Author :J. Carballido-Gamio J.S. Bauer Keh-YangLee

   S. Krause   S. MajumdarSource :27th Annual International Conference of the IEEE-EMBS 2005; On page(s): 3043-3046

Speaker : Ren-Li ShenAdvisor : Ku-Yaw Chang

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OutlineIntroductionMethodologyResultsDiscussionConclusion

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IntroductionArticular cartilage

Common manifestation of osteoarthritis (OA) Morphological degeneration

Magnetic resonance imaging (MRI)Visualize and analyze

Purpose Development new image processing techniques

For quantitative analysis

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IntroductionImage process consists

MRI acquisitionCartilage segmentation

Automatic Semi-automatic

InteractiveInterpolation

Morphing techniqueRegistration

3D shape-contextsQuantification

Minimum 3D Euclidean distances 3D shape-contexts

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OutlineIntroductionMethodologyResultsDiscussionConclusion

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Methodology17 porcine kneesSagittal 3D SPGR MR images （ Intra-subject）Knee of 6 subjects （ resolution ： 0.234 mm x

0.234 mm, slice thickness ： 2mm,obtained at 1.5T）

Sagittal fast spin-echo(FSE) images （ Inter-subject）Both knees of 6 different subjects （ resolution ：

0.3125 mm x 0.3125mm, slice thickness ： 1.5 mm,obtained at 1.5T）

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Methodology

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Methodology-Cartilage segmentationSemi-automatic segmentation technique

Based on edge detection and Bezier splinesControl points

Placed inside the cartilage Following its shape to create Bezier spline

Smoothing techniquesAnisotropic diffusionMedian filteringMultiplication

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Methodology-Thickness and volumeCompute 3D cartilage thickness

Labeling bone-cartilage and articular Automatically

For each point on the articular surface Can find point on the bone-cartilage interface

Corresponding distance was assigned Thickness value

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Methodology-Image registrationBones to be registered

Using 3D shape-contexts Robust contour matching

Manual and automaticUsing minimum Euclidean

distancesAvoid false matching

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OutlineIntroductionMethodologyResultsDiscussionConclusion

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ResultsUsing Bland-Altman method

Check for any deviationAll methods

Good agreement on all data samples

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OutlineIntroductionMethodologyResultsDiscussionConclusion

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DiscussionProper quantification of thickness and

volumeImportant to OA of the knee

In follow-up studiesCompare common regions

Have presented an validatedAutomatic registration technique

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OutlineIntroductionMethodologyResultsDiscussionConclusion

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ConclusionIt’s important to assess the quantification

Knee cartilage morphologyMonitor the progression of joint diseases

Have presented and validatedAccurate image processing tools

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