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Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer

Gemma Urbanos1,2, Alberto Martín1, Guillermo Vázquez1

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Summary

Hyperspectral imaging combined with machine learning aids brain tumor surgery by differentiating healthy and tumor tissues. This non-invasive approach achieved up to 95% accuracy, improving surgical precision and reducing damage to healthy areas.

Keywords:
brainclassificationconvolutional neural networkhyperspectral imagingmachine learningneurosurgeryrandom forestsupport vector machinetumor

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Area of Science:

  • Medical imaging
  • Machine learning
  • Oncology

Background:

  • Hyperspectral imaging (HSI) is a non-invasive, non-ionizing medical imaging technique.
  • Machine learning (ML) models enhance diagnostic capabilities in healthcare.
  • Accurate differentiation of brain tumor tissue is critical during surgery.

Purpose of the Study:

  • To evaluate the efficacy of HSI combined with ML for in-vivo differentiation of brain tumor tissues.
  • To train and compare Support Vector Machine (SVM), Random Forest (RF), and Convolutional Neural Network (CNN) classifiers.
  • To assess the contribution of spectral bands to classification accuracy.

Main Methods:

  • Utilized thirteen in-vivo hyperspectral images from twelve high-grade glioma patients.
  • Defined five tissue classes: healthy, tumor, venous blood vessel, arterial blood vessel, and dura mater.
  • Trained SVM, RF, and CNN classifiers on hyperspectral data.

Main Results:

  • Achieved Overall Accuracy (OACC) ranging from 60% to 95% depending on training conditions.
  • Demonstrated the potential of HSI and ML for real-time surgical guidance.
  • Spectral band contribution analysis showed significant improvement over existing literature.

Conclusions:

  • HSI combined with ML offers a reliable method for intraoperative brain tumor margin assessment.
  • The developed ML models can assist neurosurgeons in precise tissue differentiation.
  • This technique has the potential to improve surgical outcomes and minimize damage to healthy brain tissue.