Extracting and smoothing contours in mammograms using Fourier descriptors

Cyrille K. Feudjio, Alain Tiedeu, Marie-Laure Noubeg, Mihaela Gordan, Aurel Vlaicu, Samuel Domngang

Centre Mère et Enfant, Fondation Chantal Biya, Yaoundé, Cameroun.
CTMED, Technical University of Cluj-Napoca, Cluj-Napoca, Romania.
Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon.
LETS, GRETMAT, National Advanced School of Engineering, Yaoundé, Cameroon.

DOI: 10.4236/jbise.2014.73017                

Abstract

Contour is an important pattern descriptor in image processing and particularly in region description, registration and length estimation. In many applications where contour is used, a good segmentation and an efficient smoothing method are needed. In X-ray images, such as mammograms, where object edge is not clearly discernible, estimating the object’s contour may yield substantial shift along the boundary due to noise or segmentation drawbacks. An appropriate smoothing is therefore required to reduce these effects. In this paper, an approach based on local adaptive threshold segmentation to extract contour and a new smoothing approach founded on Fourier descriptors are introduced. The experimental results of extraction obtained from a set of mammograms and compared with the breast regions delineated by radiologists yielded a percent overlap area of 98.7% ± 0.9% with false positive and negative rates of 0.36 ± 0.74 and 0.93 ± 0.44 respectively. The proposed method was tested on a set of images and improved the accuracy, leading to an average error of less than one pixel.

Keywords

Mammogram; Segmentation; Breast Contour; Smoothing; Fourier Descriptors

Conflicts of Interest

The authors declare no conflicts of interest.

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