{"title":"深度卷积神经网络在肺癌及肺结节病理图像诊断中的研究进展","authors":"P. Shimna, A. Shirly Edward, T. Roshini","doi":"10.1109/ICAIA57370.2023.10169738","DOIUrl":null,"url":null,"abstract":"Lung cancer is a serious health issue that requires early detection. Machine Learning has figured prominently in the health sector in general, and in analyzing histopathological images and detecting illnesses in particular, because it may eliminate many mistakes that may arise when radiologists analyse image data. Traditional healthcare imaging techniques such as x-rays, CT scans, MRIs, and so on have little promise for detecting lung tumours. Convolutional Neural Networks have piqued the interest of doctors and academics due to their ability to analyse images accurately. The current study examines the role of CNN in lung cancer detection. Findings presented in the literature provide prospective researchers with a deeper understanding of the issue. We examined most of the features and includes extensive recommendations for future study. The primary purpose of this study is to detect malignant lung nodules in a lung image and to categorize pulmonary cancer. This work concentrates on novel Deep Learning techniques used in literature to locate cancerous lung nodules.","PeriodicalId":196526,"journal":{"name":"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review on Diagnosis of Lung Cancer and Lung Nodules in Histopathological Images using Deep Convolutional Neural Network\",\"authors\":\"P. Shimna, A. Shirly Edward, T. Roshini\",\"doi\":\"10.1109/ICAIA57370.2023.10169738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lung cancer is a serious health issue that requires early detection. Machine Learning has figured prominently in the health sector in general, and in analyzing histopathological images and detecting illnesses in particular, because it may eliminate many mistakes that may arise when radiologists analyse image data. Traditional healthcare imaging techniques such as x-rays, CT scans, MRIs, and so on have little promise for detecting lung tumours. Convolutional Neural Networks have piqued the interest of doctors and academics due to their ability to analyse images accurately. The current study examines the role of CNN in lung cancer detection. Findings presented in the literature provide prospective researchers with a deeper understanding of the issue. We examined most of the features and includes extensive recommendations for future study. The primary purpose of this study is to detect malignant lung nodules in a lung image and to categorize pulmonary cancer. This work concentrates on novel Deep Learning techniques used in literature to locate cancerous lung nodules.\",\"PeriodicalId\":196526,\"journal\":{\"name\":\"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAIA57370.2023.10169738\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAIA57370.2023.10169738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Review on Diagnosis of Lung Cancer and Lung Nodules in Histopathological Images using Deep Convolutional Neural Network
Lung cancer is a serious health issue that requires early detection. Machine Learning has figured prominently in the health sector in general, and in analyzing histopathological images and detecting illnesses in particular, because it may eliminate many mistakes that may arise when radiologists analyse image data. Traditional healthcare imaging techniques such as x-rays, CT scans, MRIs, and so on have little promise for detecting lung tumours. Convolutional Neural Networks have piqued the interest of doctors and academics due to their ability to analyse images accurately. The current study examines the role of CNN in lung cancer detection. Findings presented in the literature provide prospective researchers with a deeper understanding of the issue. We examined most of the features and includes extensive recommendations for future study. The primary purpose of this study is to detect malignant lung nodules in a lung image and to categorize pulmonary cancer. This work concentrates on novel Deep Learning techniques used in literature to locate cancerous lung nodules.