{"title":"肺CT图像自动分割中统计方法与深度学习方法的比较研究","authors":"Dr. Akey Sungheetha, Dr. Rajesh Sharma R","doi":"10.36548/jiip.2020.4.003","DOIUrl":null,"url":null,"abstract":"Recently, deep learning technique is playing important starring role for image segmentation field in medical imaging of accurate tasks. In a critical component of diagnosis, deep learning is an organized network with homogeneous areas to provide accurate results. It is proved its superior quality with statistical model automatic segmentation methods in many critical condition environments. In this research article, we focus the improved accuracy and speed of the system process compared with conservative automatic segmentation methods. Also we compared performance metrics such as accuracy, sensitivity, specificity, precision, RMSE, Precision- Recall Curve with different algorithm in deep learning method. This comparative study covers the constructing an efficient and accurate model for Lung CT image segmentation.","PeriodicalId":20643,"journal":{"name":"Proposed for presentation at the 2020 Virtual MRS Fall Meeting & Exhibit held November 27 - December 4, 2020.","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Comparative Study: Statistical Approach and Deep Learning Method for Automatic Segmentation Methods for Lung CT Image Segmentation\",\"authors\":\"Dr. Akey Sungheetha, Dr. Rajesh Sharma R\",\"doi\":\"10.36548/jiip.2020.4.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, deep learning technique is playing important starring role for image segmentation field in medical imaging of accurate tasks. In a critical component of diagnosis, deep learning is an organized network with homogeneous areas to provide accurate results. It is proved its superior quality with statistical model automatic segmentation methods in many critical condition environments. In this research article, we focus the improved accuracy and speed of the system process compared with conservative automatic segmentation methods. Also we compared performance metrics such as accuracy, sensitivity, specificity, precision, RMSE, Precision- Recall Curve with different algorithm in deep learning method. This comparative study covers the constructing an efficient and accurate model for Lung CT image segmentation.\",\"PeriodicalId\":20643,\"journal\":{\"name\":\"Proposed for presentation at the 2020 Virtual MRS Fall Meeting & Exhibit held November 27 - December 4, 2020.\",\"volume\":\"8 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proposed for presentation at the 2020 Virtual MRS Fall Meeting & Exhibit held November 27 - December 4, 2020.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36548/jiip.2020.4.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proposed for presentation at the 2020 Virtual MRS Fall Meeting & Exhibit held November 27 - December 4, 2020.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36548/jiip.2020.4.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative Study: Statistical Approach and Deep Learning Method for Automatic Segmentation Methods for Lung CT Image Segmentation
Recently, deep learning technique is playing important starring role for image segmentation field in medical imaging of accurate tasks. In a critical component of diagnosis, deep learning is an organized network with homogeneous areas to provide accurate results. It is proved its superior quality with statistical model automatic segmentation methods in many critical condition environments. In this research article, we focus the improved accuracy and speed of the system process compared with conservative automatic segmentation methods. Also we compared performance metrics such as accuracy, sensitivity, specificity, precision, RMSE, Precision- Recall Curve with different algorithm in deep learning method. This comparative study covers the constructing an efficient and accurate model for Lung CT image segmentation.