ProjectCartilage

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Assessment of Knee Cartilage

Assessment of Knee Cartilage

In medical collaboration with:
Christian Glaser

Scientific Director: Nassir Navab

Contact Person(s): Ben Glocker

Keywords: Segmentation, Reconstruction, Medical Imaging

Abstract

Degeneration of knee joint cartilage is an important and early indicator of osteoarthritis (OA) which is one of the major socio-economic burdens nowadays. Accurate quantification of the articular cartilage degeneration in an early stage using MR images is a promising approach in diagnosis and therapy for this disease. Particularly, volume and thickness measurement of cartilage tissue has been shown to deliver significant parameters in assessment of pathologies. Here, accurate computer-aided diagnosis tools could improve the clinical routine where image segmentation plays a crucial role. In order to overcome the time-consuming and tedious work of manual segmentation, one tries to automate the segmentation as much as possible. We focus on novel atlas-based segmentation methods for knee cartilage as well as improve today’s clinical routine of manual segmentation methods. In addition, we try to evaluate different methods for the assessment of parameters such as volume and thickness which could allow computer-aided diagnosis of knee cartilage pathologies in an early stage.

Detailed Project Description

The early development of osteoarthritis (OA), a major socio-economic burden nowadays, is known to be related to the condition of the articular cartilage. For the development and refinement of therapies, noninvasive, accurate, and valid tools are needed to establish appropriate indications for new treatment options, to monitor the disease process and to control therapeutic efficacy.

Among the techniques for articular cartilage imaging, two modalities are the most promising: magnetic resonance imaging (MRI) and x-ray phase contrast imaging (PCI). Whereas in MRI image formation and acquisition is well-understood and research in cartilage examination concentrates on post-processing, in the field of PCI there is still need for adaption of existing or development of new acquisition techniques. In terms of evaluation of such methods for image acquistion and analysis, only histology is accepted to provide reliable gold standard data.

Magnetic Resonance Imaging

semi-automatic segmentation of patellar cartilage in MRI

Main article: Semi-Automatic Patellar Cartilage Segmentation

MRI is a powerful tool for non-invasive examination of articular cartilage. In the analysis and interpretation of images, segmentation is a crucial step. This task still being too complex for fully automatic procedures, yet too tedious for completely manual accomplishment, only semi-automatic approaches permit contribution of radiologists’ expertise and acceptable expenditure of time. Such segmentations tools have been developed in recent years and are currently being evaluated.

Phase Contrast X-Ray Imaging

The emerging technique of phase contrast x-ray imaging is a promising modality for examination of soft tissue such as articular cartilage. The study of degenerative processes requires the development of volume reconstruction techniques for this modality, such as computerized tomography (CT) and tomosynthesis. The latter has been subject of a Diplomarbeit by Lorenz König.

Histology

stained histology slice of cartilage

Main article: Reconstruction and Registration of Histology and Phase Contrast Images for Clinical Validation of Imaging Modalities

The gold standard in terms of evaluation of new imaging methods and modalities is histology. Currently, cross validation is performed by qualitative comparison of 3D datasets to 2D histology slices. For a more quantitative approach, we propose to improve the histology procedure and to develop methods towards a consistent reconstruction of 3D histology volumes.

Publications

2010
A. Horng, J. M. Raya Garcia del Olmo, M. Zscharn, L. König, M. Notohamiprodjo, M. Pietschmann, U. Hoehne-Hückstädt, I. Hermanns, U. Glitsch, R. Ellegast, K. G. Hering, M. Reiser, Ch. Glaser
Locoregional Deformation Pattern of the Patellar Cartilage After Different Loading Types—High-Resolution 3D-MRI Volumetry at 3 T in-vivo
Fortschr Röntgenstr. 2010; 182:1–9 (bib)
J. M. Raya Garcia del Olmo, A. Horng, L. König, M. Reiser, Ch. Glaser
Detecting Statistically Significant Changes in Cartilage Thickness with Sub-Voxel Precision
Proceedings of the 18th congress of the International Society for Magnetic Resonance in Medicine (ISMRM 2010), Stockholm, Sweden. Presentation 3192, electronic poster session “Meniscus & Cartilage” (bib)
2007
B. Glocker, N. Komodakis, N. Paragios, Ch. Glaser, G. Tziritas, N. Navab
Primal/Dual Linear Programming and Statistical Atlases for Cartilage Segmentation
Medical Image Computing and Computer-Assisted Intervention (MICCAI), Brisbane, Australia, October 29 - November 2 2007 (bib)
L. König, M. Groher, A. Keil, Ch. Glaser, M. Reiser, N. Navab
Semi-Automatic Segmentation of the Patellar Cartilage in MRI
Proc. of Bildverarbeitung für die Medizin (BVM 2007), Munich, Germany, March 2007. The original publication is available online at www.springerlink.com. (bib)

Team

Contact Person(s)

Ben Glocker
Dr. Ben Glocker

Working Group

Ben Glocker
Dr. Ben Glocker
Christian Glaser
Dr. Christian Glaser
Lorenz König
Dipl.-Inf. Univ. Lorenz König
Nassir Navab
Prof. Dr. Nassir Navab
Shanshan Cui
Shanshan Cui

Alumni

Martin Groher
Dr. Martin Groher

Location



Ludwig-Maximilians-Universität München
Campus Grosshadern
Marchioninistrae 15
81377 München

Lab - Room: 4K U1 912
Tel.: +49 89 7095 4606
Visit our lab at Klinikum Grosshadern.



internal project page

Please contact Ben Glocker for available student projects within this research project.

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