Alignment of histological and polarimetric large-scale imaging for brain tissue characterization.
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BORIS DOI
Publisher DOI
PubMed ID
40995534
Description
Significance
Mueller polarimetric imaging shows great promise for differentiating neoplastic from healthy brain tissue during neurosurgery. However, validating algorithmic approaches is limited by the scarcity of substantial tumor border zones in ex vivo samples, limiting comprehensive analysis of tumor margins.Aim
We propose a protocol to build a database of histologically annotated polarimetric images from formalin-fixed whole-brain sections. We focus on validating the image alignment pipeline on healthy tissue.Approach
To address the size mismatch between samples and the field of view of imaging instruments, we developed an automatic reconstruction pipeline to create large-scale polarimetric images from smaller raster-scanned tiles. Matching points between reference photographs and tile images allowed precise alignment. Similarly, fractionated histological sections were reconstructed and accurately aligned with the polarimetric data to serve as ground truth.Results
The integrated reconstruction and alignment approach enabled large-scale, spatially co-registered polarimetric and histological imaging, supporting a more detailed investigation of tissue polarimetric parameters. The database thus created will facilitate the training and evaluation of segmentation models.Conclusions
The developed method improved polarimetry-based brain tissue mapping by linking polarimetric parameters with histological features, enhancing the quality and quantity of data available for training and evaluating segmentation models. Although initially applied to brain tissue, the protocol could be extended to other organs to support broader studies of polarimetric tissue characterization.
Mueller polarimetric imaging shows great promise for differentiating neoplastic from healthy brain tissue during neurosurgery. However, validating algorithmic approaches is limited by the scarcity of substantial tumor border zones in ex vivo samples, limiting comprehensive analysis of tumor margins.Aim
We propose a protocol to build a database of histologically annotated polarimetric images from formalin-fixed whole-brain sections. We focus on validating the image alignment pipeline on healthy tissue.Approach
To address the size mismatch between samples and the field of view of imaging instruments, we developed an automatic reconstruction pipeline to create large-scale polarimetric images from smaller raster-scanned tiles. Matching points between reference photographs and tile images allowed precise alignment. Similarly, fractionated histological sections were reconstructed and accurately aligned with the polarimetric data to serve as ground truth.Results
The integrated reconstruction and alignment approach enabled large-scale, spatially co-registered polarimetric and histological imaging, supporting a more detailed investigation of tissue polarimetric parameters. The database thus created will facilitate the training and evaluation of segmentation models.Conclusions
The developed method improved polarimetry-based brain tissue mapping by linking polarimetric parameters with histological features, enhancing the quality and quantity of data available for training and evaluating segmentation models. Although initially applied to brain tissue, the protocol could be extended to other organs to support broader studies of polarimetric tissue characterization.
Date of Publication
2025-09
Publication Type
Article
Subject(s)
Keyword(s)
Mueller polarimetry
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brain tumors
•
image processing
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neuro-oncology
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neuropathology
Language(s)
en
Contributor(s)
Hewer, Ekkehard | |
Lucas, Théotim | |
Novikova, Tatiana |
Additional Credits
Series
Journal of Biomedical Optics
Publisher
Society of Photo-optical Instrumentation Engineers
ISSN
1560-2281
1083-3668
Access(Rights)
open.access