Logo
  • Home
  • About Us
    • Aim and Scope
    • Research Area
    • Impact Factor
    • Indexing
  • For Authors
    • Authors Guidelines
    • How to publish paper?
    • Download Paper format
    • Submit Manuscript
    • Processing Charges
    • Download Copyrights Form
    • Submit Payment-Copyrights
  • Archives
    • Current Issues
    • Past Issues
    • Conference Issues
    • Special Issues
    • Advance Search
  • IJARIIE Board
    • Join as IJARIIE Board
    • Advisory Board
    • Editorial Board
    • Sr. Reviewer Board
    • Jr. Reviewer Board
  • Proposal
    • Conferece Proposal
    • Special Proposal
    • Faqs
  • Contact Us
  • Payment Detail

Call for Papers:Vol.11 Issue.3

Submission
Last date
28-Jun-2025
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-11,Issue-3. 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

  • How to Publish Paper
  • Submit Manuscript
  • Processing Charges
  • Submit Payment

Archives

  • Current Issue
  • Past Issue

IJARIIE Board

  • Member Of Board
  • Join As Board

Downloads

  • Authors Guidelines
  • Manuscript Template
  • Copyrights Form

Android App

Download IJARIIE APP
  • Authors
  • Abstract
  • Citations
  • Downloads
  • Similar-Paper

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
NEXT-GENERATION FIREWALLS: ADVANCING NETWORK SECURITY TO COMBAT EVOLVING AND SOPHISTICATED CYBER THREATSSecurity Network EngineerVenkata Surya Teja Gollapalli Download
Swarm Intelligence-Driven Adaptive Scheduling with Fuzzy Logic-Based Real-Time Optimization for Smart HospitalsComputer ScienceVisrutatma Rao Vallu Download
Enhancing E-Commerce Transaction Security with Big Data Analytics in Cloud ComputingCloud ComputingRajani Priya Nippatla Download
AI-Assisted Fabrication of Functionalized Nanoparticles for Infectious Disease Treatmentmachine learningNandan Kumar Download
Deep Neural Networks for Enhancing Nanoparticle Drug Release Kineticsmachine learningPavan Gowda Download
Multiscale Modelling of Nano-Drug Interactions Using Artificial Intelligencemachine learningSandhya. S Download
AI-Powered Control Systems for Nanobots in Microbial Infection Zonesmachine learningPavan T.K Download
AI-Driven Discovery of Nanostructures That Disrupt Antibiotic-Resistant Biofilmsmachine learningManohar Jain Download
AI-Enhanced Biosensors for Real-Time Detection of Pathogens Using Nanomaterialsmachine learningFaisal Ahmed Download
Integrating Deep Learning with Nanotechnology for Virus Detectionmachine learningAkash Kumar Download
Predictive Modelling of Nanoparticle Interactions with the Human Microbiomemachine learningDr. Altaf Hussain Download
AI-Driven Optimization of Nanoparticle-Based Gene Delivery SystemsArtificial Intelligence (AI)Akshay Gowda Download
Crowd Density Prediction using Deep LearningComputer Science and EngineeringAbdul Jabbar Shaikh Download
HOMIGO – A FULL-STACK APPLICATIONComputer EngineeringProf. Somashekhar B M Download
Soldier Health Monitoring & Surveillance Robot using War field using IOTComputer EngineeringProf. Seema firdose Download
12
For Authors
  • Submit Paper
  • Processing Charges
  • Submit Payment
Archive
  • Current Issue
  • Past Issue
IJARIIE Board
  • Member Of Board
  • Join As Board
Privacy and Policy
Follow us

Contact Info
  • +91-8401209201 (India)
  • +86-15636082010 (China)
  • ijariiejournal@gmail.com
  • M-20/234 Ami Appt,
    Nr.Naranpura Tele-Exch,
    Naranpura,
    Ahemdabad-380063
    Gujarat,India.
Copyright © 2025. IJARIIE. All Rights Reserved.