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Title: :  IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION
PaperId: :  26711
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 3 2025
DUI:    16.0415/IJARIIE-26711
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Parvathi CMSJM institute of technology
Mathura yadav PV SJM institute of technology
Shailendra SSJM institute of technology
Chethan kumar PSJM institute of technology
Tanuja TSJM institute of technology

Abstract

Electronic and communication
. Artificial Intelligence (AI) 2. Object Recognition 3. Machine Learning (ML) 4. Deep Learning (DL) 5. Convolutional Neural Networks (CNN) 6. Brain Tumor Detection 7. Medical Imaging 8. MRI Scans 9. Image Segmentation 10. Early Diagnosis
The abstract titled "Improving Brain Cancer Detection through AI-Driven Object Recognition" explores Utilizing artificial intelligence (AI) in enhancing The accuracy and efficiency of brain cancer diagnosis. By leveraging advanced object recognition techniques, Systems with artificial intelligence can analyze data from medical imaging to determine and delineate tumor regions, facilitating early detection and precise localization of cancerous tissues. This approach aims to support clinicians in making well- informed choices, which eventually result in improved patient outcomes. Brain cancer diagnosis heavily relies on precise identification and interpretation of medical images. Recent advancements in AI (artificial intelligence) and object recognition techniques offer promising solutions to improve accuracy of diagnosis and efficiency. This study explores the use of AI-driven object recognition in brain cancer detection, leveraging CNNs, or convolutional neural networks, and transfer learning to identify tumors in both CT and MRI scans. Our High accuracy is attained by the suggested framework.in tumor detection, segmentation, and classification, outperforming traditional methods. By integrating AI-driven object recognition into clinical workflows, radiologists can benefit from enhanced diagnostic support, reduced interpretation time, and improved patient outcomes. This research demonstrates the potential of AI in revolutionizing brain cancer diagnosis and treatment

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IJARIIE Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. "IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 3 2025 Page 2073-2083
MLA Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. "IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION." International Journal Of Advance Research And Innovative Ideas In Education 11.3(2025) : 2073-2083.
APA Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, & Tanuja T. (2025). IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION. International Journal Of Advance Research And Innovative Ideas In Education, 11(3), 2073-2083.
Chicago Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. "IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 3 (2025) : 2073-2083.
Oxford Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. 'IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 3, 2025, p. 2073-2083. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/IMPROVING_BRAIN_CANCER_DETECTION_THROUGH_AI_DRIVEN_OBJECT__RECOGNAISATION_ijariie26711.pdf (Accessed : ).
Harvard Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. (2025) 'IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION', International Journal Of Advance Research And Innovative Ideas In Education, 11(3), pp. 2073-2083IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/IMPROVING_BRAIN_CANCER_DETECTION_THROUGH_AI_DRIVEN_OBJECT__RECOGNAISATION_ijariie26711.pdf (Accessed : )
IEEE Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T, "IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 3, pp. 2073-2083, May-Jun 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/IMPROVING_BRAIN_CANCER_DETECTION_THROUGH_AI_DRIVEN_OBJECT__RECOGNAISATION_ijariie26711.pdf [Accessed : ].
Turabian Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. "IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 3 ().
Vancouver Parvathi CM, Mathura yadav PV , Shailendra S, Chethan kumar P, and Tanuja T. IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(3) : 2073-2083. Available from: https://ijariie.com/AdminUploadPdf/IMPROVING_BRAIN_CANCER_DETECTION_THROUGH_AI_DRIVEN_OBJECT__RECOGNAISATION_ijariie26711.pdf
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