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

Table. 1. Descriptive Patterns used for training and classification of different types of
trajectories.
Sample VCL VAP VSL LIN WOB PROG BCF MSM1 MSM2 MSM3 CAF CLASS
Video1 4.58 0.16 0.35 2.24 0.03 4 4 3 1 6 0 A
Video1 2.21 0.35 0.16 0.45 0.16 4 4 6 2 9 0 A
Video1 3.95 0.58 0.5 0.87 0.15 5 5 2 9 11 2 A
Video3 29.05 19.73 3.69 0.19 0.68 150 17 23 9 19 1 B
Video3 30.79 24.05 5.9 0.25 0.78 172 18 4 19 6 0 B
Video3 28.11 21.8 4.27 0.2 0.78 163 7 6 8 1 2 B
Video5 37.42 27.95 16.27 0.58 0.75 208 24 23 24 14 2 C
Video5 51.63 38.84 31.21 0.8 0.75 270 16 27 33 3 0 C
Video5 83.21 50.34 37.29 0.74 0.6 334 6 33 47 10 1 C
Video7 43.11 43.36 42.44 0.98 1.01 302 20 35 4 5 7 D
Video7 72.47 71.55 68.94 0.96 0.99 425 11 38 36 19 21 D
Video7 64.11 62.8 61.23 0.97 0.98 396 16 37 19 1 40 D
Video9 18 17.92 17.7 0.99 1 119 48 6 1 19 8 E
Video9 15.79 17.08 16.86 0.99 1.08 131 54 6 19 7 3 E
Video9 14.84 15.23 14.93 0.98 1.03 109 63 6 19 15 2 E
3.6 Classification of trajectories
After extracting the descriptors for each sperm trajectories, is used a multilayer perceptron
neural networks to classify motility in five classes of movement. The structure of the ANN
comprises eleven input neurons and eight hidden layers.
4. RESULTS
According to experimental tests and with the acquisition system used, the sperm faster
moving at a speed of 25 pixel / sec. and considering that speed of the video obtained by the
digital microscope is 25 frames / sec. this means that the speed of the sperm for each frame
will be up to one pixel, for that reason the window to be used in the proposed method is 7x7
pixels ensuring no loss of tracking.
To evaluate the identification and tracking of sperm cells, are made 10 videos and from each
video is extracted the number of sperm per sample, the percentage of sperm “positives false”
and “negative false” obtained are shown in Table. 2.
Table. 2: Number of sperm identified for each video, determining the number of sperm per
sample and tracking rate.
Sample Sperm number % Positives false % Negative false % Motility
Video 1 76 2.63 6.58 97.37
Video 2 65 1.54 4.62 98.46
Video 3 81 4.94 4.94 95.06
Video 4 86 1.16 0.00 98.84
Video 5 72 4.17 1.39 95.83
Video 6 68 1.47 0.00 98.53
Video 7 70 1.43 4.29 98.57
Video 8 75 0.00 2.67 100.00
Video 9 77 2.60 5.19 97.40
Video 10 83 1.20 2.41 98.80
To evaluate the classification, the training of the ANN was performed with 200 trajectories of
each class obtained in different samples of video. These samples were previously classified by