Deep-Pneumonia Framework Using Deep Learning Models Based on Chest X-Ray Images

Abstract

Pneumonia is a contagious disease that causes ulcers of the lungs, and is one of the main reasons for death among children and the elderly in the world. Several deep learning models for detecting pneumonia from chest X-ray images have been proposed. One of the extreme challenges has been to find an appropriate and efficient model that meets all performance metrics. Proposing efficient and powerful deep learning models for detecting and classifying pneumonia is the main purpose of this work. In this paper, four different models are developed by changing the used deep learning method; two pre-trained models, ResNet152V2 and MobileNetV2, a Convolutional Neural Network (CNN), and a Long Short-Term Memory (LSTM). The proposed models are implemented and evaluated using Python and compared with recent similar research. The results demonstrate that our proposed deep learning framework improves accuracy, precision, F1-score, recall, and Area Under the Curve (AUC) by 99.22%, 99.43%, 99.44%, 99.44%, and 99.77%, respectively. As clearly illustrated from the results, the ResNet152V2 model outperforms other recently proposed works. Moreover, the other proposed models—MobileNetV2, CNN, and LSTM-CNN—achieved results with more than 91% in accuracy, recall, F1-score, precision, and AUC, and exceed the recently introduced models in the literature.

Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases

“…In other research papers, deep learning models only for COVID-19 as in [ 13 , 15 , 17 , 32 ], pneumonia only as in [ 12 ] or for both diseases as in [ 26 , 33 , 27 , 34 ] have been proposed. But in this paper, a multi-classification deep learning model for diagnosing COVID-19, pneumonia, and Lung Cancer from chest X-ray and CT images is developed.…”

“…Deep learning efficiently generates models that produce more accurate results in predicting and classifying different diseases using images as in breast cancer [ 6 ], liver diseases [ 7 ], colon cancer [ 8 ], brain tumor [ 9 ], skin cancer [ 10 ], lung cancer [ 11 ], pneumonia [ 12 ], and recently COVID-19 diagnosis, without requiring any human intervention. The main reason for using deep learning is that deep learning techniques learn by creating a more abstract representation of data as the network grows deeper (not like classical machine learning).…”

Pneumonia Detection from Chest X-ray Images Based on Convolutional Neural Network

“…Ayan et al [17] adopted transfer learning and fine-tuning to train two classical CNN models, Xception-Net and VGG16-Net, to classify images containing pneumonia. The authors [18] proposed four efficient CNN models, which were two pre-trained models, Res-Net152V2 and MobileNetV2, a CNN architecture, and a Long Short-Term Memory (LSTM) network. In addition, they compared different parameters trained by each model.…”

Pneumonia Disease Detection Using Deep Learning Methods from Chest X-Ray Images: Review

“…The proposed methodology may aid medical practitioners in quickly diagnosing pneumonia using X-ray images. Elshennawy et al [9] designed a reliable and efficient methodology for the detection and classification of pneumonia. The pre-trained (DL) deep learning approach utilized, four distinct versions were formulated for better results.…”