Feature Representation Using Deep Autoencoder for Lung Nodule Image Classification

Abstract

This paper focuses on the problem of lung nodule image classification, which plays a key role in lung cancer early diagnosis. In this work, we propose a novel model for lung nodule image feature representation that incorporates both local and global characters. First, lung nodule images are divided into local patches with Superpixel. Then these patches are transformed into fixed-length local feature vectors using unsupervised deep autoencoder (DAE). The visual vocabulary is constructed based on the local features and bag of visual words (BOVW) is used to describe the global feature representation of lung nodule image. Finally, softmax algorithm is employed for lung nodule type classification, which can assemble the whole training process as an end-to-end mode. Comprehensive evaluations are conducted on the widely used public available ELCAP lung image database. Experimental results with regard to different parameter setting, data augmentation, model sparsity, classifier algorithms, and model ensemble validate the effectiveness of our proposed approach.

An Appraisal of Lung Nodules Automatic Classification Algorithms for CT Images

“…User-defined features, such as texture, shape, intensity, and fractal, are mostly designed by experienced scientists and engineers through quantitative analysis. They are covered in References [18,29,30,31,32,33,34,35,36,37,38,39,40,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,75,78,79,80,81,82,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,…”

“…The parameters in the deep model can be automatically adjusted. Deep learning models, such as CNNs, Auto-encoder, DBNs et al were used in lung nodule image classification [18,42,43,44,45,60,77,83,92,95,96,103,105,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129].…”

“…Mao and Tang [95] used local and global features for nodule representation. Deep anto-encoder was employed for transforming local patches obtained by the super-pixel into local features.…”

“…Selected papers based on deep feature are given in References [18,42,43,44,45,60,77,83,92,95,96,103,105,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129]. Selected papers that based on 3D features are given in References [18,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,78,79,80,81,82,83,88,89,90,96,97,98,105,110,123,124,125,…”

Comprehensive Classification Model for Diagnosing Multiple Disease Condition from Chest X-Ray

“…Literature also claimed of using an encoding technique of local binary pattern for classification. [36] The work of Mao et al [37] has used deep learning approach to perform classification of the lung nodule. The outcome shows better performance in contrast to other conventional classifiers.…”