P. Pardhi, Navya Verma, Nikunj Loya, Kartik Agrawal
{"title":"一种基于CNN深度学习模型的脑肿瘤检测方法","authors":"P. Pardhi, Navya Verma, Nikunj Loya, Kartik Agrawal","doi":"10.47164/ijngc.v14i1.1041","DOIUrl":null,"url":null,"abstract":"A tumor is a mass of tissue generated by the aggregation of aberrant cells that continue to grow, and the brain is the most essential organ in the human body, responsible for controlling and regulating all critical life activities for the body. A brain tumor is either formed in the brain or has migrated. Yet, no reason has been found for developing brain tumors. Though brain tumors are uncommon (approximately 1.8 percent of all reported cancers), the death risk of malignant brain tumors is particularly high due to the tumor’s location in the body’s most essential organ. To reduce the mortality rate, it is critical to accurately detect brain tumors at an early stage. As a result, we’ve proposed a computer-assisted radiology method for assessing brain tumors from MRI scans forbrain tumor diagnostic management. In this research paper, we developed a model that uses the Watershed technique to segment images, extract features, and then use deep learning to detect cancers with high accuracy. ","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"11 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Approach to Detect Brain Tumor Using CNN model of Deep Learning\",\"authors\":\"P. Pardhi, Navya Verma, Nikunj Loya, Kartik Agrawal\",\"doi\":\"10.47164/ijngc.v14i1.1041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A tumor is a mass of tissue generated by the aggregation of aberrant cells that continue to grow, and the brain is the most essential organ in the human body, responsible for controlling and regulating all critical life activities for the body. A brain tumor is either formed in the brain or has migrated. Yet, no reason has been found for developing brain tumors. Though brain tumors are uncommon (approximately 1.8 percent of all reported cancers), the death risk of malignant brain tumors is particularly high due to the tumor’s location in the body’s most essential organ. To reduce the mortality rate, it is critical to accurately detect brain tumors at an early stage. As a result, we’ve proposed a computer-assisted radiology method for assessing brain tumors from MRI scans forbrain tumor diagnostic management. In this research paper, we developed a model that uses the Watershed technique to segment images, extract features, and then use deep learning to detect cancers with high accuracy. \",\"PeriodicalId\":42021,\"journal\":{\"name\":\"International Journal of Next-Generation Computing\",\"volume\":\"11 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Next-Generation Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47164/ijngc.v14i1.1041\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Next-Generation Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47164/ijngc.v14i1.1041","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Approach to Detect Brain Tumor Using CNN model of Deep Learning
A tumor is a mass of tissue generated by the aggregation of aberrant cells that continue to grow, and the brain is the most essential organ in the human body, responsible for controlling and regulating all critical life activities for the body. A brain tumor is either formed in the brain or has migrated. Yet, no reason has been found for developing brain tumors. Though brain tumors are uncommon (approximately 1.8 percent of all reported cancers), the death risk of malignant brain tumors is particularly high due to the tumor’s location in the body’s most essential organ. To reduce the mortality rate, it is critical to accurately detect brain tumors at an early stage. As a result, we’ve proposed a computer-assisted radiology method for assessing brain tumors from MRI scans forbrain tumor diagnostic management. In this research paper, we developed a model that uses the Watershed technique to segment images, extract features, and then use deep learning to detect cancers with high accuracy.