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: :  DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION
PaperId: :  22759
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-22759
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
K. Sandhya RaniVasireddy Venkatadri Institute of Technology
Sk. Chisti KarimullahVasireddy Venkatadri Institute of Technology
T. Pavan Kumar ReddyVasireddy Venkatadri Institute of Technology
K. Venkat SubbaraoVasireddy Venkatadri Institute of Technology
Sk. YasinVasireddy Venkatadri Institute of Technology

Abstract

Deep Learning
Lung Cancer, Pulmonary nodules, Computer-Aided Diagnosis(CAD) system, Computed Tomography(CT), Convolutional Neural Networks(CNNs), Watershed algorithm, Deep Learning.
Early detection of lung cancer is crucial for improving patient survival rates, with pulmonary nodules serving as vital indicators. Traditionally, radiologists manually analyze CT scans to identify these nodules, a process requiring significant expertise and time. To address this, a Computer-Aided Diagnosis (CAD) system utilizing Computed Tomography (CT) and Convolutional Neural Networks (CNNs) with image segmentation via the watershed algorithm is proposed. CNNs, being deep structured algorithms, excel at visualizing and extracting hidden texture features from image datasets. By automating the nodule detection process, this approach aims to streamline and expedite the diagnosis of lung cancer, facilitating early intervention and improving patient outcomes. The integration of CNNs with image segmentation techniques like the watershed algorithm enhances the system's accuracy and efficiency. This method holds promise for enabling early detection of lung cancer, potentially saving lives by facilitating timely intervention and treatment. Its implementation would significantly alleviate the burden on radiologists while enhancing the overall effectiveness of lung cancer screening programs. Through leveraging advancements in deep learning and medical imaging technology, this CAD system offers a promising avenue for improving the prognosis and management of lung cancer, ultimately contributing to better healthcare outcomes and patient well-being.

Citations

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

IJARIIE K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. "DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 424-430
MLA K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. "DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 424-430.
APA K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, & Sk. Yasin. (2024). DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 424-430.
Chicago K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. "DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 424-430.
Oxford K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. 'DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 424-430. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/DEEP_LEARNING_EMPOWERED_PULMONARY_NODULE_EXAMINATION_ijariie22759.pdf (Accessed : ).
Harvard K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. (2024) 'DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 424-430IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/DEEP_LEARNING_EMPOWERED_PULMONARY_NODULE_EXAMINATION_ijariie22759.pdf (Accessed : )
IEEE K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin, "DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 424-430, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/DEEP_LEARNING_EMPOWERED_PULMONARY_NODULE_EXAMINATION_ijariie22759.pdf [Accessed : ].
Turabian K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. "DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 ().
Vancouver K. Sandhya Rani, Sk. Chisti Karimullah, T. Pavan Kumar Reddy, K. Venkat Subbarao, and Sk. Yasin. DEEP LEARNING EMPOWERED PULMONARY NODULE EXAMINATION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(2) : 424-430. Available from: https://ijariie.com/AdminUploadPdf/DEEP_LEARNING_EMPOWERED_PULMONARY_NODULE_EXAMINATION_ijariie22759.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads



Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
Satellite Communication: Recent Developments and Future DirectionEngineeringShraddhitha P Shettigar Download
Design and Development Of Agribot using Machine LearningElectronics and telecommunication EngineeringSwati Bodake Download
Performance analysis of compact E-Shaped Microstrip Patch Antenna for Wireless Body Area NetworkElectronics & Communication EngineeringMohammad Shareefuddin Tabrez Download
FISH-shaped WLAN MIMO antennaElectronics and Communication EngineeringSivasankari N Download
Design and Analysis of Coupler for Micro Strip patch Antenna ApplicationsElectronics and Communication EngineeringSivasankari N Download
ROAD SAFETY ALERT SYSTEM: ENSURING VEHICLE SAFETY THROUGH DIGITAL NOTIFICATIONS DURING MANHOLE AND ROAD CONSTRUCTION DIVERSIONELECTRONICS AND COMMUNICATION ENGINEERINGGANGULA SRINIVASULU Download
Vehicle to Vehicle Communication Using Cognitive Radio TechnologyComputer EngineeringHARI PRASATH M Download
Open source ventilator systemElectronics and Telecommunication, Engineering.Gauri Rajesh Awaghade Download
Design and Implementation of a low power high speed full adder cell for low power applicationsElectronics and Communication EngineeringRiya Srivastava Download
Smart Multi-purpose TrolleyE&TC EngineeringSatish Chavan Download
SMART ENERGY METER AND MONITORING SYSTEM USING GSMElectronics and Telecommunication Aditya Khadage Download
Advanced Low-Power High-Speed SAFF Implementation with MTCMOS in 45nmElectronics and Communication EngineeringAdarsh Bhardwaj Download
ARDUINO BASED PLANT WATERING SYSTEMElectronics and Communication EngineeringAbhilipsa Biswal Download
Arduino-Powered Smart Irrigation SystemElectronics and Communication Engineering Ashutosh Pati Download
SMART ATTENDANCE MONITORING SYSTEM USING RFID AND IR SENSORSElectronics and Communication EngineeringPradyumna Kumar Sahoo Download
12