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Brain tumor detection using HyGSNet and feature extraction with DWT-based GDP.

Ponlatha Sambandham1, Someswari Perla2, Katakam Venkateswara Rao3

  • 1Department of ECE, Mahendra Engineering College, Tamil Nadu, India.

Journal of Neuroimmunology
|January 27, 2026
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Summary
This summary is machine-generated.

This study introduces Hybrid Google SpinalNet (HyGSNet), an AI system for detecting brain tumors in MRI scans. HyGSNet offers a reliable and accurate method for early detection, improving patient outcomes.

Keywords:
Adaptive wiener filterGoogleNetHyGSNetSpinalNetUNeXt

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Area of Science:

  • Medical Image Analysis
  • Artificial Intelligence in Healthcare
  • Neurological Imaging

Background:

  • Brain tumors are serious neurological conditions often leading to psychiatric issues.
  • Early detection and treatment are crucial for improving patient quality of life and healing.
  • Manual analysis of medical images for brain tumor detection is time-consuming and requires expert interpretation.

Purpose of the Study:

  • To develop an intelligent system for automated brain tumor detection from MRI images.
  • To enhance clinical decision-making through accurate and efficient abnormality classification.
  • To introduce the Hybrid Google SpinalNet (HyGSNet) model for brain tumor detection.

Main Methods:

  • Utilized Adaptive Wiener filter for image pre-processing.
  • Employed UNeXt for segmentation of filtered MRI images.
  • Implemented image augmentation and feature extraction prior to HyGSNet analysis.

Main Results:

  • The HyGSNet model achieved high performance metrics.
  • Specificity was recorded at 93%, accuracy at 93%, and sensitivity at 93.7%.
  • The proposed approach demonstrated robustness and reliability in brain tumor detection.

Conclusions:

  • The HyGSNet model shows significant promise for automated brain tumor detection.
  • The system provides accurate and reliable results, supporting clinical diagnosis.
  • This AI-driven approach can aid in timely intervention and treatment planning.