Presentation + Paper
2 April 2020 Wavelet transform of Fourier domain low coherence interference spectra for breast cancer detection
Dipti Bharti, Gyana Ranjan Sahoo, Shivam Shukla, Asima Pradhan
Author Affiliations +
Abstract
Breast cancer arises either in the lobules or the ducts of the tissue. Structural changes occurring with malignancy manifest as refractive index variations inside the tissue. It is crucial to quantify these depth wise variation in refractive index for early cancer detection. In this study, three types of unstained breast tissue sections - fibrocystic, fibroadenoma, and invasive carcinoma have been examined for the ultra-structural changes using `Fourier domain low coherence interferometry'. The resulting interference spectra of the backscattered light from the front and the rear surface of the sample are Fourier analyzed to provide depth correlation function. The subtle small-scale fluctuations in the Fourier analyzed spectra are then evaluated using Discrete Wavelet Transform (DWT). Daubechies-1 wavelet of DWT is used to calculate the high pass and low pass coefficients. The sixth level low pass coefficients of DWT clearly discriminate among normal, benign, and malignant breast tissue. Skewness and kurtosis values for these coefficients are also able to well distinguish the type of tissues.
Conference Presentation
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Dipti Bharti, Gyana Ranjan Sahoo, Shivam Shukla, and Asima Pradhan "Wavelet transform of Fourier domain low coherence interference spectra for breast cancer detection", Proc. SPIE 11363, Tissue Optics and Photonics, 113631R (2 April 2020); https://doi.org/10.1117/12.2555055
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KEYWORDS
Tissues

Breast

Wavelets

Breast cancer

Discrete wavelet transforms

Tumors

Interferometry

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