Simulating nailfold capillaroscopy sequences to evaluate algorithms for blood flow estimation

P. A. Tresadern; M. Berks; Andrea Murray; Graham Dinsdale; C. J. Taylor; A. L. Herrick

doi:10.1109/EMBC.2013.6610081

Simulating nailfold capillaroscopy sequences to evaluate algorithms for blood flow estimation

P. A. Tresadern, M. Berks, Andrea Murray, Graham Dinsdale, C. J. Taylor, A. L. Herrick

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

Abstract

The effects of systemic sclerosis (SSc) - a disease of the connective tissue causing blood flow problems that can require amputation of the fingers - can be observed indirectly by imaging the capillaries at the nailfold, though taking quantitative measures such as blood flow to diagnose the disease and monitor its progression is not easy. Optical flow algorithms may be applied, though without ground truth (i.e. known blood flow) it is hard to evaluate their accuracy. We propose an image model that generates realistic capillaroscopy videos with known flow, and use this model to quantify the effect of flow rate, cell density and contrast (among others) on estimated flow. This resource will help researchers to design systems that are robust under real-world conditions. © 2013 IEEE.

Original language	English
Article number	6610081
Pages (from-to)	2636-2639
Number of pages	3
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology. Proceedings
DOIs	https://doi.org/10.1109/EMBC.2013.6610081
Publication status	Published - 2013

Access to Document

10.1109/EMBC.2013.6610081

Cite this

@article{f9d3343ebace4afcae67efe680d9ceeb,

title = "Simulating nailfold capillaroscopy sequences to evaluate algorithms for blood flow estimation",

abstract = "The effects of systemic sclerosis (SSc) - a disease of the connective tissue causing blood flow problems that can require amputation of the fingers - can be observed indirectly by imaging the capillaries at the nailfold, though taking quantitative measures such as blood flow to diagnose the disease and monitor its progression is not easy. Optical flow algorithms may be applied, though without ground truth (i.e. known blood flow) it is hard to evaluate their accuracy. We propose an image model that generates realistic capillaroscopy videos with known flow, and use this model to quantify the effect of flow rate, cell density and contrast (among others) on estimated flow. This resource will help researchers to design systems that are robust under real-world conditions. {\textcopyright} 2013 IEEE.",

author = "Tresadern, {P. A.} and M. Berks and Andrea Murray and Graham Dinsdale and Taylor, {C. J.} and Herrick, {A. L.}",

year = "2013",

doi = "10.1109/EMBC.2013.6610081",

language = "English",

pages = "2636--2639",

journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology. Proceedings",

issn = "0589-1019",

publisher = "IEEE",

}

TY - JOUR

T1 - Simulating nailfold capillaroscopy sequences to evaluate algorithms for blood flow estimation

AU - Tresadern, P. A.

AU - Berks, M.

AU - Murray, Andrea

AU - Dinsdale, Graham

AU - Taylor, C. J.

AU - Herrick, A. L.

PY - 2013

Y1 - 2013

N2 - The effects of systemic sclerosis (SSc) - a disease of the connective tissue causing blood flow problems that can require amputation of the fingers - can be observed indirectly by imaging the capillaries at the nailfold, though taking quantitative measures such as blood flow to diagnose the disease and monitor its progression is not easy. Optical flow algorithms may be applied, though without ground truth (i.e. known blood flow) it is hard to evaluate their accuracy. We propose an image model that generates realistic capillaroscopy videos with known flow, and use this model to quantify the effect of flow rate, cell density and contrast (among others) on estimated flow. This resource will help researchers to design systems that are robust under real-world conditions. © 2013 IEEE.

AB - The effects of systemic sclerosis (SSc) - a disease of the connective tissue causing blood flow problems that can require amputation of the fingers - can be observed indirectly by imaging the capillaries at the nailfold, though taking quantitative measures such as blood flow to diagnose the disease and monitor its progression is not easy. Optical flow algorithms may be applied, though without ground truth (i.e. known blood flow) it is hard to evaluate their accuracy. We propose an image model that generates realistic capillaroscopy videos with known flow, and use this model to quantify the effect of flow rate, cell density and contrast (among others) on estimated flow. This resource will help researchers to design systems that are robust under real-world conditions. © 2013 IEEE.

U2 - 10.1109/EMBC.2013.6610081

DO - 10.1109/EMBC.2013.6610081

M3 - Article

C2 - 24110268

SN - 0589-1019

SP - 2636

EP - 2639

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology. Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology. Proceedings

M1 - 6610081

ER -

Simulating nailfold capillaroscopy sequences to evaluate algorithms for blood flow estimation

Abstract

Access to Document

Fingerprint

Cite this