Literature DB >> 16686021

Characterizing vascular connectivity from microCT images.

Marcel Jackowski1, Xenophon Papademetris, Lawrence W Dobrucki, Albert J Sinusas, Lawrence H Staib.   

Abstract

X-ray microCT (computed tomography) has become a valuable tool in the analysis of vascular architecture in small animals. Because of its high resolution, a detailed assessment of blood vessel physiology and pathology is possible. Vascular measurement from noninvasive imaging is important for the study and quantification of vessel disease and can aid in diagnosis, as well as measure disease progression and response to therapy. The analysis of tracked vessel trajectories enables the derivation of vessel connectivity information, lengths between vessel junctions as well as level of ramification, contributing to a quantitative analysis of vessel architecture. In this paper, we introduce a new vessel tracking methodology based on wave propagation in oriented domains. Vessel orientation and vessel likelihood are estimated based on an eigenanalysis of gray-level Hessian matrices computed at multiple scales. An anisotropic wavefront then propagates through this vector field with a speed modulated by the maximum vesselness response at each location. Putative vessel trajectories can be found by tracing the characteristics of the propagation solution between different points. We present preliminary results from both synthetic and mouse microCT image data.

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Year:  2005        PMID: 16686021     DOI: 10.1007/11566489_86

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


  3 in total

1.  A non-parametric vessel detection method for complex vascular structures.

Authors:  Xiaoning Qian; Matthew P Brennan; Donald P Dione; Wawrzyniec L Dobrucki; Marcel P Jackowski; Christopher K Breuer; Albert J Sinusas; Xenophon Papademetris
Journal:  Med Image Anal       Date:  2008-06-14       Impact factor: 8.545

2.  A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks.

Authors:  Sepideh Almasi; Xiaoyin Xu; Ayal Ben-Zvi; Baptiste Lacoste; Chenghua Gu; Eric L Miller
Journal:  Med Image Anal       Date:  2014-11-28       Impact factor: 8.545

3.  Joint volumetric extraction and enhancement of vasculature from low-SNR 3-D fluorescence microscopy images.

Authors:  Sepideh Almasi; Ayal Ben-Zvi; Baptiste Lacoste; Chenghua Gu; Eric L Miller; Xiaoyin Xu
Journal:  Pattern Recognit       Date:  2016-09-22       Impact factor: 7.740

  3 in total

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