A. Anil, Aditya Raj, H. Aravind Sarma, N. R, Deepa P L
{"title":"基于深度学习的脑MRI肿瘤检测","authors":"A. Anil, Aditya Raj, H. Aravind Sarma, N. R, Deepa P L","doi":"10.29027/ijirase.v3.i2.2019.458-465","DOIUrl":null,"url":null,"abstract":"Health experts are increasingly taking advantage of the benefits of most modern technologies, thus generating a scalable improvement in the area of health care. Because of this, there is a paradigm shift from manual monitoring towards more accurate virtual monitoring with minimum percentage of error. Advances in artificial intelligence (AI) led to exciting solutions with high accuracy for medical imaging technology and is a key method for enhancing future applications. Detection of brain tumor is a very difficult task in medical field. Detection of brain tumor manually is time consuming and requires large number of mri images for cancer diagnosis. So, there is a need for automatic brain tumor detection from Brain MR images. Deep learning methods can achieve this task. Different deep learning networks can be used for the detection of brain tumors. The proposed method comprises of a classification network which classifies the input MR images into 2 classes: on with tumor and the second without tumor. In this work, detection of brain tumor is done via classification by retraining the classifier using the technique known as transfer learning. The obtained result shows that our method outperforms the existing methods.","PeriodicalId":447225,"journal":{"name":"International Journal of Innovative Research in Applied Sciences and Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Brain Tumor detection from brain MRI using Deep Learning\",\"authors\":\"A. Anil, Aditya Raj, H. Aravind Sarma, N. R, Deepa P L\",\"doi\":\"10.29027/ijirase.v3.i2.2019.458-465\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Health experts are increasingly taking advantage of the benefits of most modern technologies, thus generating a scalable improvement in the area of health care. Because of this, there is a paradigm shift from manual monitoring towards more accurate virtual monitoring with minimum percentage of error. Advances in artificial intelligence (AI) led to exciting solutions with high accuracy for medical imaging technology and is a key method for enhancing future applications. Detection of brain tumor is a very difficult task in medical field. Detection of brain tumor manually is time consuming and requires large number of mri images for cancer diagnosis. So, there is a need for automatic brain tumor detection from Brain MR images. Deep learning methods can achieve this task. Different deep learning networks can be used for the detection of brain tumors. The proposed method comprises of a classification network which classifies the input MR images into 2 classes: on with tumor and the second without tumor. In this work, detection of brain tumor is done via classification by retraining the classifier using the technique known as transfer learning. The obtained result shows that our method outperforms the existing methods.\",\"PeriodicalId\":447225,\"journal\":{\"name\":\"International Journal of Innovative Research in Applied Sciences and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Innovative Research in Applied Sciences and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29027/ijirase.v3.i2.2019.458-465\",\"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 Innovative Research in Applied Sciences and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29027/ijirase.v3.i2.2019.458-465","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Brain Tumor detection from brain MRI using Deep Learning
Health experts are increasingly taking advantage of the benefits of most modern technologies, thus generating a scalable improvement in the area of health care. Because of this, there is a paradigm shift from manual monitoring towards more accurate virtual monitoring with minimum percentage of error. Advances in artificial intelligence (AI) led to exciting solutions with high accuracy for medical imaging technology and is a key method for enhancing future applications. Detection of brain tumor is a very difficult task in medical field. Detection of brain tumor manually is time consuming and requires large number of mri images for cancer diagnosis. So, there is a need for automatic brain tumor detection from Brain MR images. Deep learning methods can achieve this task. Different deep learning networks can be used for the detection of brain tumors. The proposed method comprises of a classification network which classifies the input MR images into 2 classes: on with tumor and the second without tumor. In this work, detection of brain tumor is done via classification by retraining the classifier using the technique known as transfer learning. The obtained result shows that our method outperforms the existing methods.