Call for Papers:Vol.10 Issue.6

Submission
Last date		 30-Dec-2024
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-10,Issue-6. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN
PaperId: :  16914
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 8 Issue 3 2022
DUI:    16.0415/IJARIIE-16914
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Sakshi K. JadhavSir Visvesvaraya Institute of Technology, Nashik
Khan Mohommad Faraaz FirozSir Visvesvaraya Institute of Technology, Nashik
Khan Mohd Afraaz FirozSir Visvesvaraya Institute of Technology, Nashik
Rushikesh S. OholSir Visvesvaraya Institute of Technology, Nashik
Prof. Uttam R. Patole Sir Visvesvaraya Institute of Technology, Nashik

Abstract

Computer Engineering
Pneumonia, diagnosis, cardiomegaly, tomography, CXR, CNN
Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans commonly caused by bacteria called Streptococcus pneumonia. COVID19 can cause severe pneumonia and is estimated to have a high impact on the healthcare system. Early diagnosis is crucial for the correct treatment to possibly reduce the stress in the healthcare system. Pneumonia has caused significant deaths worldwide, and it is a challenging task to detect many lung diseases such as atelectasis, cardiomegaly, lung cancer, etc., often due to limited professional radiologists in hospital settings. The standard image diagnosis tests for pneumonia are chest X-ray (CXR) and computed tomography (CT) scan. Although CT scan is the gold standard, CXR is still useful because it is cheaper, faster, and more widespread. Chest X-Rays which are used to diagnose pneumonia need expert radiotherapists for evaluation. Thus, developing an automatic system for detecting pneumonia would be beneficial and it can save lots of people's lives and help to stop and cure, control a treat the disease without any delay, particularly in remote areas. Due to the success of deep learning algorithms in analyzing medical images, Convolutional Neural Networks (CNNs) have gained much attention for disease classification. In addition, features learned by pre-trained CNN models on large-scale datasets are much useful in image classification tasks. In this work, we appraise the functionality of pre-trained CNN models utilized as feature extractors followed by different classifiers for the classification of abnormal and normal chest X-Rays. We analytically determine the optimal CNN model for the purpose. Statistical results obtained demonstrate that pre-trained CNN models employed along with supervised classifier algorithms can be very beneficial in analyzing chest X-ray images, specifically to detect Pneumonia. This study aims to identify pneumonia caused by other types and also healthy lungs using only X-Ray images. Keywords: X-Ray, CXR, COVID-19, Chest X-ray images, pneumonia detection; convolutional network (CNN), image enhancement.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN" International Journal Of Advance Research And Innovative Ideas In Education Volume 8 Issue 3 2022 Page 2024-2029
MLA Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal Of Advance Research And Innovative Ideas In Education 8.3(2022) : 2024-2029.
APA Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, & Prof. Uttam R. Patole . (2022). LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN. International Journal Of Advance Research And Innovative Ideas In Education, 8(3), 2024-2029.
Chicago Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal Of Advance Research And Innovative Ideas In Education 8, no. 3 (2022) : 2024-2029.
Oxford Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . 'LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN', International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, 2022, p. 2024-2029. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/LUNG_X_RAY_IMAGE_ENHANCEMENT_TO_IDENTIFY_PNEUMONIA_WITH_CNN_ijariie16914.pdf (Accessed : 06 October 2022).
Harvard Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . (2022) 'LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN', International Journal Of Advance Research And Innovative Ideas In Education, 8(3), pp. 2024-2029IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/LUNG_X_RAY_IMAGE_ENHANCEMENT_TO_IDENTIFY_PNEUMONIA_WITH_CNN_ijariie16914.pdf (Accessed : 06 October 2022)
IEEE Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole , "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN," International Journal Of Advance Research And Innovative Ideas In Education, vol. 8, no. 3, pp. 2024-2029, May-Jun 2022. [Online]. Available: https://ijariie.com/AdminUploadPdf/LUNG_X_RAY_IMAGE_ENHANCEMENT_TO_IDENTIFY_PNEUMONIA_WITH_CNN_ijariie16914.pdf [Accessed : 06 October 2022].
Turabian Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . "LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 8 number 3 (06 October 2022).
Vancouver Sakshi K. Jadhav, Khan Mohommad Faraaz Firoz, Khan Mohd Afraaz Firoz, Rushikesh S. Ohol, and Prof. Uttam R. Patole . LUNG X-RAY IMAGE ENHANCEMENT TO IDENTIFY PNEUMONIA WITH CNN. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2022 [Cited : 06 October 2022]; 8(3) : 2024-2029. Available from: https://ijariie.com/AdminUploadPdf/LUNG_X_RAY_IMAGE_ENHANCEMENT_TO_IDENTIFY_PNEUMONIA_WITH_CNN_ijariie16914.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 10/6/2022 7:37:21 AM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
A Review on Ad Makers- Creation & Design Advertising CampaignsComputer EngineeringSwapnil Ohol1 Download
DETECTING FACIAL FORGERIES USING NOVEL FREQUENCY CONVOLUTIONAL NEURAL NETWORKComputer ScienceChikati Madhava Rao Download
Detecting Diabetes Early and Classifying Risk with Interpretable Deep Learning ModelsComputer ScienceMohmad Ahmed Ali Download
Enhance Accuracy of Medical Disease Prediction Using Machine Learning TechniquesMachine LearningSandeep Singh Sikarwar Download
Transformer-based Generative Adversarial Network (GAN) hybrid model for sentiment analysisInformation Technologyhridesh kumar Download
A Step Ahead in Operational Resilience - Integrating Observability with DevOpsComputer EngineeringAmit Sengupta Download
The Influence of Artificial Intelligence and Human-Computer Interaction on Enhancing Children's Learning ExperiencesComputer Engineering,Supriya S Kendhuli Download
Medicinal Plants Identification Using Deep LearningComputer Engineering Rohan Kumar Verma Download
“How to balance automation and ethics when rolling out AI automation in an Educational Framework”Computer SciecneSudhakar mishra Download
Microservices Fault Tolerance PatternsComputer EngineeringAmit Sengupta Download
Forecasting and Categorization of Cardiac Arrhythmia using Soft Computational ApproachesComputer Science and EngineeringDr. Sivaprakash. C Download
Enhancing CybersecurityComputer EngineeringG Tarun Download
Microservices Design PatternsComputer EngineeringAmit Sengupta Download
The Novel Approach to Detect Kidney Stones Using Deep Learning and Convolutional Neural NetworksCSEN Manjunatha Download
An investigation into the use of deep learning and image processing in the domain of diabetic medical careCSEHR Ravikumar Download
12