TY - JOUR
T1 - Near-real-time Mueller polarimetric image processing for neurosurgical intervention
AU - Moriconi, Stefano
AU - Rodríguez-Núñez, Omar
AU - Gros, Romain
AU - Felger, Leonard A.
AU - Maragkou, Theoni
AU - Hewer, Ekkehard
AU - Pierangelo, Angelo
AU - Novikova, Tatiana
AU - Schucht, Philippe
AU - McKinley, Richard
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - Purpose: Wide-field imaging Mueller polarimetry is a revolutionary, label-free, and non-invasive modality for computer-aided intervention; in neurosurgery, it aims to provide visual feedback of white matter fibre bundle orientation from derived parameters. Conventionally, robust polarimetric parameters are estimated after averaging multiple measurements of intensity for each pair of probing and detected polarised light. Long multi-shot averaging, however, is not compatible with real-time in vivo imaging, and the current performance of polarimetric data processing hinders the translation to clinical practice. Methods: A learning-based denoising framework is tailored for fast, single-shot, noisy acquisitions of polarimetric intensities. Also, performance-optimised image processing tools are devised for the derivation of clinically relevant parameters. The combination recovers accurate polarimetric parameters from fast acquisitions with near-real-time performance, under the assumption of pseudo-Gaussian polarimetric acquisition noise. Results: The denoising framework is trained, validated, and tested on experimental data comprising tumour-free and diseased human brain samples in different conditions. Accuracy and image quality indices showed significant (p<0.05) improvements on testing data for a fast single-pass denoising versus the state-of-the-art and high polarimetric image quality standards. The computational time is reported for the end-to-end processing. Conclusion: The end-to-end image processing achieved real-time performance for a localised field of view (≈6.5mm2). The denoised polarimetric intensities produced visibly clear directional patterns of neuronal fibre tracts in line with reference polarimetric image quality standards; directional disruption was kept in case of neoplastic lesions. The presented advances pave the way towards feasible oncological neurosurgical translations of novel, label-free, interventional feedback.
AB - Purpose: Wide-field imaging Mueller polarimetry is a revolutionary, label-free, and non-invasive modality for computer-aided intervention; in neurosurgery, it aims to provide visual feedback of white matter fibre bundle orientation from derived parameters. Conventionally, robust polarimetric parameters are estimated after averaging multiple measurements of intensity for each pair of probing and detected polarised light. Long multi-shot averaging, however, is not compatible with real-time in vivo imaging, and the current performance of polarimetric data processing hinders the translation to clinical practice. Methods: A learning-based denoising framework is tailored for fast, single-shot, noisy acquisitions of polarimetric intensities. Also, performance-optimised image processing tools are devised for the derivation of clinically relevant parameters. The combination recovers accurate polarimetric parameters from fast acquisitions with near-real-time performance, under the assumption of pseudo-Gaussian polarimetric acquisition noise. Results: The denoising framework is trained, validated, and tested on experimental data comprising tumour-free and diseased human brain samples in different conditions. Accuracy and image quality indices showed significant (p<0.05) improvements on testing data for a fast single-pass denoising versus the state-of-the-art and high polarimetric image quality standards. The computational time is reported for the end-to-end processing. Conclusion: The end-to-end image processing achieved real-time performance for a localised field of view (≈6.5mm2). The denoised polarimetric intensities produced visibly clear directional patterns of neuronal fibre tracts in line with reference polarimetric image quality standards; directional disruption was kept in case of neoplastic lesions. The presented advances pave the way towards feasible oncological neurosurgical translations of novel, label-free, interventional feedback.
KW - AI
KW - Mueller polarimetric imaging
KW - Neurosurgery
KW - Real-time denoising
U2 - 10.1007/s11548-024-03090-6
DO - 10.1007/s11548-024-03090-6
M3 - Article
C2 - 38503943
AN - SCOPUS:85188122515
SN - 1861-6410
VL - 19
SP - 1033
EP - 1043
JO - International Journal of Computer Assisted Radiology and Surgery
JF - International Journal of Computer Assisted Radiology and Surgery
IS - 6
ER -
