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Machine learning for real-time optical property recovery in interstitial photodynamic therapy: a stimulation-based

Abdul-Amir Yassine1, Lothar Lilge2,3, Vaughn Betz1

  • 1Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Rd, Toronto, ON M5S3G8, Canada.

Biomedical Optics Express
|October 25, 2021
PubMed
Summary

This study introduces a machine learning approach to improve interstitial photodynamic therapy (iPDT) by accurately determining patient-specific optical properties. This enhances treatment planning and real-time power adjustments for better efficacy.

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