{"title":"基于深度学习网络的肺癌检测:比较分析","authors":"Susmita Das, Swanirbhar Majumder","doi":"10.1109/ICRCICN50933.2020.9296197","DOIUrl":null,"url":null,"abstract":"Deep learning is an emergent and influential method which is used for feature learning and pattern recognition. We provide a comparison between Computer Aided Diagnosis scheme using Deep Learning Technique and traditional Computer Aided Diagnosis scheme in our paper. In this paper, we have compared several deep neural networks for recognition of pulmonary cancer. In our study, we find that Convolutional neural networks are used for pulmonary cancer detection in most of the cases, as compared to other algorithms in deep learning techniques. In conclusion, we address the few difficulties in the implementation of the systems for pulmonary cancer, then we summarise the advantages and disadvantages of the existing algorithms for diagnosis of pulmonary cancer.","PeriodicalId":138966,"journal":{"name":"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Lung Cancer Detection Using Deep Learning Network: A Comparative Analysis\",\"authors\":\"Susmita Das, Swanirbhar Majumder\",\"doi\":\"10.1109/ICRCICN50933.2020.9296197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Deep learning is an emergent and influential method which is used for feature learning and pattern recognition. We provide a comparison between Computer Aided Diagnosis scheme using Deep Learning Technique and traditional Computer Aided Diagnosis scheme in our paper. In this paper, we have compared several deep neural networks for recognition of pulmonary cancer. In our study, we find that Convolutional neural networks are used for pulmonary cancer detection in most of the cases, as compared to other algorithms in deep learning techniques. In conclusion, we address the few difficulties in the implementation of the systems for pulmonary cancer, then we summarise the advantages and disadvantages of the existing algorithms for diagnosis of pulmonary cancer.\",\"PeriodicalId\":138966,\"journal\":{\"name\":\"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRCICN50933.2020.9296197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN50933.2020.9296197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lung Cancer Detection Using Deep Learning Network: A Comparative Analysis
Deep learning is an emergent and influential method which is used for feature learning and pattern recognition. We provide a comparison between Computer Aided Diagnosis scheme using Deep Learning Technique and traditional Computer Aided Diagnosis scheme in our paper. In this paper, we have compared several deep neural networks for recognition of pulmonary cancer. In our study, we find that Convolutional neural networks are used for pulmonary cancer detection in most of the cases, as compared to other algorithms in deep learning techniques. In conclusion, we address the few difficulties in the implementation of the systems for pulmonary cancer, then we summarise the advantages and disadvantages of the existing algorithms for diagnosis of pulmonary cancer.