Computer-aided BSE torso tracking algorithm using neural networks, contours, and edge features

Author

Masilang, Rey Anthony A. ; Cabatuan, Melvin K. ; Dadios, Elmer P. ; Gan Lim, Laurence A.

Author_Institution

Electron. & Commun. Eng. Dept., De La Salle Univ. Manila, Manila, Philippines

fYear

2014

fDate

22-25 Oct. 2014

Firstpage

1

Lastpage

5

Abstract

This paper presents an algorithm for tracking the torso of the user in a computer-aided breast self-examination system. The algorithm uses a neural network-based skin classifier for segmenting the skin area from the non-skin area. Using the skin mask produced by the classifier, the contours of the body are extracted and used to identify the region containing the torso of the user. The algorithm is tested on 4 different videos. The performance of the algorithm is measured in terms of its F1-score. Results show that the algorithm is capable of accurate tracking with an F1-score of 92.97%.

Keywords

feature extraction; image classification; image segmentation; medical image processing; neural nets; object tracking; video signal processing; F1-score; body contour extraction; computer-aided BSE torso tracking algorithm; computer-aided breast self-examination system; edge features; neural network-based skin classifier; skin area segmentation; skin mask; Artificial neural networks; Breast; Image color analysis; Image edge detection; Skin; Torso; Videos; artificial neural network; breast self-examination; contours; edge detection; skin detection;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2014 - 2014 IEEE Region 10 Conference

Conference_Location

Bangkok

ISSN

2159-3442

Print_ISBN

978-1-4799-4076-9

Type

conf

DOI

10.1109/TENCON.2014.7022300

Filename

7022300