Fourier-based segmentation of microcalcifications in mammograms

Elizabeth López-Meléndez; Luis David Lara-Rodríguez; Gonzalo Urcid

doi:10.1117/12.2188703

22 September 2015 Fourier-based segmentation of microcalcifications in mammograms

Elizabeth López-Meléndez, Luis David Lara-Rodríguez, Gonzalo Urcid

Proceedings Volume 9599, Applications of Digital Image Processing XXXVIII; 95992N (2015) https://doi.org/10.1117/12.2188703
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

This paper presents a Fourier transform approach to detect microcalcifications in digital mammograms. The basic idea consists in the design of parametric Butterworth bandpass filters in the Fourier domain used to extract sharpened border like structures that correspond to detected mammography microcalcifications. Image thresholding of the filtered image is accomplished, first by homogenizing the background (fibroglandular tissue) with a median filter, after which a gamma correction is applied to change the global contrast. Second, by postprocessing the resulting image using histogram based local and global statistics we obtain a properly binarized image that emphasizes the desired objects (microcalcifications) and segmentation is completed using a sequence of morphological binary operations. Several illustrative examples taken from a clinical database are included to demonstrate the capability of the proposed approach in comparison with other edge detection techniques such as the difference of Gaussians (DoG) and the Laplacian of a Gaussian (LoG).

Citation Download Citation

Elizabeth López-Meléndez, Luis David Lara-Rodríguez, and Gonzalo Urcid "Fourier-based segmentation of microcalcifications in mammograms", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 95992N (22 September 2015); https://doi.org/10.1117/12.2188703

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KEYWORDS

Image segmentation

Mammography

Fourier transforms

Image enhancement

Binary data

Image processing

Sensors

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