Fiber enhancement and 3D orientation analysis in label-free two-photon fluorescence microscopy

Year: 2023

Authors: Sorelli Michele; Costantini Irene; Bocchi Leonardo; Axer Markus; Pavone Francesco Saverio; Mazzamuto Giacomo

Autors Affiliation: Univ Florence, Dept Phys & Astron, I-50019 Sesto Fiorentino, Italy; European Lab Nonlinear Spect LENS, I-50019 Sesto Fiorentino, Italy; Univ Florence, Dept Biol, I-50019 Sesto Fiorentino, Italy; Natl Inst Opt CNR INO, Natl Res Council, I-50019 Sesto Fiorentino, Italy; Univ Florence, Dept Informat Engn, I-50039 Florence, Italy; Res Ctr Julich, Inst Neurosci & Med, D-52428 Julich, Germany.

Abstract: Fluorescence microscopy can be exploited for evaluating the brain?s fiber architecture with unsurpassed spatial resolution in combination with different tissue preparation and staining protocols. Differently from state-of-the-art polarimetry-based neuroimaging modalities, the quantification of fiber tract orientations from fluorescence microscopy volume images entails the application of specific image processing techniques, such as Fourier or structure tensor analysis. These, however, may lead to unreliable outcomes as they do not isolate myelinated fibers from the surrounding tissue. In this work, we describe a novel image processing pipeline that enables the computation of accurate 3D fiber orientation maps from both grey and white matter regions, exploiting the selective multiscale enhancement of tubular structures of varying diameters provided by a 3D implementation of the Frangi filter. The developed software tool can efficiently generate orientation distribution function maps at arbitrary spatial scales which may support the histological validation of modern diffusion-weighted magnetic resonance imaging tractography. Despite being tested here on two-photon scanning fluorescence microscopy images, acquired from tissue samples treated with a label-free technique enhancing the autofluorescence of myelinated fibers, the presented pipeline was developed to be employed on all types of 3D fluorescence images and fiber staining.

Journal/Review: SCIENTIFIC REPORTS

Volume: 13      Pages from: 4160-1  to: 4160-15

KeyWords: brain, fluorescence microscopy, fibers, image processing
DOI: 10.1038/s41598-023-30953-w

ImpactFactor: 3.800
Citations: 3
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-11-24
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