A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network
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...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/12/3482 |
| _version_ | 1797564647156482048 |
|---|---|
| author | Abdullah-Al Nahid Niloy Sikder Anupam Kumar Bairagi Md. Abdur Razzaque Mehedi Masud Abbas Z. Kouzani M. A. Parvez Mahmud |
| author_facet | Abdullah-Al Nahid Niloy Sikder Anupam Kumar Bairagi Md. Abdur Razzaque Mehedi Masud Abbas Z. Kouzani M. A. Parvez Mahmud |
| author_sort | Abdullah-Al Nahid |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T19:01:03Z |
| format | Article |
| id | doaj.art-40451390598e4b199ba1e9ca6127d3ac |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T19:01:03Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-40451390598e4b199ba1e9ca6127d3ac2023-11-20T04:26:08ZengMDPI AGSensors1424-82202020-06-012012348210.3390/s20123482A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural NetworkAbdullah-Al Nahid0Niloy Sikder1Anupam Kumar Bairagi2Md. Abdur Razzaque3Mehedi Masud4Abbas Z. Kouzani5M. A. Parvez Mahmud6Electronics and Communication Engineering Discipline, Khulna University, Khulna 9208, BangladeshComputer Science and Engineering Discipline, Khulna University, Khulna 9208, BangladeshComputer Science and Engineering Discipline, Khulna University, Khulna 9208, BangladeshDepartment of Computer Science and Engineering, University of Dhaka, Dhaka 1000, BangladeshDepartment of Computer Science, Taif University, Taif 21944, Saudi ArabiaSchool of Engineering, Deakin University, Geelong, VIC 3216, AustraliaSchool of Engineering, Deakin University, Geelong, VIC 3216, AustraliaPneumonia 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.https://www.mdpi.com/1424-8220/20/12/3482pneumoniachest radiographmedical image processingdeep learning |
| spellingShingle | Abdullah-Al Nahid Niloy Sikder Anupam Kumar Bairagi Md. Abdur Razzaque Mehedi Masud Abbas Z. Kouzani M. A. Parvez Mahmud A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network Sensors pneumonia chest radiograph medical image processing deep learning |
| title | A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network |
| title_full | A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network |
| title_fullStr | A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network |
| title_full_unstemmed | A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network |
| title_short | A Novel Method to Identify Pneumonia through Analyzing Chest Radiographs Employing a Multichannel Convolutional Neural Network |
| title_sort | novel method to identify pneumonia through analyzing chest radiographs employing a multichannel convolutional neural network |
| topic | pneumonia chest radiograph medical image processing deep learning |
| url | https://www.mdpi.com/1424-8220/20/12/3482 |
| work_keys_str_mv | AT abdullahalnahid anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT niloysikder anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT anupamkumarbairagi anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT mdabdurrazzaque anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT mehedimasud anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT abbaszkouzani anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT maparvezmahmud anovelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT abdullahalnahid novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT niloysikder novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT anupamkumarbairagi novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT mdabdurrazzaque novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT mehedimasud novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT abbaszkouzani novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork AT maparvezmahmud novelmethodtoidentifypneumoniathroughanalyzingchestradiographsemployingamultichannelconvolutionalneuralnetwork |