The Effect of Nonlinear Wavelet Transform Based De-noising in Sperm Abnormality Classification

Hamza Osman Ilhan, Ibrahim Onur Sigirci, Gorkem Serbes, Nizamettin Aydin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Morphological sperm analysis is one of the crucial steps in the male-based infertility diagnosis. Currently, analyses are mostly performed by visual assessment technique because of its easy implementation, quick response and cheapness properties. However, the expertise level of the observer has great importance in the visual assessment technique. Results can be different and misleading according to the observer analysis capability. Therefore, human factor should be eliminated and the analysis should be performed by an objective computerized system. In this study, we used descriptor-based features in the classification of the normal, abnormal and non-sperm patches. Additionally, we investigated the effects of two de-noising techniques in the classification performance due to the presence of noises in the patches. Results indicate that the de-noising processes have great importance in the classification performance. Moreover, a wavelet based adaptive de-noising approach dramatically increased the performance to 86% with support vector machine polynomial kernel classifier.

Original languageEnglish
Title of host publicationUBMK 2018 - 3rd International Conference on Computer Science and Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages658-661
Number of pages4
ISBN (Electronic)9781538678930
DOIs
Publication statusPublished - 6 Dec 2018
Externally publishedYes
Event3rd International Conference on Computer Science and Engineering, UBMK 2018 - Sarajevo, Bosnia and Herzegovina
Duration: 20 Sept 201823 Sept 2018

Publication series

NameUBMK 2018 - 3rd International Conference on Computer Science and Engineering

Conference

Conference3rd International Conference on Computer Science and Engineering, UBMK 2018
Country/TerritoryBosnia and Herzegovina
CitySarajevo
Period20/09/1823/09/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Adaptive Denoising
  • Speed Up Robust Features
  • Sperm Morphological Analysis
  • Support Vector Machine

Fingerprint

Dive into the research topics of 'The Effect of Nonlinear Wavelet Transform Based De-noising in Sperm Abnormality Classification'. Together they form a unique fingerprint.

Cite this