A Survey of Lung Nodules Detection and Classification from CT Scan Images
作者机构：Faculty of Computing and TechnologyIQRA UniversityIslamabad44000Pakistan Faculty of Engineering and Computer ScienceNational University of Modern LanguagesIslamabad44000Pakistan Faculty of Computing and InformaticsMultimedia UniversityCyberjaya63100Malaysia Faculty of ComputingRiphah International UniversityIslamabad44000Pakistan Department of Information SciencesDivision of Sciences and TechnologyUniversity of EducationLahore54770Pakistan
出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)
年 卷 期：2024年第48卷第6期
页 面：1483-1511页
学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学]
主 题：Lung nodules computed tomography scans lung cancer deep learning
摘 要：In the contemporary era,the death rate is increasing due to lung ***,technology is continuously enhancing the quality of *** improve the survival rate,radiologists rely on Computed Tomography(CT)scans for early detection and diagnosis of lung *** paper presented a detailed,systematic review of several identification and categorization techniques for lung *** analysis of the report explored the challenges,advancements,and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning(DL)*** findings also highlighted the usefulness of DL networks,especially convolutional neural networks(CNNs)in elevating sensitivity,accuracy,and specificity as well as overcoming false positives in the initial stages of lung cancer *** paper further presented the integral nodule classification stage,which stressed the importance of differentiating between benign and malignant nodules for initial cancer ***,the findings presented a comprehensive analysis of multiple techniques and studies for nodule classification,highlighting the evolution of methodologies from conventional machine learning(ML)classifiers to transfer learning and integrated ***,while accepting the strides formed by CAD systems,the review addressed persistent challenges.
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