Voxel classification of periprosthetic tissues in clinical computed tomography of loosened hip prostheses

We present an automated algorithm which classifies periprosthetic tissues in CT scans of patients with loosened hip prostheses. To our knowledge this is the first application of CT voxel classification to periprosthetic tissues of the hip. We use several image features including multi-scale image in...

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Bibliographic Details
Published in2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro pp. 1341 - 1344
Main Authors Malan, D F, Botha, C P, Nelissen, R G H H, Valstar, E R
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2010
Subjects
Automatic
Biomedical imaging
Bones
classification
Computed tomography
Hip
Image segmentation
Lesions
Magnetic resonance imaging
osteolysis
periprosthetic
Prosthetics
Radiography
segmentation
Solid modeling
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Summary:We present an automated algorithm which classifies periprosthetic tissues in CT scans of patients with loosened hip prostheses. To our knowledge this is the first application of CT voxel classification to periprosthetic tissues of the hip. We use several image features including multi-scale image intensity, multi-scale image gradient and distance metrics. Seven classifier types were trained using five manually segmented clinical CT datasets, and their classification performance compared to manual segmentations using a leave-one-out scheme. Using this technique we are able to correctly segment the majority of each of the six tissue categories, in spite of low bone densities, metal-induced CT imaging artefacts and inter-patient and inter-scan variation. Our automated classifier forms a pragmatic first step towards eventual automatic tissue segmentation.
ISBN:9781424441259
1424441250
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2010.5490245