An automated system for detecting and measuring nailfold capillaries

Michael Berks; Phil Tresadern; Graham Dinsdale; Andrea Murray; Tonia Moore; Ariane Herrick; Chris Taylor

doi:10.1007/978-3-319-10404-1_82

An automated system for detecting and measuring nailfold capillaries

Michael Berks, Phil Tresadern, Graham Dinsdale, Andrea Murray, Tonia Moore, Ariane Herrick, Chris Taylor

Research output: Contribution to journal › Article › peer-review

Abstract

Nailfold capillaroscopy is an established qualitative technique in the assessment of patients displaying Raynaud's phenomenon. We describe a fully automated system for extracting quantitative biomarkers from capillaroscopy images, using a layered machine learning approach. On an unseen set of 455 images, the system detects and locates individual capillaries as well as human experts, and makes measurements of vessel morphology that reveal statistically significant differences between patients with (relatively benign) primary Raynaud's phenomenon, and those with potentially life-threatening systemic sclerosis. © 2014 Springer International Publishing.

Original language	English
Pages (from-to)	658-665
Number of pages	7
Journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8673
Issue number	1
DOIs	https://doi.org/10.1007/978-3-319-10404-1_82
Publication status	Published - 2014

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10.1007/978-3-319-10404-1_82

http://springerlink.com/content/0302-9743/copyright/2005/

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title = "An automated system for detecting and measuring nailfold capillaries",

abstract = "Nailfold capillaroscopy is an established qualitative technique in the assessment of patients displaying Raynaud's phenomenon. We describe a fully automated system for extracting quantitative biomarkers from capillaroscopy images, using a layered machine learning approach. On an unseen set of 455 images, the system detects and locates individual capillaries as well as human experts, and makes measurements of vessel morphology that reveal statistically significant differences between patients with (relatively benign) primary Raynaud's phenomenon, and those with potentially life-threatening systemic sclerosis. {\textcopyright} 2014 Springer International Publishing.",

author = "Michael Berks and Phil Tresadern and Graham Dinsdale and Andrea Murray and Tonia Moore and Ariane Herrick and Chris Taylor",

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An automated system for detecting and measuring nailfold capillaries. / Berks, Michael; Tresadern, Phil; Dinsdale, Graham et al.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8673, No. 1, 2014, p. 658-665.

Research output: Contribution to journal › Article › peer-review

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AU - Berks, Michael

AU - Tresadern, Phil

AU - Dinsdale, Graham

AU - Murray, Andrea

AU - Moore, Tonia

AU - Herrick, Ariane

AU - Taylor, Chris

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PY - 2014

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N2 - Nailfold capillaroscopy is an established qualitative technique in the assessment of patients displaying Raynaud's phenomenon. We describe a fully automated system for extracting quantitative biomarkers from capillaroscopy images, using a layered machine learning approach. On an unseen set of 455 images, the system detects and locates individual capillaries as well as human experts, and makes measurements of vessel morphology that reveal statistically significant differences between patients with (relatively benign) primary Raynaud's phenomenon, and those with potentially life-threatening systemic sclerosis. © 2014 Springer International Publishing.

AB - Nailfold capillaroscopy is an established qualitative technique in the assessment of patients displaying Raynaud's phenomenon. We describe a fully automated system for extracting quantitative biomarkers from capillaroscopy images, using a layered machine learning approach. On an unseen set of 455 images, the system detects and locates individual capillaries as well as human experts, and makes measurements of vessel morphology that reveal statistically significant differences between patients with (relatively benign) primary Raynaud's phenomenon, and those with potentially life-threatening systemic sclerosis. © 2014 Springer International Publishing.

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DO - 10.1007/978-3-319-10404-1_82

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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ER -

An automated system for detecting and measuring nailfold capillaries

Abstract

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