TITLE:
Extracting and smoothing contours in mammograms using Fourier descriptors
AUTHORS:
Cyrille K. Feudjio, Alain Tiedeu, Marie-Laure Noubeg, Mihaela Gordan, Aurel Vlaicu, Samuel Domngang
KEYWORDS:
Mammogram; Segmentation; Breast Contour; Smoothing; Fourier Descriptors
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.7 No.3,
February
21,
2014
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.