Mass segmentation in mammograms by using Bidimensional Emperical Mode Decomposition BEMD

Author

Jai-Andaloussi, Said ; Sekkaki, Abderrahim ; Quellec, Gwenole ; Lamard, Mathieu ; Cazuguel, Guy ; Roux, C.

Author_Institution

Fac. of Sci. Ain-chok, Casablanca, Morocco

fYear

2013

fDate

3-7 July 2013

Firstpage

5441

Lastpage

5444

Abstract

Breast mass segmentation in mammography plays a crucial role in Computer-Aided Diagnosis (CAD) systems. In this paper a Bidimensional Emperical Mode Decomposition (BEMD) method is introduced for the mass segmentation in mammography images. This method is used to decompose images into a set of functions named Bidimensional Intrinsic Mode Functions (BIMF) and a residue. Our approach consists of three steps: 1) the regions of interest (ROIs) were identified by using iterative thresholding; 2) the contour of the regions of interest (ROI) was extracted from the first BIMF by using the (BEMD) method; 3) the region of interest was finally refined by the extracted contour. The proposed approach is tested on (MIAS) database and the obtained results demonstrate the efficacy of the proposed approach.

Keywords

biological tissues; edge detection; feature extraction; image segmentation; iterative methods; mammography; medical image processing; BEMD method; BIMF; CAD system; MIAS database; ROI contour extraction; ROI identification; ROI refining; bidimensional emperical mode decomposition method; bidimensional intrinsic mode function; breast mass segmentation; computer-aided diagnosis system; image decomposition; iterative thresholding; mammography image; regions of interest identification; Breast; Cancer; Databases; Image edge detection; Image segmentation; Iterative methods; Joining processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE

Conference_Location

Osaka

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2013.6610780

Filename

6610780