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BIOMEDICAL IMAGING GROUP (BIG)
Laboratoire d'imagerie biomédicale (LIB)
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Multivariate Statistical Analysis and Classification of Zygotes

A. Beuchat, C.O.S. Sorzano, D. Sage, A. Senn, F. Urner, M. Unser

Proceedings of the 2005 Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE'05), Lausanne VD, Swiss Confederation, September 1-2, 2005, pp. F04.


The aim was initiated to assess if morphological characteristics of zygotes could be used as markers of future embryo developmental competence using statistical tools. Thus, allowing us to transfer only the embryos that would result in the highest pregnancy rates while minimizing the high order multiple pregnancies. No study has attempted to evaluate the contribution of morphological characteristics automatically detected by an advanced image analysis tool (see Figure).

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AUTHOR="Beuchat, A. and S{\'{a}}nchez Sorzano, C.{\'{O}}. and Sage, D.
	and Senn, A. and Urner, F. and Unser, M.",
TITLE="Multivariate Statistical Analysis and Classification of Zygotes",
BOOKTITLE="Proceedings of the 2005 Annual Meeting of the {S}wiss Society
	for Biomedical Engineering ({SSBE'05})",
YEAR="2005",
editor="",
volume="",
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pages="F04",
address="Lausanne VD, Swiss Confederation",
month="September 1-2,",
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© 2005 SSBE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from SSBE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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