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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.

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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
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