{"title":"神经网络和卷积算法在电子医学中的应用","authors":"T. Rymarczyk, Barbara Stefaniak, P. Adamkiewicz","doi":"10.5604/01.3001.0012.5282","DOIUrl":null,"url":null,"abstract":"The solution shows the architecture of the system collecting and analyzing data. There was tried to develop algorithms to image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. With the use of algorithms such as the level set method, neural networks and deep learning methods, it can obtain a quicker diagnosis and automatically marking areas of the interest region in medical images.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"NEURAL NETWORK AND CONVOLUTIONAL ALGORITH TO EXTRACT SHAPES BY E-MEDICUS APPLICATION\",\"authors\":\"T. Rymarczyk, Barbara Stefaniak, P. Adamkiewicz\",\"doi\":\"10.5604/01.3001.0012.5282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The solution shows the architecture of the system collecting and analyzing data. There was tried to develop algorithms to image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. With the use of algorithms such as the level set method, neural networks and deep learning methods, it can obtain a quicker diagnosis and automatically marking areas of the interest region in medical images.\",\"PeriodicalId\":53131,\"journal\":{\"name\":\"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5604/01.3001.0012.5282\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5604/01.3001.0012.5282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
NEURAL NETWORK AND CONVOLUTIONAL ALGORITH TO EXTRACT SHAPES BY E-MEDICUS APPLICATION
The solution shows the architecture of the system collecting and analyzing data. There was tried to develop algorithms to image segmentation. These algorithms are needed to identify arbitrary number of phases for the segmentation problem. With the use of algorithms such as the level set method, neural networks and deep learning methods, it can obtain a quicker diagnosis and automatically marking areas of the interest region in medical images.