{"title":"利用图像处理技术从MRI图像中检测和分割乳腺肿瘤","authors":"Mahmuda Rahman, Md Gulzar Hussain, Md. Rashidul Hasan, Babe Sultana, S. Akter","doi":"10.1109/ICCMC48092.2020.ICCMC-000134","DOIUrl":null,"url":null,"abstract":"In medical image processing, segmentation plays an important role in the identification of breast tumors and has recently been performed with AI. But the same result can be achieved using different image processing tools in combined and successively. This proposed work advances an image processing based automated identification of breast tumors from MRI images. In the proposed method otsu’s thresholding segmentation is used with different image processing steps to identify the desired regions of interests’ from the MRI images. Results obtained in this research study prove that the accuracy rate has been increased compared to other existing approaches and human intervention is not necessary which means no calibration of processing parameters is essential.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detection and Segmentation of Breast Tumor from MRI Images Using Image Processing Techniques\",\"authors\":\"Mahmuda Rahman, Md Gulzar Hussain, Md. Rashidul Hasan, Babe Sultana, S. Akter\",\"doi\":\"10.1109/ICCMC48092.2020.ICCMC-000134\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In medical image processing, segmentation plays an important role in the identification of breast tumors and has recently been performed with AI. But the same result can be achieved using different image processing tools in combined and successively. This proposed work advances an image processing based automated identification of breast tumors from MRI images. In the proposed method otsu’s thresholding segmentation is used with different image processing steps to identify the desired regions of interests’ from the MRI images. Results obtained in this research study prove that the accuracy rate has been increased compared to other existing approaches and human intervention is not necessary which means no calibration of processing parameters is essential.\",\"PeriodicalId\":130581,\"journal\":{\"name\":\"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000134\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection and Segmentation of Breast Tumor from MRI Images Using Image Processing Techniques
In medical image processing, segmentation plays an important role in the identification of breast tumors and has recently been performed with AI. But the same result can be achieved using different image processing tools in combined and successively. This proposed work advances an image processing based automated identification of breast tumors from MRI images. In the proposed method otsu’s thresholding segmentation is used with different image processing steps to identify the desired regions of interests’ from the MRI images. Results obtained in this research study prove that the accuracy rate has been increased compared to other existing approaches and human intervention is not necessary which means no calibration of processing parameters is essential.