Machine learning methods for spectrally-resolved imaging analysis in neuro-oncology

Machine learning methods for spectrally-resolved imaging analysis in neuro-oncology

To reduce the frequency of relapses after surgical removal a brain tumor, it is critically important to completely remove all affected areas of the brain without disrupting the functionality of vital organs. Therefore, intraoperative differential diagnostics of micro-areas of tumor tissue with their...

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Bibliographic Details
Main Authors: T. A. Savelieva, I. D. Romanishkin, A. Ospanov, K. G. Linkov, S. A. Goryajnov, G. V. Pavlova, I. N. Pronin, V. B. Loschenov
Format: Article
Language:Russian
Published: Non-profit partnership for development of domestic photodynamic therapy and photodiagnosis "Russian Photodynamic Association" 2024-12-01
Series:Biomedical Photonics
Subjects:
optical spectroscopy
spectrally-resolved imaging
intracranial tumor
machine learning
fluorescence intraoperative navigation
fluorescence endomicroscopy
raman microscopy
cars
stimulated raman histology
, hyperspectral images
Online Access:https://www.pdt-journal.com/jour/article/view/680
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