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Sperm detection in video frames of semen sample using morphology and effective ellipse detection method

CASA (Computer assisted semen analysis) systems are designed to assist Andrologist labour. Most available CASA systems are not accurate or so expensive. Therefore labours use manual methods to provide parameters. Although some companies have achieved appropriate accuracy, they have not released thei...

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Detalles Bibliográficos
Autores principales: Mahdavi, H.S., Monadjemi, A., Vafae, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347227/
https://www.ncbi.nlm.nih.gov/pubmed/22606677
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author Mahdavi, H.S.
Monadjemi, A.
Vafae, A.
author_facet Mahdavi, H.S.
Monadjemi, A.
Vafae, A.
author_sort Mahdavi, H.S.
collection PubMed
description CASA (Computer assisted semen analysis) systems are designed to assist Andrologist labour. Most available CASA systems are not accurate or so expensive. Therefore labours use manual methods to provide parameters. Although some companies have achieved appropriate accuracy, they have not released their methods. So proposing methods in this area might be useful for groups who intend to design new CASA system. One of the parameters which these systems compute is sperm count. In this paper we introduce our algorithm which can count sperms with an acceptable accuracy. Sperm count or concentration is one determinant parameter in male fertility. Our program preprocesses the video frame or image of semen sample under the microscope recorded by camera, then use morphology and effective ellipse detection method techniques to segment sperms and then count appropriate sperms.
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spelling pubmed-33472272012-05-09 Sperm detection in video frames of semen sample using morphology and effective ellipse detection method Mahdavi, H.S. Monadjemi, A. Vafae, A. J Med Signals Sens Original Article CASA (Computer assisted semen analysis) systems are designed to assist Andrologist labour. Most available CASA systems are not accurate or so expensive. Therefore labours use manual methods to provide parameters. Although some companies have achieved appropriate accuracy, they have not released their methods. So proposing methods in this area might be useful for groups who intend to design new CASA system. One of the parameters which these systems compute is sperm count. In this paper we introduce our algorithm which can count sperms with an acceptable accuracy. Sperm count or concentration is one determinant parameter in male fertility. Our program preprocesses the video frame or image of semen sample under the microscope recorded by camera, then use morphology and effective ellipse detection method techniques to segment sperms and then count appropriate sperms. Medknow Publications & Media Pvt Ltd 2011 /pmc/articles/PMC3347227/ /pubmed/22606677 Text en Copyright: © Journal of Medical Signals and Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Mahdavi, H.S.
Monadjemi, A.
Vafae, A.
Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title_full Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title_fullStr Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title_full_unstemmed Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title_short Sperm detection in video frames of semen sample using morphology and effective ellipse detection method
title_sort sperm detection in video frames of semen sample using morphology and effective ellipse detection method
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347227/
https://www.ncbi.nlm.nih.gov/pubmed/22606677
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