Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Detecting Rheumatic Arthritis by Artificial Intelligent Multi-Parameter Classifications of Optical Tomographic Images

Not Accessible

Your library or personal account may give you access

Abstract

We demonstrate that sensitivity and specificity in detecting rheumatoid arthritis from optical tomographic images can be greatly increased when an artificial intelligent multi-parameter classifications method, called Self-Organizing Mapping (SOM), is used.

© 2008 Optical Society of America

PDF Article
More Like This
Frequency-Domain Optical Tomography of Arthritic Joints

A.H. Hielscher, H.K. Kim, U. Netz, L.D. Montejo, C.D. Klose, S. Blaschke, P.A. Zwaka, G.A. Müller, and J. Beuthan
BSuD87 Biomedical Optics (BIOMED) 2010

Comparison of Classification Methods for the Detection of Rheumatoid Arthritis with Optical Tomography

Ludguier D. Montejo, Julio D. Montejo, Hyun K. Kim, Uwe J. Netz, Christian D. Klose, Sabine Blaschke, P.A. Zwaka, Gerhard A. Müller, Jürgen Beuthan, and Andreas H. Hielscher
BWF2 Biomedical Optics (BIOMED) 2010

Early Detection of Rheumatoid Arthritis in Humans by Fluorescence Imaging

Bernd Ebert, Jörn Berger, Jan Voigt, Rainer Macdonald, Thomas Fischer, Kay-Geert Hermann, Kai Licha, and Michael Schirner
BTuF19 Biomedical Optics (BIOMED) 2008

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.