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  Authors

Nitin Prajapati,Raj Gupta,Shivam Singh,Dr. Bhawesh K. Thakur

  Keywords

Brain Tumor, MRI, YOLO

  Abstract


Automated detection and localization of brain tumors in MRI scans are essential tasks in clinical practice, facilitating early diagnosis and treatment planning. Recent advancements in deep learning techniques have led to the development of efficient and accurate models for this purpose. You Only Look Once (YOLO) models have shown promising results in detecting brain tumors with high precision and recall. This abstract presents a summary of recent research efforts utilizing YOLO-based models for brain tumor detection and localization. These studies leverage transfer learning, fine-tuning approaches, and innovative architectural designs to train models on annotated MRI datasets. Experimental analyses demonstrate the robust performance of these models, achieving notable metrics such as precision, recall, and mean average precision (mAP). Furthermore, computational analyses indicate the efficient resource utilization of these models, making them suitable for deployment across diverse computing platforms. Despite architectural complexities, these models exhibit stable convergence during training, highlighting their reliability and effectiveness in medical applications. Overall, the findings underscore the potential of YOLO-based models as robust and efficient tools for automated brain tumor detection, paving the way for improved diagnostic accuracy and clinical decision-making in neuroimaging.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2405882

  Paper ID - 261007

  Author type - Indian Author

  Page Number(s) - i98-i101

  Pubished in - Volume 12 | Issue 5 | May 2024

  DOI (Digital Object Identifier) -   

  No Of Downloads - 10

  Author Country - India, 226028, Lucknow, Lucknow, 226028, Science and Technology

  Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2405882

  Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRT2405882

  Published Paper PDF Downlaod: - download.php?file=IJCRT2405882

  Cite this article

Nitin Prajapati,Raj Gupta,Shivam Singh,Dr. Bhawesh K. Thakur,   "Advancements in Automated Brain Tumor Detection: A Review of YOLO-Based Deep Learning Models", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.i98-i101, May 2024, Available at :http://www.ijcrt.org/papers/IJCRT2405882.pdf

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