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Steerable3D: An ImageJ plugin for neurovascular enhancement in 3-D segmentation

DOI: 10.1016/j.ejmp.2020.12.010 DOI Help

Authors: Paolo Miocchi (IRCCS Fondazione Santa Lucia) , Alejandra Sierra (University of Eastern Finland) , Laura Maugeri (IRCCS Fondazione Santa Lucia; CNR, Rome Unit, Roma & Institute of Nanotechnology) , Eleonora Stefanutti (IRCCS Fondazione Santa Lucia) , Ali Abdollahzadeh (University of Eastern Finland) , Fabio Mangini (IRCCS Fondazione Santa Lucia) , Marta Moraschi (MARBILab) , Inna Bukreeva (CNR, Rome Unit, Roma & Institute of Nanotechnology; P.N. Lebedev Physical Institute, RAS) , Lorenzo Massimi (CNR, Rome Unit, Roma & Institute of Nanotechnology) , Francesco Brun (CNR, Rome Unit, Roma & Institute of Nanotechnology; University of Trieste) , Jussi Tohka (University of Eastern Finland) , Olli Gröhn (University of Eastern Finland) , Alberto Mittone (CELLS- ALBA Synchrotron Light Source) , Alberto Bravin (European Synchrotron Radiation Facility (ESRF)) , Charles Nicaise (URPhyM NARILIS, Université de Namur) , Federico Giove (MARBILab) , Alessia Cedola (CNR, Rome Unit, Roma & Institute of Nanotechnology) , M. Fratini (IRCCS Fondazione Santa Lucia; CNR, Rome Unit, Roma & Institute of Nanotechnology)
Co-authored by industrial partner: No

Type: Journal Paper
Journal: Physica Medica , VOL 81 , PAGES 197 - 209

State: Published (Approved)
Published: January 2021

Abstract: Purpose: Image processing plays a fundamental role in the study of central nervous system, for example in the analysis of the vascular network in neurodegenerative diseases. Synchrotron X-ray Phase-contrast micro-Tomography (SXPCT) is a very attractive method to study weakly absorbing samples and features, such as the vascular network in the spinal cord (SC). However, the identification and segmentation of vascular structures in SXPCT images is seriously hampered by the presence of image noise and strong contrast inhomogeneities, due to the sensitivity of the technique to small electronic density variations. In order to help with these tasks, we implemented a user-friendly ImageJ plugin based on a 3D Gaussian steerable filter, tuned up for the enhancement of tubular structures in SXPCT images. Methods: The developed 3D Gaussian steerable filter plugin for ImageJ is based on the steerability properties of Gaussian derivatives. We applied it to SXPCT images of ex-vivo mouse SCs acquired at different experimental conditions. Results: The filter response shows a strong amplification of the source image contrast-to-background ratio (CBR), independently of structures orientation. We found that after the filter application, the CBR ratio increases by a factor ranging from ~6 to ~60. In addition, we also observed an increase of 35% of the contrast to noise ratio in the case of injured mouse SC. Conclusion: The developed tool can generally facilitate the detection/segmentation of capillaries, veins and arteries that were not clearly observable in non-filtered SXPCT images. Its systematic application could allow obtaining quantitative information from pre-clinical and clinical images.

Journal Keywords: X-ray phase contrast tomography; Vascular network; 3D steerable filter

Subject Areas: Technique Development, Biology and Bio-materials

Instruments: I13-2-Diamond Manchester Imaging

Other Facilities: ID17 at ESRF

Added On: 20/01/2021 10:44

Discipline Tags:

Life Sciences & Biotech Technique Development - Life Sciences & Biotech

Technical Tags:

Imaging Tomography