Review on Brain Tumor Detection |
Author(s): |
| Akshada Borhade , DY Patil International University; Nikita Verma, DY Patil International University; Sulaxan Jadhav , DY Patil International University; Dr. Maheshwari Biradar, DY Patil International University |
Keywords: |
| Deep Learning Models, Machine Learning, Image Pre-Processing, Classifiers, Algorithms |
Abstract |
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Brain tumor detection is an important task in medical imaging since it can have a major impact on patient outcomes. There has been a surge in interest in developing automated systems to aid in the detection and diagnosis of brain tumors utilizing multiple imaging modalities in recent years. The major purpose is to highlight the proposed strategies and limitations of these approaches, as well as to examine their benefits for enhancing the accuracy and efficiency of brain tumor identification. Overall, the advancement of automated brain tumor detection systems has the potential to enhance patient outcomes by allowing for earlier identification, more accurate diagnosis, and more prompt treatment. |
Other Details |
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Paper ID: IJSRDV11I30341 Published in: Volume : 11, Issue : 3 Publication Date: 01/06/2023 Page(s): 425-428 |
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