Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks

CC
CBMS
2007
Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07)
Abstract - Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks

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Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07)

Maribor, Slovenia

June 20-June 22

ISBN: 0-7695-2905-4

	ASCII Text	x
	M. Palfy, B. Jesensek Papez, "Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks," Computer-Based Medical Systems, IEEE Symposium on, pp. 59-64, Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007.

	BibTex	x
	@article{ 10.1109/CBMS.2007.40, author = {M. Palfy and B. Jesensek Papez}, title = {Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks}, journal ={Computer-Based Medical Systems, IEEE Symposium on}, volume = {0}, year = {2007}, issn = {1063-7125}, pages = {59-64}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2007.40}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer-Based Medical Systems, IEEE Symposium on TI - Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks SN - 1063-7125 SP59 EP64 A1 - M. Palfy, A1 - B. Jesensek Papez, PY - 2007 KW - null VL - 0 JA - Computer-Based Medical Systems, IEEE Symposium on ER -

M. Palfy, Maribor General Hospital, Slovenia

B. Jesensek Papez, Maribor General Hospital, Slovenia

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2007.40

Thermography is an excellent method of examination, useful in the field of medicine for its safety, lack of pain and invasiveness, easy reproducibility and low running costs. As such it represents a possible alternative to more common methods for diagnosis of carpal tunnel syndrome (e.g. electromyography). However, manual analysis of thermal images can be a tedious job, requiring some patience and accuracy.

Here we present a software-based intelligent system for diagnosis of carpal tunnel syndrome. Artificial neural networks, known as a well established data mining technique, were used for thermal image analysis. Reliability was tested on 44 images (23 depicting pathological hands and 21 healthy). Results acquired are presented.

Citation:

M. Palfy, B. Jesensek Papez, "Diagnosis of Carpal Tunnel Syndrome from Thermal Images Using Artificial Neural Networks," cbms, pp.59-64, Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS'07), 2007

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