P. Gayathri, R. Dheepika, S. Jenitha, R. Punithalakshmi
{"title":"Automatic Brain Tissue Segmentation in Fetal MRI with Audio Generation using GUI","authors":"P. Gayathri, R. Dheepika, S. Jenitha, R. Punithalakshmi","doi":"10.1109/ICSCAN49426.2020.9262345","DOIUrl":null,"url":null,"abstract":"There is always an ultimate need to detect the cancer in various parts of the body. The project is to develop such system using the real-time database from kaggle website. It is useful to identify the cancer and it gives accurate result. Segmentation done by manual and classification of CT image consumes more power. For a large number of dataset, it is impossible to do this kind of segmentation. The extraction of region of interest area from the original image and segmentation is done. From CT image, brain tumor is partitioned by accurate segmentation algorithm. By using Gabor with PCA technique, the textures are attained. The features which extracted and its area of interest region decides that whether the disease is Malignant or starting stage or not.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"10 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN49426.2020.9262345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
There is always an ultimate need to detect the cancer in various parts of the body. The project is to develop such system using the real-time database from kaggle website. It is useful to identify the cancer and it gives accurate result. Segmentation done by manual and classification of CT image consumes more power. For a large number of dataset, it is impossible to do this kind of segmentation. The extraction of region of interest area from the original image and segmentation is done. From CT image, brain tumor is partitioned by accurate segmentation algorithm. By using Gabor with PCA technique, the textures are attained. The features which extracted and its area of interest region decides that whether the disease is Malignant or starting stage or not.