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A survey on multisperm tracking for sperm motility measurement
Hidayatullah P.a, Mengko T.L.E.R.a, Munir R.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Jawa Barat, 40132, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]Sperm motility is the main criterion in evaluating the quality of semen. Sperm motility measurements can be done in many ways. But the most effective way is to simultaneously track all sperm and calculate the motility parameters of Computer Aided Sperm Analysis (CASA). Based on those parameters, the sperm motility was categorized and the percentage of motile sperm was calculated. This paper presents the analysis of the currently available multisperm tracking methods for sperm motility measurement. In this paper, we discuss why sperm motility is an important parameter for assessing sperm quality and compare several multisperm tracking methods along with an analysis of their advantages and disadvantages. It can be concluded that the main problem in sperm motility measurement is having a good multisperm tracking to obtain precise sperm paths with an efficient computation on semen with high sperm concentrations. If the generated path precision is high, then the CASA parameters calculation results will better describe the actual sperm motility conditions. None of the existing methods can produce precise trajectories in complex cases yet. The complex case is, especially, when sperms collide or cover each other in the situation of large sperm counts appears in one microscope field of view.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]CASA,Multisperm tracking,Object tracking,Sperm motility[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.18178/ijmlc.2017.7.5.637[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]