一种新的FISH信号融合检测方法诊断慢性髓细胞白血病

Ashraf AbdelRaouf
{"title":"一种新的FISH信号融合检测方法诊断慢性髓细胞白血病","authors":"Ashraf AbdelRaouf","doi":"10.1109/ICCES48960.2019.9068133","DOIUrl":null,"url":null,"abstract":"Cancer is consider one of the worst disease in the modern era which cause a huge number of deaths each year world wide. It is generated due to the abnormal growth of attacking enormous number of cells to the human body cells that white blood cells can't defend for the human body. Regionally, the number of death as a consequence of the cancer is increasing and affect the growing economies badly. Medical imaging is a technique that visualize the inside of the human body using computerized device. Usually, manipulating the problems of medical imaging using image processing techniques. Leukemia is cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. Chronic Myeloid Leukemia (CML) is a type of blood cancer that causes the body to produce a large number of white blood cells. In this research, FISH (Florescent In Situ Hybridization) images is the key factor of detecting abnormalities in genes. FISH usually used for detecting abnormality in chromosomes and DNA features. CML also can be detected using FISH. CML diagnosis depends on the detection of fused Red and Green signals. Our approach first detects FISH signals, their colors, and then fusion between these colors. Moreover, number of fusions need to be counted in order to specify the proper treatment as the number of fusion is important in defining the severity of the case. We prepared our dataset for our own experiment and publish it online for research usage. Our approach experimental accuracy achieved 98% which prove the efficiency of the approach when compared to similar research.","PeriodicalId":136643,"journal":{"name":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A new FISH Signals Fusion Detection approach for diagnosing Chronic Myeloid Leukemia\",\"authors\":\"Ashraf AbdelRaouf\",\"doi\":\"10.1109/ICCES48960.2019.9068133\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cancer is consider one of the worst disease in the modern era which cause a huge number of deaths each year world wide. It is generated due to the abnormal growth of attacking enormous number of cells to the human body cells that white blood cells can't defend for the human body. Regionally, the number of death as a consequence of the cancer is increasing and affect the growing economies badly. Medical imaging is a technique that visualize the inside of the human body using computerized device. Usually, manipulating the problems of medical imaging using image processing techniques. Leukemia is cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. Chronic Myeloid Leukemia (CML) is a type of blood cancer that causes the body to produce a large number of white blood cells. In this research, FISH (Florescent In Situ Hybridization) images is the key factor of detecting abnormalities in genes. FISH usually used for detecting abnormality in chromosomes and DNA features. CML also can be detected using FISH. CML diagnosis depends on the detection of fused Red and Green signals. Our approach first detects FISH signals, their colors, and then fusion between these colors. Moreover, number of fusions need to be counted in order to specify the proper treatment as the number of fusion is important in defining the severity of the case. We prepared our dataset for our own experiment and publish it online for research usage. Our approach experimental accuracy achieved 98% which prove the efficiency of the approach when compared to similar research.\",\"PeriodicalId\":136643,\"journal\":{\"name\":\"2019 14th International Conference on Computer Engineering and Systems (ICCES)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 14th International Conference on Computer Engineering and Systems (ICCES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCES48960.2019.9068133\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 14th International Conference on Computer Engineering and Systems (ICCES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCES48960.2019.9068133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

癌症被认为是现代最严重的疾病之一,每年在世界范围内造成大量死亡。它是由于白细胞无法为人体防御的大量细胞攻击人体细胞的异常生长而产生的。就区域而言,癌症造成的死亡人数正在增加,并严重影响到不断增长的经济。医学成像是一种利用计算机设备可视化人体内部的技术。通常,利用图像处理技术来处理医学成像问题。白血病是人体造血组织的癌症,包括骨髓和淋巴系统。慢性髓性白血病(CML)是一种导致身体产生大量白细胞的血癌。在本研究中,FISH(荧光原位杂交)图像是检测基因异常的关键因素。FISH通常用于检测染色体和DNA特征的异常。CML也可以用FISH检测。CML的诊断依赖于检测融合的红绿信号。我们的方法首先检测FISH信号,它们的颜色,然后在这些颜色之间融合。此外,需要统计融合的数量,以便指定适当的治疗,因为融合的数量对于确定病例的严重程度很重要。我们为自己的实验准备了数据集,并将其发布到网上供研究使用。该方法的实验精度达到98%,与同类研究相比,证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A new FISH Signals Fusion Detection approach for diagnosing Chronic Myeloid Leukemia
Cancer is consider one of the worst disease in the modern era which cause a huge number of deaths each year world wide. It is generated due to the abnormal growth of attacking enormous number of cells to the human body cells that white blood cells can't defend for the human body. Regionally, the number of death as a consequence of the cancer is increasing and affect the growing economies badly. Medical imaging is a technique that visualize the inside of the human body using computerized device. Usually, manipulating the problems of medical imaging using image processing techniques. Leukemia is cancer of the body's blood-forming tissues, including the bone marrow and the lymphatic system. Chronic Myeloid Leukemia (CML) is a type of blood cancer that causes the body to produce a large number of white blood cells. In this research, FISH (Florescent In Situ Hybridization) images is the key factor of detecting abnormalities in genes. FISH usually used for detecting abnormality in chromosomes and DNA features. CML also can be detected using FISH. CML diagnosis depends on the detection of fused Red and Green signals. Our approach first detects FISH signals, their colors, and then fusion between these colors. Moreover, number of fusions need to be counted in order to specify the proper treatment as the number of fusion is important in defining the severity of the case. We prepared our dataset for our own experiment and publish it online for research usage. Our approach experimental accuracy achieved 98% which prove the efficiency of the approach when compared to similar research.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Social Networking Sites (SNS) and Digital Communication Across Nations Improving Golay Code Using Hashing Technique Alzheimer's Disease Integrated Ontology (ADIO) Session PC: Parallel and Cloud Computing Multipath Traffic Engineering for Software Defined Networking
×
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