Author Affiliations
  • Laser Biomedical Applications and Instrumentation Division Raja Ramanna Center for Advanced Technology Indore 452 013, India
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    We report the results of a comparative study of Fourier domain analysis (FDA) and texture analysis (TA) of optical coherence tomography (OCT) images of resected human breast tissues for binary classification between normal-abnormal classes and benign-malignant classes. With the incorporation of Fisher linear discriminant analysis (FLDA) in TA for feature extraction, the TA-based algorithm provided improved diagnostic performance as compared to the FDAbased algorithm in discriminating OCT images corresponding to breast tissues with three different pathologies. The specificity and sensitivity values obtained for normal-abnormal classification were both 100%, whereas they were 90% and 85%, respectively for benign-malignant classification.

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    M. BHATTACHARJEE, P. C. ASHOK, K. DIVAKAR RAO, S. K. MAJUMDER, Y. VERMA, P. K. GUPTA. BINARY TISSUE CLASSIFICATION STUDIESON RESECTED HUMAN BREAST TISSUES USING OPTICAL COHERENCE TOMOGRAPHY IMAGES[J]. Journal of Innovative Optical Health Sciences, 2011, 4(1): 59

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    Paper Information

    Received: --

    Accepted: --

    Published Online: Jan. 10, 2019

    The Author Email: RAO K. DIVAKAR (kdivakar@rrcat.gov.in)

    DOI:10.1142/s1793545811001083

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