Automatic Blastomere Recognition from a Single Embryo Image
Joint Authors
Duan, Fu-qing
Tian, Yun
Wang, Wei
Wang, Wei-zhou
Yin, Ya-bo
Zhou, Ming-Quan
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-14
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
The number of blastomeres of human day 3 embryos is one of the most important criteria for evaluating embryo viability.
However, due to the transparency and overlap of blastomeres, it is a challenge to recognize blastomeres automatically using a single embryo image.
This study proposes an approach based on least square curve fitting (LSCF) for automatic blastomere recognition from a single image.
First, combining edge detection, deletion of multiple connected points, and dilation and erosion, an effective preprocessing method was designed to obtain part of blastomere edges that were singly connected.
Next, an automatic recognition method for blastomeres was proposed using least square circle fitting.
This algorithm was tested on 381 embryo microscopic images obtained from the eight-cell period, and the results were compared with those provided by experts.
Embryos were recognized with a 0 error rate occupancy of 21.59%, and the ratio of embryos in which the false recognition number was less than or equal to 2 was 83.16%.
This experiment demonstrated that our method could efficiently and rapidly recognize the number of blastomeres from a single embryo image without the need to reconstruct the three-dimensional model of the blastomeres first; this method is simple and efficient.
American Psychological Association (APA)
Tian, Yun& Yin, Ya-bo& Duan, Fu-qing& Wang, Wei-zhou& Wang, Wei& Zhou, Ming-Quan. 2014. Automatic Blastomere Recognition from a Single Embryo Image. Computational and Mathematical Methods in Medicine،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-486375
Modern Language Association (MLA)
Tian, Yun…[et al.]. Automatic Blastomere Recognition from a Single Embryo Image. Computational and Mathematical Methods in Medicine No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-486375
American Medical Association (AMA)
Tian, Yun& Yin, Ya-bo& Duan, Fu-qing& Wang, Wei-zhou& Wang, Wei& Zhou, Ming-Quan. Automatic Blastomere Recognition from a Single Embryo Image. Computational and Mathematical Methods in Medicine. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-486375
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-486375