Pectoral muscle detection in mammograms based on the shortest path with endpoints learnt by SVMs.

• Type: Article in International Scientific Journal
• Date: 2010

Authors

Domingues, I (Author) Other; Jaime S Cardoso (Author) FEUP; Amaral, I (Author) Other; Moreira, I (Author) Other; Passarinho, P (Author) Other; Santa Comba, J (Author) Other; Correia, R (Author) Other; Cardoso, MJ (Author) Other

Journal

The Journal is awaiting validation by the Administrative Services.

Title: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

Vol. 2010

Pages: 3158-3161

ISSN: 1557-170X

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-017-C80

Abstract (EN): Automatic pectoral muscle removal on medio-lateral oblique view of mammogram is an essential step for many mammographic processing algorithms. However, the wide variability in the position of the muscle contour, together with the similarity between in muscle and breast tissues makes the detection a difficult task. In this paper, we propose a two step procedure to detect the muscle contour. In a first step, the endpoints of the contour are predicted with a pair of support vector regression models; one model is trained to predict the intersection point of the contour with the top row while the other is designed for the prediction of the endpoint of the contour on the left column. Next, the muscle contour is computed as the shortest path between the two endpoints. A comprehensive comparison with manually-drawn contours reveals the strength of the proposed method.

Language: English

Type (Professor's evaluation): Scientific