Classification of hyperactivated spermatozoa using a robust minimum bounding square ratio algorithm

Author

Kaula, Norbert ; Andrews, Anneliese ; Durso, Catherine ; Dixon, Christopher ; Graham, James K.

Author_Institution

Dept. of Comput. Sci., Univ. of Denver, Denver, CO, USA

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

4941

Lastpage

4944

Abstract

A method for automatically identifying and classifying hyperactivated spermatozoa trajectories is described. This physiologically-based computerized algorithm captures the motion behavior of sperm during hyperactivation. A novel minimum bounding square ratio (MBSR) algorithm classifies spermatoza as hyperactivated, transitional or progressive. Classification boundaries were established on selected trajectory data from a single stallion and then tested on random trajectories of sperm from other stallions. MBSR classified sperm in a robust and effective manner.

Keywords

cell motility; medical computing; pattern classification; automatic identification; classification boundaries; hyperactivated spermatozoa trajectories; physiologically-based computerized algorithm; random trajectories; robust minimum bounding square ratio algorithm; Algorithms; Animals; Humans; Male; Semen Analysis; Spermatozoa;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5332709

Filename

5332709