@inproceedings{887ee9e456b544d9ab9101e2cc00b1c2,
title = "Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection",
abstract = "Disorders associated with repeated trauma account for about 60\% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.",
keywords = "Acquisition Protocol, Carpal Tunnel Syndrome, Feature Extraction, Infrared Image Registration, Infrared Imaging",
author = "\{Estupinan Roldan\}, Kevin and \{Ortega Piedrahita\}, \{Marco A.\} and Benitez, \{Hernan D.\}",
year = "2014",
doi = "10.1117/12.2042575",
language = "English",
isbn = "9780819499363",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
booktitle = "Proceedings of SPIE-IS and T Electronic Imaging - Image Processing",
address = "United States",
note = "Image Processing: Algorithms and Systems XII ; Conference date: 03-02-2014 Through 05-02-2014",
}