Literature DB >> 25485429

Crossing-preserving multi-scale vesselness.

Julius Hannink, Remco Duits, Erik Bekkers.   

Abstract

The multi-scale Frangi vesselness filter is an established tool in (retinal) vascular imaging. However, it cannot properly cope with crossings or bifurcations since it only looks for elongated structures. Therefore, we disentangle crossings/bifurcations via (multiple scale) invertible orientation scores and apply vesselness filters in this domain. This new method via scale-orientation scores performs considerably better at enhancing vessels throughout crossings and bifurcations than the Frangi version. Both methods are evaluated on a public dataset. Performance is measured by comparing ground truth data to the segmentation results obtained by basic thresholding and morphological component analysis of the filtered images.

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Mesh:

Year:  2014        PMID: 25485429     DOI: 10.1007/978-3-319-10470-6_75

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  5 in total

1.  Content-Aware Enhancement of Images With Filamentous Structures.

Authors:  Haris Jeelani; Haoyi Liang; Scott T Acton; Daniel S Weller
Journal:  IEEE Trans Image Process       Date:  2019-02-04       Impact factor: 10.856

2.  Unbiased analysis of mouse brain endothelial networks from two- or three-dimensional fluorescence images.

Authors:  Moises Freitas-Andrade; Cesar H Comin; Matheus Viana da Silva; Luciano da F Costa; Baptiste Lacoste
Journal:  Neurophotonics       Date:  2022-05-18       Impact factor: 4.212

3.  Combining efficient hand-crafted features with learned filters for fast and accurate corneal nerve fibre centreline detection.

Authors:  Roberto Annunziata; Ahmad Kheirkhah; Pedram Hamrah; Emanuele Trucco
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015-08

4.  A sub-Riemannian model of the visual cortex with frequency and phase.

Authors:  E Baspinar; A Sarti; G Citti
Journal:  J Math Neurosci       Date:  2020-07-29       Impact factor: 1.300

5.  Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D.

Authors:  Erik J Bekkers; Da Chen; Jorg M Portegies
Journal:  J Math Imaging Vis       Date:  2018-01-25       Impact factor: 1.627

  5 in total

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