Transcript Autonomous Direct 3D Segmentation of Articular Knee Cartilage

Autonomous Direct
3D Segmentation of
Articular Knee Cartilage
Author :Enrico Hinrichs, Brian C. Lovell,
Ben Appleton, Graham John Galloway
Source :Australian and New Zealand Intelligent
Information Systems, 10-12 December 1(1),
pages 417-420, Sydney
Speaker : Ren-LI Shen
Advisor : Ku-Yaw Chang
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Outline
Introduction
 Segmentation
 Discussion and results

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Introduction

Osteoarthritis (OA) occurs
◦ 30 to 70 years
◦ Years<30:High-impact sports player

Using MRI
◦ High-contrast cartilage images

Focus on
◦ Automation segmentation
◦ Improvement accuracy of cartilage
measurements
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Introduction

Expected outcomes
◦ Autonomous segmentation method
◦ Early detection of Pathology-Associated
Changes
◦ Detection of early onset OA

Problem
◦ Can’t use only grey level features
 Similar cartilage contact zones
 Between the femoral and tibia cartilage
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Introduction
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Introduction

Solution of these drawbacks is the main
objective of this work
◦ Develop a fully automated 3D segmentation
◦ Non-linear diffusion(NLD)

Cartilage lesion classification system by
Outerbridge
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Introduction
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Outline
Introduction
 Segmentation
 Discussion and results

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Segmentation
Previous work: B-Spline snakes
 Develop a fully automated segmentation
method

◦ Using NLD and level sets
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Articular cartilage is difficult to segment
◦ It is a thin structure (1-2mm)
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Another difficulty
◦ Cannot be used to reliably cartilage degeneration
 Multispectral Segmentation

Manual Segmentation
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Segmentation

Non-Linear Diffusion
◦ Overcome meaningful details are removed as
less important details
◦ Enables image simplification
◦ Preserves large intensity discontinuities and
sharpens the edges of objects
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Segmentation
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Non-Linear Diffusion
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I is the image at time t and c is the
diffusivity function
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Segmentation
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Algorithm Development Using 3D Level
Sets
◦ Cartilage surface S is represented in space R
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◦ Three dimensional level set function φ maps
to one dimension R
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Segmentation

Match the cartilage contour as a partial
differential level set equation
|∇φ | describes the normal velocity of the
surface
 F defined range of surface deformations

◦ Match the cartilage contour
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Outline
Introduction
 Segmentation
 Discussion and results

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Discussion and results

Automatic segmentation
◦ Speed up drug development
◦ Improve OA medication

The algorithm development is currently in
the initial phase and more results will be
provided soon
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