Computer-aided BSE torso tracking algorithm using neural networks, contours, and edge features
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 b...
Saved in:
Main Authors: | Masilang, Rey Anthony A., Cabatuan, Melvin K., Dadios, Elmer P., Gan Lim, Laurence |
---|---|
Format: | text |
Published: |
Animo Repository
2015
|
Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1892 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Similar Items
-
Monocular depth level estimation for breast self-examination (BSE) using RGBD BSE dataset
by: Jose, John Anthony C., et al.
Published: (2016) -
Detecting and tracking female breasts using neural network in real-time
by: Eman, Mohammadi N., et al.
Published: (2013) -
Vision-based breast self-examination hand interaction tracking using sparse optical flow and genetic algorithm
by: Cabatuan, Melvin K., et al.
Published: (2014) -
Hand initialization and tracking using a modified KLT tracker for a computer vision-based breast self-examination system
by: Masilang, Rey Anthony A., et al.
Published: (2014) -
Stroke position classification in breast self-examination using parallel neural network and wavelet transform
by: Jose, John Anthony C., et al.
Published: (2015)