Van Raemdonck, L.E.M., Ur-Rehman, A., Davila-Garcia, M.L. et al. (3 more authors) (2016) Human Sperm Morphology Analysis for Assisted Reproduction Techniques. In: Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2015. , 06-08 Oct 2015, Bonn, Germany. IEEE
Abstract
The analysis of human sperm as part of infertility investigations or assisted conception treatments is a labor inten- sive process reliant upon the skill of the observer and as such prone to human error. Therefore, there is a need to develop automated systems that can adequately assess the concentration, motility and morphology of live sperm. This paper presents an algorithm for analyzing the morphology of motile sperm. Techniques for eliminating the background, segmentation of the cells and template matching techniques are used to analyze the morphology in two stages: first stage eliminates the immotile cells and at the second stage the morphology of the motile cells is analyzed. Results are presented with real sperm samples recorded in the andrology lab at the University of Sheffield. The performance of the proposed algorithm is analyzed in terms of accuracy and complexity. The proposed algorithm demonstrates high accuracy under variable conditions.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Keywords: | Classification; Images; Video; Structural similarity measure; Motile sperm |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Feb 2016 17:14 |
Last Modified: | 19 Dec 2022 13:32 |
Published Version: | http://dx.doi.org/10.1109/SDF.2015.7347714 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/SDF.2015.7347714 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:93488 |