Computer vision-based breast self-examination palpation pressure level classification using artificial neural networks and wavelet transforms
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
IEEE Region 10 Annual International Conference, Proceedings/TENCON
Publication Date
12-1-2012
Abstract
Breast cancer is the leading cause of cancer mortality among women and early diagnosis with proper treatment is the key to survival. Women who practice regular breast self-examination are the ones most likely to detect early abnormalities in their breast. However, studies have shown that most women performing BSE do not carry out the procedure efficiently. This paper presents a method for BSE procedure guidance through the classification of palpation pressure levels, i.e. superficial, medium, and deep, based on computer vision. In particular, we utilize an artificial neural network (ANN) to classify the pressure levels of the image frames extracted from an actual BSE video yielding an accuracy of 91 % respectively. © 2012 IEEE.
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Digitial Object Identifier (DOI)
10.1109/TENCON.2012.6412282
Recommended Citation
Cabatuan, M. K., Dadios, E. P., & Naguib, R. G. (2012). Computer vision-based breast self-examination palpation pressure level classification using artificial neural networks and wavelet transforms. IEEE Region 10 Annual International Conference, Proceedings/TENCON https://doi.org/10.1109/TENCON.2012.6412282
Disciplines
Electrical and Computer Engineering | Electrical and Electronics | Systems and Communications
Keywords
Breast—Cancer; Breast—Examination; Computer vision
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