Next Article in Journal
Technique and Circuit for Contactless Readout of Piezoelectric MEMS Resonator Sensors
Next Article in Special Issue
Breast Cancer Histopathology Image Classification Using an Ensemble of Deep Learning Models
Previous Article in Journal
Mobile Computing Technologies for Health and Mobility Assessment: Research Design and Results of the Timed Up and Go Test in Older Adults
Previous Article in Special Issue
Comparison of Deep-Learning and Conventional Machine-Learning Methods for the Automatic Recognition of the Hepatocellular Carcinoma Areas from Ultrasound Images
Open AccessArticle

A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network

1
Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, Bangladesh
2
Computer Science and Engineering Discipline, Khulna University, Khulna 9208, Bangladesh
3
Department of Computer Science and Engineering, University of Dhaka, Dhaka 1000, Bangladesh
4
Department of Computer Science, Taif University, Taif 21944, Saudi Arabia
5
School of Engineering, Deakin University, Geelong, VIC 3216, Australia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2020, 20(12), 3482; https://doi.org/10.3390/s20123482
Received: 27 April 2020 / Revised: 7 June 2020 / Accepted: 10 June 2020 / Published: 19 June 2020
(This article belongs to the Special Issue Machine Learning for Biomedical Imaging and Sensing)
Pneumonia is a virulent disease that causes the death of millions of people around the world. Every year it kills more children than malaria, AIDS, and measles combined and it accounts for approximately one in five child-deaths worldwide. The invention of antibiotics and vaccines in the past century has notably increased the survival rate of Pneumonia patients. Currently, the primary challenge is to detect the disease at an early stage and determine its type to initiate the appropriate treatment. Usually, a trained physician or a radiologist undertakes the task of diagnosing Pneumonia by examining the patient’s chest X-ray. However, the number of such trained individuals is nominal when compared to the 450 million people who get affected by Pneumonia every year. Fortunately, this challenge can be met by introducing modern computers and improved Machine Learning techniques in Pneumonia diagnosis. Researchers have been trying to develop a method to automatically detect Pneumonia using machines by analyzing and the symptoms of the disease and chest radiographic images of the patients for the past two decades. However, with the development of cogent Deep Learning algorithms, the formation of such an automatic system is very much within the realms of possibility. In this paper, a novel diagnostic method has been proposed while using Image Processing and Deep Learning techniques that are based on chest X-ray images to detect Pneumonia. The method has been tested on a widely used chest radiography dataset, and the obtained results indicate that the model is very much potent to be employed in an automatic Pneumonia diagnosis scheme. View Full-Text
Keywords: pneumonia; chest radiograph; medical image processing; deep learning pneumonia; chest radiograph; medical image processing; deep learning
Show Figures

Figure 1

MDPI and ACS Style

Nahid, A.-A.; Sikder, N.; Bairagi, A.K.; Razzaque, M.A.; Masud, M.; Z. Kouzani, A.; Mahmud, M.A.P. A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network. Sensors 2020, 20, 3482. https://doi.org/10.3390/s20123482

AMA Style

Nahid A-A, Sikder N, Bairagi AK, Razzaque MA, Masud M, Z. Kouzani A, Mahmud MAP. A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network. Sensors. 2020; 20(12):3482. https://doi.org/10.3390/s20123482

Chicago/Turabian Style

Nahid, Abdullah-Al; Sikder, Niloy; Bairagi, Anupam K.; Razzaque, Md. A.; Masud, Mehedi; Z. Kouzani, Abbas; Mahmud, M. A.P. 2020. "A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network" Sensors 20, no. 12: 3482. https://doi.org/10.3390/s20123482

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop