A Comprehensive Study of Deep Learning Approaches for Lung Nodule Analysis with Recent Computational Techniques

Autor: Sudha R., Umamaheswari K.M.
Rok vydání: 2022
Předmět:
Zdroj: Webology. 19:749-763
ISSN: 1735-188X
DOI: 10.14704/web/v19i1/web19053
Popis: Lung nodules resemble a spot or coin lesion, which is an abnormal part of the Lung. The size of the nodule is more significant than 3 cm, which may lead to cancer later. Lung cancer is one of the life treating cancers in the world. The American Lung Association says that the five years of survival rate is 18.6% lower when compared to other dominant cancers. But when it is diagnosed earlier, the survival rate can be increased by about 60%. Deep Learning-based Computer-aided Detection (CADe) and Computer-aided Diagnose (CADx) systems help the radiologist detect and classify the nodules as early as possible. This survey focuses on various methods, techniques, and algorithms available for Detecting, Classifying and Reducing the FP on Lung nodules. And also the familiar datasets that are used for processing the images. This work also reviews how the CNN model can be deployed and stored as cloud services.
Databáze: OpenAIRE