Automated Methods for Detection and Classification Pneumonia Based on X-Ray Images Using Deep Learning

نویسندگان

چکیده

Recently, researchers, specialists, and companies around the world are rolling out deep learning image processing-based systems that can fastly process hundreds of X-Ray Computed Tomography (CT) images to accelerate diagnosis pneumonia such as SARS, covid-19, etc., aid in its containment. Medical analysis is one most promising research areas; it provides facilities for making decisions several diseases MERS, etc. In this paper, we present a comparison recent convolutional neural network (CNN) architectures automatic binary classification based on fined tuned versions (VGG16, VGG19, DenseNet201, Inception_ResNet_V2, Inception_V3, Resnet50, MobileNet_V2 Xception) retraining baseline CNN. The proposed work has been tested using chest & CT dataset, which contains 6087 (4504 1583 normal). As result, conclude fine-tuned version Resnet50 shows highly satisfactory performance with rate increase training testing accuracy (more than 96% accuracy).

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ژورنال

عنوان ژورنال: Studies in big data

سال: 2021

ISSN: ['2197-6503', '2197-6511']

DOI: https://doi.org/10.1007/978-3-030-74575-2_14