Open AccessA New Approach to the Detection of Mammogram Boundary
Author(s) -
Mohammed Rmili,
Abdelmajid El Moutaouakkil,
Mousatapha M. Saleck,
Maksi Bouchaib,
Fatiha El Adnani,
El Mehdi El Aroussi
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i5.pp3587-3593
Subject(s) - mammography , rectangle , computer science , artificial intelligence , boundary (topology) , pattern recognition (psychology) , pixel , computer aided diagnosis , computer vision , digital mammography , point (geometry) , sensitivity (control systems) , cad , breast cancer , mathematics , cancer , medicine , geometry , mathematical analysis , electronic engineering , engineering drawing , engineering
Mammography is a method used for the detection of breast cancer. computer-aided diagnostic (CAD) systems help the radiologist in the detection and interpretation of mass in breast mammography. One of the important information of a mass is its contour and its form because it provides valuable information about the abnormality of a mass. The accuracy in the recognition of the shape of a mass is related to the accuracy of the detected mass contours. In this work we propose a new approach for detecting the boundaries of lesion in mammography images based on region growing algorithm without using the threshold, the proposed method requires an initial rectangle surrounding the lesion selected manually by the radiologist (Region Of Interest), where the region growing algorithm applies on lines segments that attach each pixel of this rectangle with the seed point, such as the ends (seeds) of each line segment grow in a direction towards one another. The proposed approach is evaluated on a set of data with 20 masses of the MIAS base whose contours are annotated manually by expert radiologists. The performance of the method is evaluated in terms of specificity, sensitivity, accuracy and overlap. All the findings and details of approach are presented in detail.