Near-real-time Mueller polarimetric image processing for neurosurgical intervention.

Moriconi, Stefano; Rodríguez-Núñez, Omar; Gros, Romane; Felger, Leonard A; Maragkou, Theoni; Hewer, Ekkehard; Pierangelo, Angelo; Novikova, Tatiana; Schucht, Philippe; McKinley, Richard (2024). Near-real-time Mueller polarimetric image processing for neurosurgical intervention. International journal of computer assisted radiology and surgery, 19(6), pp. 1033-1043. Springer 10.1007/s11548-024-03090-6

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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.


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.


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 ( ) 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.


The end-to-end image processing achieved real-time performance for a localised field of view ( ). 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.

Item Type:

Journal Article (Original Article)


04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
04 Faculty of Medicine > Department of Head Organs and Neurology (DKNS) > Clinic of Neurosurgery
04 Faculty of Medicine > Service Sector > Institute of Pathology > Clinical Pathology
04 Faculty of Medicine > Service Sector > Institute of Pathology
04 Faculty of Medicine > Service Sector > Institute of Pathology > Tumour Pathology

UniBE Contributor:

Moriconi, Stefano, Rodriguez Nunez, Omar, Gros, Romane, Felger, Leonard Alexander, Maragkou, Theoni, Schucht, Philippe, McKinley, Richard Iain


600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology








Pubmed Import

Date Deposited:

21 Mar 2024 15:53

Last Modified:

15 Jun 2024 00:13

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Uncontrolled Keywords:

AI Mueller polarimetric imaging Neurosurgery Real-time denoising




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