Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling

Paul Bromiley; Eleni Kariki; Judith Adams; Timothy Cootes

doi:10.1007/978-3-319-74113-0_12

Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling

Paul Bromiley^*, Eleni Kariki, Judith Adams, Timothy Cootes

^*Corresponding author for this work

Division of Informatics, Imaging & Data Sciences (L5)

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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Abstract

Osteoporotic vertebral fractures (VFs) are under-diagnosed, creating an opportunity for computer-aided, opportunistic fracture identification in clinical images. VF diagnosis and grading in clinical practice involves comparisons of vertebral body heights. However, machine vision systems can provide a high-resolution segmentation of the vertebrae and fully characterise their shape and appearance, potentially allowing improved diagnostic accuracy. We compare approaches based on vertebral heights to shape/appearance modelling combined with k-nearest neighbours and random forest (RF) classifiers, on both dual-energy X-ray absorptiometry images and computed tomography image volumes. We demonstrate that the combination of RF classifiers and appearance modelling, which is novel in this application, results in a significant (up to 60% reduction in false positive rate at 80% sensitivity) improvement in diagnostic accuracy.

Original language	English
Title of host publication	Computational Methods and Clinical Applications in Musculoskeletal Imaging
Subtitle of host publication	5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers
Editors	Ben Glocker, Jianhua Yao, Tomaz Vrtovec, Alejandro Frangi, Guoyan Zheng
Place of Publication	Cham
Publisher	Springer Cham
Pages	133-147
Number of pages	15
ISBN (Electronic)	9783319741130
ISBN (Print)	9783319741123
DOIs	https://doi.org/10.1007/978-3-319-74113-0_12
Publication status	Published - 10 Jan 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10734
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Keywords

osteoporosis
shape modelling
vertebral fracture

Access to Document

10.1007/978-3-319-74113-0_12

MICCAI-MSKI2017_013_final_v3Accepted author manuscript, 598 KB

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Bromiley, P., Kariki, E., Adams, J., & Cootes, T. (2018). Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling. In B. Glocker, J. Yao, T. Vrtovec, A. Frangi, & G. Zheng (Eds.), Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers (pp. 133-147). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10734). Springer Cham. https://doi.org/10.1007/978-3-319-74113-0_12

Bromiley, Paul ; Kariki, Eleni ; Adams, Judith et al. / Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling. Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. editor / Ben Glocker ; Jianhua Yao ; Tomaz Vrtovec ; Alejandro Frangi ; Guoyan Zheng. Cham : Springer Cham, 2018. pp. 133-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Osteoporotic vertebral fractures (VFs) are under-diagnosed, creating an opportunity for computer-aided, opportunistic fracture identification in clinical images. VF diagnosis and grading in clinical practice involves comparisons of vertebral body heights. However, machine vision systems can provide a high-resolution segmentation of the vertebrae and fully characterise their shape and appearance, potentially allowing improved diagnostic accuracy. We compare approaches based on vertebral heights to shape/appearance modelling combined with k-nearest neighbours and random forest (RF) classifiers, on both dual-energy X-ray absorptiometry images and computed tomography image volumes. We demonstrate that the combination of RF classifiers and appearance modelling, which is novel in this application, results in a significant (up to 60% reduction in false positive rate at 80% sensitivity) improvement in diagnostic accuracy.",

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Bromiley, P, Kariki, E, Adams, J & Cootes, T 2018, Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling. in B Glocker, J Yao, T Vrtovec, A Frangi & G Zheng (eds), Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10734, Springer Cham, Cham, pp. 133-147. https://doi.org/10.1007/978-3-319-74113-0_12

Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling. / Bromiley, Paul; Kariki, Eleni; Adams, Judith et al.
Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. ed. / Ben Glocker; Jianhua Yao; Tomaz Vrtovec; Alejandro Frangi; Guoyan Zheng. Cham: Springer Cham, 2018. p. 133-147 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10734).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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T1 - Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling

AU - Bromiley, Paul

AU - Kariki, Eleni

AU - Adams, Judith

AU - Cootes, Timothy

PY - 2018/1/10

Y1 - 2018/1/10

N2 - Osteoporotic vertebral fractures (VFs) are under-diagnosed, creating an opportunity for computer-aided, opportunistic fracture identification in clinical images. VF diagnosis and grading in clinical practice involves comparisons of vertebral body heights. However, machine vision systems can provide a high-resolution segmentation of the vertebrae and fully characterise their shape and appearance, potentially allowing improved diagnostic accuracy. We compare approaches based on vertebral heights to shape/appearance modelling combined with k-nearest neighbours and random forest (RF) classifiers, on both dual-energy X-ray absorptiometry images and computed tomography image volumes. We demonstrate that the combination of RF classifiers and appearance modelling, which is novel in this application, results in a significant (up to 60% reduction in false positive rate at 80% sensitivity) improvement in diagnostic accuracy.

AB - Osteoporotic vertebral fractures (VFs) are under-diagnosed, creating an opportunity for computer-aided, opportunistic fracture identification in clinical images. VF diagnosis and grading in clinical practice involves comparisons of vertebral body heights. However, machine vision systems can provide a high-resolution segmentation of the vertebrae and fully characterise their shape and appearance, potentially allowing improved diagnostic accuracy. We compare approaches based on vertebral heights to shape/appearance modelling combined with k-nearest neighbours and random forest (RF) classifiers, on both dual-energy X-ray absorptiometry images and computed tomography image volumes. We demonstrate that the combination of RF classifiers and appearance modelling, which is novel in this application, results in a significant (up to 60% reduction in false positive rate at 80% sensitivity) improvement in diagnostic accuracy.

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Bromiley P, Kariki E, Adams J, Cootes T. Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling. In Glocker B, Yao J, Vrtovec T, Frangi A, Zheng G, editors, Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers. Cham: Springer Cham. 2018. p. 133-147. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-74113-0_12

Classification of Osteoporotic Vertebral Fractures Using Shape and Appearance Modelling

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