NEW HUMAN SEMEN ANALYSIS SYSTEM (CASA) USING MICROSCOPIC IMAGE PROCESSING TECHNIQUES

M. ChaudhariN, B. Pawar
{"title":"NEW HUMAN SEMEN ANALYSIS SYSTEM (CASA) USING MICROSCOPIC IMAGE PROCESSING TECHNIQUES","authors":"M. ChaudhariN, B. Pawar","doi":"10.21917/IJIVP.2016.0201","DOIUrl":null,"url":null,"abstract":"Computer assisted semen analysis (CASA) helps the pathologist or fertility specialist to evaluate the human semen. Detail analysis of spermatozoa like morphology and motility is very important in the process of intrauterine insemination (IUI) or In-vitro fertilization (IVF) in infertile couple. The main objective for this new semen analysis is to provide a low cost solution to the pathologist and gynecologist for the routine raw semen analysis, finding the concentration of the semen with dynamic background removal and classify the spermatozoa type (grade) according to the motility and structural abnormality as per the WHO criteria. In this paper a new system , computer assisted semen analysis system is proposed in which hybrid approach is used to identify the moving object, scan line algorithm is applied for confirmation of the objects having tails, so that we can count the actual number of spermatozoa. For removal of background initially the dynamic background generation algorithm is proposed to create a background for background subtraction stage. The standard data set is created with 40× and 100× magnification from the different raw semen s. For testing the efficiency of proposed algorithm, same frames are applied to the existing algorithm. Another module of the system is focused on finding the motility and Type classification of individual spermatozoa.","PeriodicalId":30615,"journal":{"name":"ICTACT Journal on Image and Video Processing","volume":"7 1","pages":"1381-1391"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICTACT Journal on Image and Video Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21917/IJIVP.2016.0201","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Computer assisted semen analysis (CASA) helps the pathologist or fertility specialist to evaluate the human semen. Detail analysis of spermatozoa like morphology and motility is very important in the process of intrauterine insemination (IUI) or In-vitro fertilization (IVF) in infertile couple. The main objective for this new semen analysis is to provide a low cost solution to the pathologist and gynecologist for the routine raw semen analysis, finding the concentration of the semen with dynamic background removal and classify the spermatozoa type (grade) according to the motility and structural abnormality as per the WHO criteria. In this paper a new system , computer assisted semen analysis system is proposed in which hybrid approach is used to identify the moving object, scan line algorithm is applied for confirmation of the objects having tails, so that we can count the actual number of spermatozoa. For removal of background initially the dynamic background generation algorithm is proposed to create a background for background subtraction stage. The standard data set is created with 40× and 100× magnification from the different raw semen s. For testing the efficiency of proposed algorithm, same frames are applied to the existing algorithm. Another module of the system is focused on finding the motility and Type classification of individual spermatozoa.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用显微图像处理技术的新型人类精液分析系统(casa)
计算机辅助精液分析(CASA)可以帮助病理学家或生育专家评估人类精液。精子样形态和运动的详细分析在不育夫妇进行宫内人工授精(IUI)或体外受精(IVF)的过程中非常重要。这种新型精液分析的主要目的是为病理学家和妇科医生提供一种低成本的常规原始精液分析解决方案,发现动态背景去除的精液浓度,并根据运动和结构异常根据WHO标准对精子类型(等级)进行分类。本文提出了一种新的系统——计算机辅助精液分析系统,该系统采用混合方法对运动物体进行识别,采用扫描线算法对有尾物体进行确认,从而计算出精子的实际数量。对于初始背景的去除,提出了动态背景生成算法,为背景减除阶段生成背景。从不同的原始图像中创建了40倍和100倍放大的标准数据集。为了测试算法的效率,将相同的帧应用于现有算法。该系统的另一个模块侧重于寻找单个精子的活力和类型分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
8 weeks
期刊最新文献
DIMENSIONALITY REDUCTION BASED CLASSIFICATION USING GENERATIVE ADVERSARIAL NETWORKS DATASET GENERATION ADVANCED COLOR COVERT IMAGE SHARING USING ARNOLD CAT MAP AND VISUAL CRYPTOGRAPHY STREETLIGHT OBJECTS RECOGNITION BY REGION AND HISTOGRAM FEATURES IN AN AUTONOMOUS VEHICLE SYSTEM SMART GESTURE USING REAL TIME OBJECT TRACKING CLASSIFICATION OF BRAIN TUMOR USING BEES SWARM OPTIMISATION
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1