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Optical imaging for diagnosis of rheumatoid arthritis automatic versus human evaluation.
In: (2nd International Conference on Bioimaging, BIOIMAGING 201, 12-15 January 2015, Lisbon; Portugal). 2015. 36-43
Successful detection of rheumatoid arthritis (RA) at the early stages of development can significantly enhance the chances of effective therapy. The early onset of RA is often marked with inflammation of the synovial lining of the joint, a condition known as synovitis. Effective imaging of synovitis is therefore of critical importance. While dynamic, contrast-enhanced magnetic resonance imaging (MRI) is capable of effective imaging of synovitis, it is a costly modality. As an alternative, inexpensive approach, optical imaging post injection of the near-infrared fluorescent dye indocynine green (ICG) has been recently proposed for imaging RA. Evaluation of the obtained optical images is performed via examination by trained human readers. However, optical imaging has yet to achieve the diagnostic accuracy of MRI. In this paper we present a method for automatic evaluation of the fluorescence images and compare its performance with the human-based evaluation. Our method relies on our previous work on spatiotemporal analysis of image sequence with principal component analysis (PCA) to seek synovitis signal components with the help of a segmentation method. The results for a group of 600 joints, obtained from 20 patients, suggest improved diagnostic performance using the automatic approach in comparison to human-based evaluation.
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Publikationstyp
Artikel: Konferenzbeitrag
Schlagwörter
Fluorescence Indocynine green (ICG) Inflammation Near-infrared dyes Optical imaging Planar illumination Principal component analysis (PCA) Rheumatoid arthritis (RA) Spatiotemporal analysis
Sprache
englisch
Veröffentlichungsjahr
2015
HGF-Berichtsjahr
2015
ISSN (print) / ISBN
978-989-758-072-7
Konferenztitel
2nd International Conference on Bioimaging, BIOIMAGING 201
Konferzenzdatum
12-15 January 2015
Konferenzort
Lisbon; Portugal
Quellenangaben
Seiten: 36-43
POF Topic(s)
30205 - Bioengineering and Digital Health
Forschungsfeld(er)
Enabling and Novel Technologies
PSP-Element(e)
G-505500-001
Erfassungsdatum
2018-02-22