A Survey of Deep Learning for Lung Nodule Classification

Deep learning algorithms, especially convolutional networks, have quickly risen to prominence as the preferred method for analysing medical images. However, several deep learning approaches have been used in lung nodule classification in recent years, and they have shown impressive outcomes as compared to many other state-of-the-art approaches. This paper presents a systematic comparison of Multiple deep learning approaches for lung nodule classification have been used in the past, as well as variations applied to deep learning design to enhance the classification program's accuracy and also discuss the main deep learning concepts relevant to medical image analysis and also help to concludes that new problems in nodule classification must be resolved in order to identify malignant lesions at an early stage.