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

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING
PaperId: :  22780
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-22780
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Padmaraju ThamatamVasireddy Venkatadri Institute of Technology
Papana Naga Sai KrishnaVasireddy Venkatadri Institute of Technology
Kothurthi Dinesh Naga MurthyVasireddy Venkatadri Institute of Technology
Narasimha Deva Reddy PodapalaVasireddy Venkatadri Institute of Technology

Abstract

Deep Learning
Oral Cancer, Neural Network, Deep learning, Squeezenet
Oral cancer poses a significant global health challenge, with India bearing a disproportionate burden, evidenced by over 48,000 annual deaths attributed to the disease. Addressing this issue requires innovative approaches to improve early detection and classification of oral lesions, ultimately enhancing patient outcomes and reducing mortality rates. This project aims to revolutionize oral healthcare by leveraging deep learning techniques to promptly detect and classify oral lesions. Early detection of oral lesions is critical for timely intervention and improved prognosis, particularly in cases of potential malignancy. To achieve this, we utilize a comprehensive dataset comprising diverse oral images, including normal cases, lesions, and malignant conditions. Our deep learning model, based on Convolutional Neural Networks (CNN), is trained and fine-tuned using both SqueezeNet and ConvNet architectures. Through rigorous data augmentation and intensive training, the CNN model learns to accurately identify and categorize oral lesions, while also estimating the probability of tumor presence within a given dataset, thus aiding in lesion type determination. By automating the identification of potentially malignant oral lesions, our project aims to enable cost-effective and early diagnosis of oral cancer. We envision the development of a user-friendly interface that empowers clinicians to input patient data and oral images, facilitating real-time feedback and streamlining the oral lesion diagnosis process. Our approach holds promise for enhancing oral healthcare delivery, potentially saving lives through timely intervention and improved diagnostic accuracy.

Citations

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

IJARIIE Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. "EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 594-605
MLA Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. "EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 594-605.
APA Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, & Narasimha Deva Reddy Podapala. (2024). EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 594-605.
Chicago Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. "EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 594-605.
Oxford Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. 'EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 594-605. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_AND_CLASSIFICATION_OF_ORAL_LESIONS_USING_DEEP_LEARNING_ijariie22780.pdf (Accessed : ).
Harvard Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. (2024) 'EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 594-605IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_AND_CLASSIFICATION_OF_ORAL_LESIONS_USING_DEEP_LEARNING_ijariie22780.pdf (Accessed : )
IEEE Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala, "EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 594-605, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_AND_CLASSIFICATION_OF_ORAL_LESIONS_USING_DEEP_LEARNING_ijariie22780.pdf [Accessed : ].
Turabian Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. "EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver Padmaraju Thamatam, Papana Naga Sai Krishna, Kothurthi Dinesh Naga Murthy, and Narasimha Deva Reddy Podapala. EARLY DETECTION AND CLASSIFICATION OF ORAL LESIONS USING DEEP LEARNING. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 594-605. Available from: https://ijariie.com/AdminUploadPdf/EARLY_DETECTION_AND_CLASSIFICATION_OF_ORAL_LESIONS_USING_DEEP_LEARNING_ijariie22780.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
SOLAR WIRELESS ELECTRIC VEHICLE USING CHARGING SYSTEMElectronic and communication Hima J Download
Literature Review on Fibre Bragg Grating Sensors: Principles, Fabrication Techniques, Applications, and Future ProspectsElectronics and Communication Engineering Yashaswini D Download
Literature Survey on Smart Optical Fiber based Respiratory Monitoring systemElectronics and communication engineering Sai Priyanka A M Download
An loT Based Novel Approach to Health Emergency Management Through Real-Time Data Acquisition and AnalysisHealth sectorDr Siddesh G K Download
DESIGN AND DEVELOPMENT OF RIVER SURFACE CLEANING ROBOT USING IOTElectronics and communication engineeringBALAJI B R Download
A Solar Powered Wireless Power Transfer for Electric Vehicle (EV) ChargingElectronics and Communication EngineeringDr. Siddesh G K Download
AI-XRAY: AUTOMATED LUNG CANCER AND PNEUMONIA DETECTIONElectronics and communication engineeringYASHASWINI H M Download
Predictive Health Monitoring for Proactive Public Safety and ManagementElectronics and Communication EngineeringROOPA G D Download
IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATIONElectronic and communication Parvathi CM Download
IOT BASED SMART FOOTWEAR FOR WOMEN & CHILDEREN SECURITYElectronics & CommunicationNandini G R Download
Smart Pesticide Sprayer Robot Using IOT In Agriculture FieldEletronics and Communication EngineeringMadhukeshava M Download
Evaluation of LoRa Based Air Pollution Monitoring SystemElectronic and Communication EngineeringSATHISH H Download
SMART CROP MONITORING SYSTEM AND IOTElectronics and Communication EngineeringSangeetha M R Download
Design of a IoT-based Water Harvesting, Moisture Monitoring, and Crop Monitoring System for Precision AgricultureElectronics and communication engineeringDeepthi T R Download
SMART GLOVES FOR SPEECH IMPAIRED PEOPLESELECTRONICS AND COMMUNICATION ENGINEERINGSudharshan M K Download
12