Title
Deep-Learning Framework to Detect Lung Abnormality – A study with Chest X-Ray and Lung CT Scan Images
Abstract
•This work proposes a Modified AlexNet (MAN) deep-learning framework to evaluate the lung abnormality.•This work introduces a threshold filter to remove the artifacts from the Lung CT images.•This work introduces an Ensemble-Feature-Technique (EFT) by integrating the deep-features and the handcrafted features.•Serial fusion and PCA based selection is implemented in EFT to chose principal feature set.•Experimental results demonstrate superior performance of MAN in comparison with other existing state of the art methods.
Year
DOI
Venue
2020
10.1016/j.patrec.2019.11.013
Pattern Recognition Letters
Field
DocType
Volume
Lung cancer,Feature vector,Pattern recognition,Softmax function,Support vector machine,Abnormality,Artificial intelligence,Deep learning,Mathematics,Principal component analysis,Cancer
Journal
129
ISSN
Citations 
PageRank 
0167-8655
11
0.67
References 
Authors
0
10