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October 23, 2025Scientific ReportsOpen Access

A lightweight network for brain MRI segmentation

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Authors

PCPubali ChatterjeeACAmlan ChakrabartiKSKaushik Das Sharma

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Overview

This framework utilizes deep learning for brain segmentation, enhancing accuracy while addressing model complexity and class imbalance.

Key Points

  • Segmentation improves identification of brain diseases, making it crucial for medical imaging.
  • The method achieves high accuracy with a lightweight design, facilitating real-world application.
  • Analysis employing state-space modeling effectively captures long-range spatial dependencies for better performance.
  • This approach may enable superior segmentation results compared to traditional methods with higher complexity.

Cite This Study

Chatterjee et al. (2025) studied this question.

synapsesocial.com/papers/68fa32a40df2e6cd2f7421dahttps://doi.org/10.1038/s41598-025-18062-2
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