Automated Sperm Head Detection Using Intersecting Cortical Model Optimised by Particle Swarm Optimization

作者：Tan Weng Chun; Isa Nor Ashidi Mat

来源：PLos One, 2016, 11(9): e0162985.

DOI：10.1371/journal.pone.0162985

In human spermmotility analysis, sperm segmentation plays an important role to determine the location of multiple sperms. To ensure an improved segmentation result, the Laplacian of Gaussian filter is implemented as a kernel in a pre-processing step before applying the image segmentation process to automatically segment and detect human spermatozoa. This study proposes an intersecting cortical model (ICM), which was derived from several visual cortex models, to segment the spermhead region. However, the proposed method suffered from parameter selection; thus, the ICM network is optimised using particle swarm optimization where feature mutual information is introduced as the new fitness function. The final results showed that the proposed method is more accurate and robust than four state-of-the-artsegmentation methods. The proposed method resulted in rates of 98.14%, 98.82%, 86.46% and 99.81% in accuracy, sensitivity, specificity and precision, respectively, after testing with 1200 sperms. The proposed algorithm is expected to be implemented in analysing spermmotility because of the robustness and capability of this algorithm.

• 出版日期2016-9-15