ARUP; ISBN: 978-0-9562121-5-3 - CMBBE 2012 - Cardiff University

Method for classification of porcine sperm
movement using artificial intelligence.
1. ABSTRACT
H. A. Rojas 1 , J. A. Rojas 1 , G. A Zuleta 1 , C. A. Madrigal 2
This paper presents an artificial vision system for analysis and classification of cell motility of
porcine spermatozoa. In the identification of sperm were used morphology features. To avoid
loss of information for the occlusions between sperm, use a predictor through a Kalman filter.
In evaluating the motion, the descriptors VCL, VAP, VSL, LIN, WOB, PROG, and BCF,
used frequently in the literature, were extracted, also propose the inclusion of a new descriptor
(MSM) based on the statistical mode of motion and crosses between VAP and VSL. The
classifier used is a multilayer perceptron ANN. The results obtained show that with this
method of detection and classification, the movement paths of porcine sperm cells are
calculated to an accuracy of up to 98%.
2. INTRODUCTION
High consumption of meat requires a large production of pigs in different races, so it is
looking to have a high growth, improving the semen evaluation times and delivering faster the
product orders to its various customers.
In the evaluation of semen quality is analyzed parameters such as motility, concentration and
morphological abnormalities, resulting many differences in the results. Order to overcome
these differences have been proposed, turbidimetry systems, spectroscopic and photometric
methods (1), however, these systems provide an approximate estimate of total sperm, such as
the combination of total sperm concentration and total mobility, without taking into account
the evaluation of individual sperm. There are other techniques more precise, such as flow
cytometry, which provides the evaluation of concentration and the cellulose-acetate/nitrate
filter for the speed analysis, which allows measurement of key parameter semen; but several
times the classification process of porcine sperm motility is manually carry out, which it is a
quiet slow and subjective process depending on individual abilities of the analyst, creating a
high degree of error and, as consequence, low reliability in consumer. Therefore, it has been
used computer assisted sperm analyses (CASA), which is able to determine objectively
morphology features and motility, they are not manually measurable or observable.
In (2) it is studied the suitability of features recognition for exploration data provided,
provided by computer assisted design (CAD) for semen analysis, using the Hobson tracking
sperm (Hobson Tracking Systems, Sheffield). In (1) it is carried out a review of the state of
the art and troubles related to Computer-assisted sperm analysis (CASA) technology, which
has been a technology lets evaluate characteristics such as movement, speed and morphology.
In (3) are evaluated morphological and geometrical characteristics, like area, perimeter,
length, wideness, form and mass factor, with automated sperm-head morphometry analysis
1
Estudiante, Ingeniería de Sistemas, Instituto Tecnológico Metropolitano, Facultad de Ingeniería, Sede
Fraternidad, Medellín CLL 54 # 30 - 01, Antioquia, Colombia.
2
Profesor, Ingeniero Electrónico, Instituto Tecnológico Metropolitano, Faculta de Ingeniería, Sede Fraternidad,
Medellín CLL 54 # 30 - 01, Antioquia, Colombia.