An automatic system for spermiogram analysis based on image processing techniques and Support Vector Machines

N. V. REVOLLO; GONZALEZ-JOSE ROLANDO; CLAUDIO DELRIEUX

Congreso; SIPAIM; 2017

UNIVERSIDAD NACIONAL DE COLOMBIA

Image-based diagnosis becoming one of the most important areas in medicine, as the diversity and sophistication of imaging techniques arebeing increasingly used in hospitals and medical centers. This, however, raises the issue of having image analysis capabilities that go with thistrend, to be able to use medical imagery to provide fast and accurate diagnosis. In andrology in particular, the spermiogram analysis is consideredthe most significant study to evaluate the male reproductive capacity. Spermiograms can be produced with relatively little effort and cost, since theyrequire only standard procedures for sample treatment. However, an adequate assessment of sperm quality requires the careful inspection by higlytrained specialists, requiring time, and being prone to high inter- and intra-specialist variances. In this paper we present a system for automaticspermiogram analysis using image processing and machine learning techniques. The system was trained using a repository of spermiograms andthe opinion of several experts in andrology and in human reproduction, using different information sources and classificat