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Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
IEEE Transactions on Medical Imaging
Purpose: Deep learning techniques have recently achieved impressive results in a variety of computer vision problems, raising expectations that they might be applied in other domains, such as medical image analysis. We propose and evaluate a convolutional neural network (CNN), designed for the classification of interstitial lung disease (ILD) patterns. Materials and methods: The proposed network consists of 5 convolutional layers with 2×2 kernels and LeakyReLU activations, followed by averagedoi:10.1109/tmi.2016.2535865 pmid:26955021 fatcat:jswmtyvfdvhr3kysjwdy3oecnm