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In recent times, brain cancer has been recognized as one of the most deadly brain diseases. Gliomas are the most common type of brain tumor and have a high mortality rate (Bauer et al. 2013). These tumors develop in the brain or spinal cord and are classified into low-grade (LGGs) and high-grade gliomas (HGGs). Highgrade gliomas are highly aggressive and typically result in a life expectancy of around two years after diagnosis. This chapter discusses application of light-weight architecture for brain tumor prediction.

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Brain Tumor Prediction Using Transfer Learning and Light-Weight Deep Learning Architectures

  • 章节

  • 发表日期：

    2025年

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  • M. Arif Wani,
  • Bisma Sultan,
  • Sarwat Ali,
  • Mukhtar Ahmad Sofi

摘要

In recent times, brain cancer has been recognized as one of the most deadly brain diseases. Gliomas are the most common type of brain tumor and have a high mortality rate (Bauer et al. 2013). These tumors develop in the brain or spinal cord and are classified into low-grade (LGGs) and high-grade gliomas (HGGs). Highgrade gliomas are highly aggressive and typically result in a life expectancy of around two years after diagnosis. This chapter discusses application of light-weight architecture for brain tumor prediction.