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July 31, 2025Journal of improved oil and gas recovery technology.

Advancements in Multimodal Image Fusion and Deep Learning-based Segmentation Techniques for Gliomas: A Comprehensive Review

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Authors

LCLirong ChenLWLiqiang WangWWWei Wang

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Overview

This review explores deep learning approaches for image segmentation of gliomas, suggesting improvements in multimodal image fusion and diagnostic accuracy.

Key Points

  • Multimodal image fusion enhances the characterization of gliomas through the integration of diverse imaging techniques.
  • Deep learning models are vital for accurate segmentation of gliomas, aiding in treatment planning and diagnosis.
  • The review covers preprocessing methods and evaluation metrics crucial for effective image analysis in gliomas.
  • Challenges in data management and model interpretability are discussed, highlighting the need for ongoing research in this area.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/689a0c5fe6551bb0af8cf600https://doi.org/10.53469/wjimt.2025.08(07).13
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