Title :
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
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5332709
