{"title":"Detection of lung cancer nodules using automatic region growing method","authors":"Kenji Suzuki, H. Abe, H. MacMahon","doi":"10.1109/ICCCNT.2013.6726669","DOIUrl":null,"url":null,"abstract":"Image Segmentation is an important part of image processing. It is used in medical field to detect and to diagnose the death threatening diseases. Manual readings can be done to analyze the medical images. But still the result leads to misdiagnosis by manual segmentation and the accuracy is not so high. Many Computer Aided Detection systems arise to increase the accuracy and performance rate. In the field of medical diagnosis, imaging techniques is presently available, such as radiography, computed tomography (CT) and magnetic resonance imaging (MRI). Medical image segmentation is more crucial part in analyzing the images. Although the conventional region growing algorithm yields in better result, it lacks with the concept of manual selection of seed points. A new approach is used to segment the images to identify the focal areas in lung nodules. Threat Points Identification is used with region growing method for segmenting the suspicious region. Experiment is carried out using real time images to investigate our method.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"47 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"35","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCNT.2013.6726669","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 35
Abstract
Image Segmentation is an important part of image processing. It is used in medical field to detect and to diagnose the death threatening diseases. Manual readings can be done to analyze the medical images. But still the result leads to misdiagnosis by manual segmentation and the accuracy is not so high. Many Computer Aided Detection systems arise to increase the accuracy and performance rate. In the field of medical diagnosis, imaging techniques is presently available, such as radiography, computed tomography (CT) and magnetic resonance imaging (MRI). Medical image segmentation is more crucial part in analyzing the images. Although the conventional region growing algorithm yields in better result, it lacks with the concept of manual selection of seed points. A new approach is used to segment the images to identify the focal areas in lung nodules. Threat Points Identification is used with region growing method for segmenting the suspicious region. Experiment is carried out using real time images to investigate our method.