A novel data acquisition and analyzing approach to spermiogram tests. (March 2018)

• Record Type: Journal Article
• Authors: Ilhan, Hamza Osman; Aydin, Nizamettin
• Is Part Of: Biomedical signal processing and control. Volume 41(2018)
• Page Start: 129
• Page End: 139
• Publication Date: 2018-03
• Subjects: Video stabilization -- Descriptor -- Spermiogram -- Sperm counting -- Speed up robust features -- Binary robust invariant scalable keypoints -- Features from accelerated segment test; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.11.009
• Languages: English
• ISSNs: 1746-8094

Abstract

Graphical abstract: Highlights: We proposed a novel data acquisition and analyzing approach to spermiogram tests. Proposed approach is cheap, reliable, modular, portable and platform independent. Proposed approach eliminates the observer variability in visual assessment analysis. Feature matching based stabilization was utilized for the stable video microscopy. Performance of the approach was evaluated by comparing to visual assessment technique. Abstract: Spermiogram tests are currently performed in two ways; computer assisted and visual assessment. Computerized techniques are costly and parameter dependent. Therefore, it is not preferred in many laboratories. Analysis based on visual assessment technique is subjective. In this study, we proposed a new computerized approach in which data acquisition is performed as in visual assessment, but analysis is done by computer. This approach provides more generalized results, requires less parameters due to the usage of standard counting chambers as in visual assessment technique, and cheaper than the other computerized techniques. Proposed approach includes two modules; video stabilization and motile sperm detection module. Stabilization is a requirement because it is impossible to fix proposed approach in ocular part completely. Otherwise, vibration affects the detection process of motile sperms. In this respect, feature-matching video stabilization idea is firstly utilized within the video-microscopy concept. Several feature extraction techniques were tested to sustain more stable videos in stabilization module. Motile sperm detection algorithm is then adapted to evaluate the efficiency of video stabilization and analyzing part. In case of vibrated frame sequence, the detection of total motile sperms concludes immediate peak values while it is around average values in stable frames. Samples were also evaluated by an expert with the visual assessment technique. Comparative tables and figures emphasize that the proposed approach can be employed in laboratories due to the high correlation with the visual assessment results.