title: Classification of hyperactivated spermatozoa using a robust Minimum Bounding Square Ratio algorithm.
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.
authors: Department of Computer Science, University of Denver, Denver, CO, USA. nkaula@cs.du.edu
authors: Norbert
authors: N
authors: Kaula
authors: Anneliese
authors: A
authors: Andrews
authors: Catherine
authors: C
authors: Durso
authors: Christopher
authors: C
authors: Dixon
authors: James K
authors: JK
authors: Graham
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D008297:Male; D055101:Semen Analysis / Q000379:methods*; D013094:Spermatozoa / Q000145:classification / Q000502:physiology*