Development and validation of an algorithm for cardiomyocyte beating frequency determination

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The Chagas disease or Tripanosomiasis Americana affects between 16 and 18 million people in endemic areas. This disease affects the beating rate of infected patients' cardiomyocytes. At the Molecular Biology of Chagas Disease Laboratory in Argentina the effect of isolated patient's serum a...

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Autores principales: Wassermann, D., Mejail, M.
Formato: Artículo publishedVersion
Publicado: 2005
Materias:
Algorithms
Biological membranes
Diseases
Image processing
Medical imaging
Patient monitoring
Problem solving
Cardiomyocyte beating frequency
Cardiomyocyte membranes
Monte Carlo experiments
Video sequences
Biomedical engineering
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03029743_v3773LNCS_n_p420_Wassermann
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v3773LNCS_n_p420_Wassermann_oai
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Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires
id I28-R145-paper_03029743_v3773LNCS_n_p420_Wassermann_oai
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spelling I28-R145-paper_03029743_v3773LNCS_n_p420_Wassermann_oai2020-10-19 Wassermann, D. Mejail, M. 2005 The Chagas disease or Tripanosomiasis Americana affects between 16 and 18 million people in endemic areas. This disease affects the beating rate of infected patients' cardiomyocytes. At the Molecular Biology of Chagas Disease Laboratory in Argentina the effect of isolated patient's serum antibodies is studied over rat cardiomyocyte cultures. In this work an image processing application to measure the beating rate of this culture over video sequences is presented. This work is organized as follows. Firstly, a preliminary analysis of the problem is introduced, isolating the main characteristics of the problem. Secondly, a Monte Carlo experiment is designed and used to evaluate the robustness and validity of the algorithm. Finally, an algorithm of order O(T(N log N + N)) for tracking cardiomyocyte membranes is presented, where T is the number of frames and N is the maximum area of the membrane. Its performance is compared against the standard beating rate measure method. © Springer-Verlag Berlin Heidelberg 2005. Fil:Wassermann, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. application/pdf http://hdl.handle.net/20.500.12110/paper_03029743_v3773LNCS_n_p420_Wassermann info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar Lect. Notes Comput. Sci. 2005;3773 LNCS:420-430 Algorithms Biological membranes Diseases Image processing Medical imaging Patient monitoring Problem solving Cardiomyocyte beating frequency Cardiomyocyte membranes Monte Carlo experiments Video sequences Biomedical engineering Development and validation of an algorithm for cardiomyocyte beating frequency determination info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v3773LNCS_n_p420_Wassermann_oai
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-145
collection Repositorio Digital de la Universidad de Buenos Aires (UBA)
topic Algorithms
Biological membranes
Diseases
Image processing
Medical imaging
Patient monitoring
Problem solving
Cardiomyocyte beating frequency
Cardiomyocyte membranes
Monte Carlo experiments
Video sequences
Biomedical engineering
spellingShingle Algorithms
Biological membranes
Diseases
Image processing
Medical imaging
Patient monitoring
Problem solving
Cardiomyocyte beating frequency
Cardiomyocyte membranes
Monte Carlo experiments
Video sequences
Biomedical engineering
Wassermann, D.
Mejail, M.
Development and validation of an algorithm for cardiomyocyte beating frequency determination
topic_facet Algorithms
Biological membranes
Diseases
Image processing
Medical imaging
Patient monitoring
Problem solving
Cardiomyocyte beating frequency
Cardiomyocyte membranes
Monte Carlo experiments
Video sequences
Biomedical engineering
description The Chagas disease or Tripanosomiasis Americana affects between 16 and 18 million people in endemic areas. This disease affects the beating rate of infected patients' cardiomyocytes. At the Molecular Biology of Chagas Disease Laboratory in Argentina the effect of isolated patient's serum antibodies is studied over rat cardiomyocyte cultures. In this work an image processing application to measure the beating rate of this culture over video sequences is presented. This work is organized as follows. Firstly, a preliminary analysis of the problem is introduced, isolating the main characteristics of the problem. Secondly, a Monte Carlo experiment is designed and used to evaluate the robustness and validity of the algorithm. Finally, an algorithm of order O(T(N log N + N)) for tracking cardiomyocyte membranes is presented, where T is the number of frames and N is the maximum area of the membrane. Its performance is compared against the standard beating rate measure method. © Springer-Verlag Berlin Heidelberg 2005.
format Artículo
Artículo
publishedVersion
author Wassermann, D.
Mejail, M.
author_facet Wassermann, D.
Mejail, M.
author_sort Wassermann, D.
title Development and validation of an algorithm for cardiomyocyte beating frequency determination
title_short Development and validation of an algorithm for cardiomyocyte beating frequency determination
title_full Development and validation of an algorithm for cardiomyocyte beating frequency determination
title_fullStr Development and validation of an algorithm for cardiomyocyte beating frequency determination
title_full_unstemmed Development and validation of an algorithm for cardiomyocyte beating frequency determination
title_sort development and validation of an algorithm for cardiomyocyte beating frequency determination
publishDate 2005
url http://hdl.handle.net/20.500.12110/paper_03029743_v3773LNCS_n_p420_Wassermann
http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=artiaex&d=paper_03029743_v3773LNCS_n_p420_Wassermann_oai
work_keys_str_mv AT wassermannd developmentandvalidationofanalgorithmforcardiomyocytebeatingfrequencydetermination
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