<  Retour au portail Polytechnique Montréal

Data consistency and classification model transferability across biomedical Raman spectroscopy systems

Fabien Picot, François Daoust, Guillaume Sheehy, Frédérick Dallaire, Layal Chaikho, Théophile Bégin, Samuel Kadoury et Frédéric Leblond

Article de revue (2020)

Document en libre accès dans PolyPublie et chez l'éditeur officiel
[img]
Affichage préliminaire
Libre accès au plein texte de ce document
Version officielle de l'éditeur
Conditions d'utilisation: Creative Commons: Attribution (CC BY)
Télécharger (492kB)
Afficher le résumé
Cacher le résumé

Abstract

Surgical guidance applications using Raman spectroscopy are being developed at a rapid pace in oncology to ensure safe and complete tumor resection during surgery. Clinical translation of these approaches relies on the acquisition of large spectral and histopathological data sets to train classification models. Data calibration must ensure compatibility across Raman systems and predictive model transferability to allow multi-centric studies to be conducted. This paper addresses issues relating to Raman measurement standardization by first comparing Raman spectral measurements made on an optical phantom and acquired with nine distinct point probe systems and one wide-field imaging instrument. Data standardization method led to normalized root-mean-square deviations between instruments of 2%. A classification model discriminating between white and gray matter was trained with one point probe system. When used to classify independent data sets acquired with the other systems, model predictions led to >95% accuracy, preliminarily demonstrating model transferability across different biomedical Raman spectroscopy instruments.

Mots clés

cancer, classification models, medical imaging, Raman spectroscopy

Sujet(s): 3100 Physique > 3100 Physique
3100 Physique > 3101 Études atomiques et moléculaires
3100 Physique > 3111 Laser
Département: Département de génie physique
Organismes subventionnaires: CRSNG/NSERC - Discovery Grant Program, TransMedTech Institute, Canadian Institutes of Health Research & CRSNG/NSERC - Collaborative Health Research Program, Canadian Network for Research and Innovation in Machining Technology
URL de PolyPublie: https://publications.polymtl.ca/9253/
Titre de la revue: Translational Biophotonics (vol. 3, no 1)
Maison d'édition: Wiley
DOI: 10.1002/tbio.202000019
URL officielle: https://doi.org/10.1002/tbio.202000019
Date du dépôt: 26 janv. 2022 15:22
Dernière modification: 20 mai 2023 11:09
Citer en APA 7: Picot, F., Daoust, F., Sheehy, G., Dallaire, F., Chaikho, L., Bégin, T., Kadoury, S., & Leblond, F. (2020). Data consistency and classification model transferability across biomedical Raman spectroscopy systems. Translational Biophotonics, 3(1), 1-11. https://doi.org/10.1002/tbio.202000019

Statistiques

Total des téléchargements à partir de PolyPublie

Téléchargements par année

Provenance des téléchargements

Dimensions

Actions réservées au personnel

Afficher document Afficher document