ArticleMedical image analysis2009
A non-parametric vessel detection method for complex vascular structures.
Article in Medical image analysis, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review.La Radiologia medica · 2022Pooled it
- Masked Vascular Structure Segmentation and Completion in Retinal Images.IEEE transactions on medical imaging · 2025Article
- Vessel segmentation for X-ray coronary angiography using ensemble methods with deep learning and filter-based features.BMC medical imaging · 2022Article
- Vascularity and Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging.Frontiers in radiology · 2021Review
- CT Image Enhancement for Feature Detection and Localization.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2017Article
- Joint volumetric extraction and enhancement of vasculature from low-SNR 3-D fluorescence microscopy images.Pattern recognition · 2017Article
- A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks.Medical image analysis · 2015Article
- Automatic extraction of blood vessels in the retinal vascular tree using multiscale medialness.International journal of biomedical imaging · 2015Article
- A nonparametric shape prior constrained active contour model for segmentation of coronaries in CTA images.Computational and mathematical methods in medicine · 2014Article
- A Hessian-based filter for vascular segmentation of noisy hepatic CT scans.International journal of computer assisted radiology and surgery · 2012Article
- Estimation of local orientations in fibrous structures with applications to the Purkinje system.IEEE transactions on bio-medical engineering · 2011Article
- Vascular Tree Reconstruction by Minimizing A Physiological Functional Cost.Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops · 2010Article
- SERIAL NONRIGID VASCULAR REGISTRATION USING WEIGHTED NORMALIZED MUTUAL INFORMATION.Proceedings. IEEE International Symposium on Biomedical Imaging · 2010Article
- Effective visualization of complex vascular structures using a non-parametric vessel detection method.IEEE transactions on visualization and computer graphicsArticle
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Authors and funding
8 authors.
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Abstract
Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions.
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