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Authors: Pouyan Mohajerani 1 ; Reinhard Meier 2 ; Ernst Rummeny 2 and Vasilis Ntziachristos 1

Affiliations: 1 Institute for Biological and Medical Imaging and Technische Universität München and Helmholtz Zentrum München, Germany ; 2 Department of Radiology, Klinikum Rechts der Isar and Technische Universität München, Germany

ISBN: 978-989-758-072-7

Keyword(s): Optical Imaging, Fluorescence, Rheumatoid Arthritis (RA), Inflammation, Indocynine Green (ICG), Planar Illumination, Near-Infrared Dyes, Spatiotemporal Analysis, Principal Component Analysis (PCA).

Related Ontology Subjects/Areas/Topics: Bioimaging ; Biomedical Engineering ; Biophotonics ; Image Processing Methods ; Medical Imaging and Diagnosis ; Ultrasound and Optical Imaging

Abstract: 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 prev ious 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. (More)

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Paper citation in several formats:
Mohajerani, P.; Meier, R.; Rummeny, E. and Ntziachristos, V. (2015). Optical Imaging for Diagnosis of Rheumatoid Arthritis - Automatic Versus Human Evaluation.In Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015) ISBN 978-989-758-072-7, pages 36-43. DOI: 10.5220/0005217200360043

@conference{bioimaging15,
author={Pouyan Mohajerani. and Reinhard Meier. and Ernst Rummeny. and Vasilis Ntziachristos.},
title={Optical Imaging for Diagnosis of Rheumatoid Arthritis - Automatic Versus Human Evaluation},
booktitle={Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015)},
year={2015},
pages={36-43},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005217200360043},
isbn={978-989-758-072-7},
}

TY - CONF

JO - Proceedings of the International Conference on Bioimaging - Volume 1: BIOIMAGING, (BIOSTEC 2015)
TI - Optical Imaging for Diagnosis of Rheumatoid Arthritis - Automatic Versus Human Evaluation
SN - 978-989-758-072-7
AU - Mohajerani, P.
AU - Meier, R.
AU - Rummeny, E.
AU - Ntziachristos, V.
PY - 2015
SP - 36
EP - 43
DO - 10.5220/0005217200360043

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