Journal of applied mathematics & informatics

  • 제42권4호
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  • Pages.931-943
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  • 2024
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  • 2734-1194(pISSN)
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  • 2234-8417(eISSN)
한국전산응용수학회 (The Korean Society for Computational and Applied Mathematics)
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THE ELEVATION OF EFFICACY IDENTIFYING PITUITARY TISSUE ABNORMALITIES WITHIN BRAIN IMAGES BY EMPLOYING MEMORY CONTRAST LEARNING TECHNIQUES

  • S. SINDHU (Department of Computer Science and Applications, SRM Institute of Science and Technology) ;
  • N. VIJAYALAKSHMI (Department of Computer Science and Applications, SRM Institute of Science and Technology)
  • 투고 : 2023.12.14
  • 심사 : 2024.03.14
  • 발행 : 2024.07.30
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초록

Accurately identifying brain tumors is crucial for medical imaging's precise diagnosis and treatment planning. This study presents a novel approach that uses cutting-edge image processing techniques to automatically segment brain tumors. with the use of the Pyramid Network algorithm. This technique accurately and robustly delineates tumor borders in MRI images. Our strategy incorporates special algorithms that efficiently address problems such as tumor heterogeneity and size and shape fluctuations. An assessment using the RESECT Dataset confirms the validity and reliability of the method and yields promising results in terms of accuracy and computing efficiency. This method has a great deal of promise to help physicians accurately identify tumors and assess the efficacy of treatments, which could lead to higher standards of care in the field of neuro-oncology.

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과제정보

Grateful for the invaluable advice and criticism that Dr. N. Vijayalakshmi, an assistant professor at the SRM Institute of Science and Technology (Sr. G), provided during the course of this study.

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