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

Paolo Miocchi, Alejandra Sierra, Laura Maugeri, Eleonora Stefanutti, Ali Abdollahzadeh, Fabio Mangini, Marta Moraschi, Inna Bukreeva, Lorenzo Massimi, Francesco Brun, Jussi Tohka, Olli Gröhn, Alberto Mittone, Alberto Bravin, Charles Nicaise, Federico Giove, Alessia Cedola, Michela Fratini

Research output: Contribution to journalArticlepeer-review

Abstract

PurposeImage 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.MethodsThe 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.ResultsThe 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.ConclusionThe 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.

Original languageEnglish
Pages (from-to)197-209
Number of pages13
JournalPhysica Medica
Volume81
DOIs
Publication statusPublished - Jan 2021

Keywords

  • 3D steerable filter
  • Vascular network
  • X ray phase contrast tomography

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Physics and Astronomy(all)

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