This paper presents an image processing approach for information extraction from three-dimensional (3-D) images of vasculature. It extracts quantitative information such as skeleton, length, diameter, and vessel-to-ti...
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This paper presents an image processing approach for information extraction from three-dimensional (3-D) images of vasculature. It extracts quantitative information such as skeleton, length, diameter, and vessel-to-tissue ratio for different vessels as well as their branches. Furthermore, it generates 3-D visualization of vessels based on desired anatomical characteristics such as vessel diameter or 3-D connectivity. Steps of the proposed approach are: (1) pre-processing, (2) distance mappings, (3) branch labeling, (4) quantification, and (5) visualization. We have tested and evaluated the proposed algorithms using simulated images of multi-branch vessels and real confocal microscopic images of the vessels in rat brains. Experimental results illustrate performance of the methods and usefulness of the results for medical image analysis applications. (c) 2004 Elsevier Ltd. All rights reserved.
3-D analysis of blood vessels from volumetric CT and MR datasets has many applications ranging from examination of pathologies such as aneurysm and calcification to measurement of cross-sections for therapy planning. ...
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ISBN:
(纸本)0819464236
3-D analysis of blood vessels from volumetric CT and MR datasets has many applications ranging from examination of pathologies such as aneurysm and calcification to measurement of cross-sections for therapy planning. Segmentation of the vascular structures followed by tracking is an important processing step towards automating the 3-D vessel analysis workflow. This paper demonstrates a fast and automated algorithm for tracking the major arterial structures that have been previously segmented. Our algorithm uses anatomical knowledge to identify the start and end points in the vessel structure that allows automation. voxel coding scheme is used to code every voxel in the vessel based on its geodesic distance from the start point. A shortest path based iterative region growing is used to extract the vessel tracks that are subsequently smoothed using an active contour method. The algorithm also has the ability to automatically detect bifurcation points of major arteries. Results are shown for tracking the major arteries such as the common carotid, internal carotid, vertebrals, and arteries coming off the Circle of Willis across multiple cases with various data related and pathological challenges from 7 CTA cases and 2 MR Time of Flight (TOF) cases.
This paper presents an image processing method for information extraction from 3D images of vasculature. It automates the study of vascular structures by extracting quantitative information such as skeleton, length, d...
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ISBN:
(纸本)0819440078
This paper presents an image processing method for information extraction from 3D images of vasculature. It automates the study of vascular structures by extracting quantitative information such as skeleton, length, diameter, and vessel-to-tissue ratio for different vessels as well as their branches. Furthermore, it generates 3D visualization of vessels based on desired anatomical characteristics such as vessel diameter or 3D connectivity. Steps of the proposed approach are as follows. 1) Preprocessing, in which intensity adjustment, optimal thresholding, and median filtering are done. 2) 3D thinning, in which medial axis and skeleton of the vessels are found. 3) Branch labeling, in which different branches are identified and each voxel is assigned to the corresponding branch. 4) Quantitation, in which length of each branch is estimated, based on the number of voxels assigned to it, and its diameter is calculated using the medial axis direction. 5) Visualization, in which vascular structure is shown in 3D, using color coding and surface rendering methods. We have tested and evaluated the proposed algorithms using simulated images of multi-branch vessels and real confocal microscopic images of the vessels in rat brains. Experimental results illustrate performance of the methods and usefulness of the results for medical image analysis applications.
This paper introduces a two-phase algorithm to extract a center-adjusted, one-voxel-thick line, representation of cerebral vascular trees from volume angiograms coded in gray-scale intensity. The first stage extracts ...
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ISBN:
(纸本)0819446564
This paper introduces a two-phase algorithm to extract a center-adjusted, one-voxel-thick line, representation of cerebral vascular trees from volume angiograms coded in gray-scale intensity. The first stage extracts and arranges, the vessel system in the form of a directed graph whose nodes correspond to the cross sections of the vessels and whose node connectivity encodes their adjacency. The manual input reduces to the selection of two thresholds and the designation of a single initial point. In a second stage, each node is replaced by a centered voxel. The locations of the extracted centerlines are insensitive to noise and to the thresholds used. The overall computational cost is linear, of the order of the size of the input image. An example is provided which demonstrates the result of the algorithm applied to actual data. While being developed to reconstruct a line representation of a vessel network, the-proposed algorithm can also be used to estimate quantitative features in any 2-D and/or 3-D intensity images. This technique is sufficiently fast to process large 3-D images at interactive rates using commodity computers.
Current sulcal modeling techniques depend, more or less, on manual interpretation. We propose a robust voxel-coding methodology for automatic extraction and parameterization of the sulcal surfaces from volume data set...
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Current sulcal modeling techniques depend, more or less, on manual interpretation. We propose a robust voxel-coding methodology for automatic extraction and parameterization of the sulcal surfaces from volume data sets. The cortical sulci are generated in two steps: initial contour extraction and final contour generation. A voxel-coding technique based on the exterior boundary of the cerebral cortex extracts the initial contours. A similar voxel-coding technique generates the final contours. Results, and comparisons with manually derived surface models, demonstrate the potential of our methodology.
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