{"title":"Detection of Brain Tumor Using Image Processing Techniques","authors":"Venkata Ratna Prabha K, Ravikiran Gujjarlapudi, Sravya Ravi, Yasaswini Satuluri, Chandini Nekkanti, Ramesh P","doi":"10.1109/AICAPS57044.2023.10074053","DOIUrl":null,"url":null,"abstract":"Brain tumor is a deadly disease since it spreads to various parts and affects their functioning. Cells grow abnormally and form as tumors. Various techniques have been implemented for the identification but image processing is quite complicated. The dataset used is brain tumor dataset which consists of MRI scans of the brain. The groundwork presents a technique in detecting this ailment of brain tumor from the provided MRI images with approving accuracy. The dataset named brain tumor dataset is utilized for proposed work. Our methodology consists of various steps such as pre-processing to enhance the image by reducing noise through filters. This is followed by threshold segmentation strategy. Later, the morphological operations are involved in the further stage. In the end, the tumor region is inferred employing image subtraction method.","PeriodicalId":146698,"journal":{"name":"2023 International Conference on Advances in Intelligent Computing and Applications (AICAPS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Advances in Intelligent Computing and Applications (AICAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICAPS57044.2023.10074053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Brain tumor is a deadly disease since it spreads to various parts and affects their functioning. Cells grow abnormally and form as tumors. Various techniques have been implemented for the identification but image processing is quite complicated. The dataset used is brain tumor dataset which consists of MRI scans of the brain. The groundwork presents a technique in detecting this ailment of brain tumor from the provided MRI images with approving accuracy. The dataset named brain tumor dataset is utilized for proposed work. Our methodology consists of various steps such as pre-processing to enhance the image by reducing noise through filters. This is followed by threshold segmentation strategy. Later, the morphological operations are involved in the further stage. In the end, the tumor region is inferred employing image subtraction method.