Toward reliable multigenerational analysis of anatomical trees in 3D high-resolution CT images

Yu, Kun‐Chang; Ritman, Erik L.; Kiraly, Atilla P.; Wan, Shu-Yen; Zamir, M.; Higgins, William E.

doi:10.1117/12.480299

Cited by 8 publications

(18 citation statements)

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“…A complete discussion of these quantities is given in the references. 5,16 The tables show that the generational description for h61's tree is far more sensible (and correct!) after tree editing than before, at least up to generation 5.…”

Section: Figs 12 and 13mentioning

confidence: 95%

“…13,14 The system is used following a 4-stage top-level approach depicted in Figure 2: (1) segment and define the surface of the tree of interest; (2) define the initial raw central axes, or centerlines, for the tree; (3) using various semi-automatic and interactive tools, correct identified tree defects; (4) perform interactive data mining to extract and examine quantitative tree data. This paper expands upon earlier efforts in building the Tree Analyzer, 11,12 gives a complete discussion of the current system, and highlights some of the interactive data-mining capabilities. Section 2 gives a discussion of the system, Section 3 presents results, and Section 4 offers concluding comments.…”

Section: Central-axesmentioning

confidence: 97%

“…The references give a detailed discussion of this sequence. 11,12,16 During Stage-3, possible tree defects are identified automatically with the Tree Diagnostician. Examples of the Tree Diagnostician and associated Defect List dialogue boxes are shown in the lower right portion of Fig.…”

Section: Tree Analysis Modulementioning

confidence: 99%

“…Yet, automated techniques, despite their imperfections, are essential in providing a complete description of a tree, and human interaction is essential for arriving at an accurate useful analysis of a tree. Our philosophy for tackling this problem, drawing upon these observations and espoused in earlier expositions of this effort, 11,12 is to use a judicious combination of automated analysis and computer-based human interaction to define a 3D tree.…”

Section: Introductionmentioning

confidence: 99%

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System for 3D visualization and data mining of large vascular trees

Ritman

Higgins

2005

SPIE Proceedings

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Modern micro-CT scanners produce very large 3D digital images of arterial trees. A typical 3D micro-CT image can consist of several hundred megabytes of image data, with a voxel resolution on the order of ten microns. The analysis and subsequent visualization of such images poses a considerable challenge. We describe a computerbased system for analyzing and visualizing such large 3D data sets. The system, dubbed the Tree Analyzer, processes an image in four major stages. In the first two stages, a series of automated 3D image-processing operations are applied to an input 3D digital image to produce a raw arterial tree and several supplemental data structures describing the tree (central-axis structure, surface rendering polygonal data, quantitative description of all tree branches). Next, the human interacts with the system to visualize and correct potential defects in the extracted raw tree. A series of sophisticated 3D editing tools and automated operations are available for this step. Finally, the corrected tree can be visualized and manipulated for data mining, using a large number of graphics-based rendering tools, such as 3D stereo viewing, global and local surface rendering, sliding-thin slabs, multiplanar reformatted views, projection images, and an interactive tree map. Quantitative data can also be perused for the tree. Results are presented for 3D micro-CT images of the heart and liver.

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Section: Figs 12 and 13mentioning

confidence: 95%

Section: Central-axesmentioning

confidence: 97%

Section: Tree Analysis Modulementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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System for 3D visualization and data mining of large vascular trees

Ritman

Higgins

2005

SPIE Proceedings

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“…33,66,88,86 The process of harvesting such data is highly tedious, and efforts are underway to apply computer imaging techniques to the complex vasculature of the heart and to develop computer software for detailed mapping and measurements which would otherwise have to be done manually. 61,83 In conclusion, in the overwhelming majority of heart failures the heart fails because of inadequate blood supply for its own metabolic needs. Blood supply to heart tissue is provided by a highly sophisticated dynamical system with an equally sophisticated network of conducting vessels.…”

Section: Dynamic and Transport Issues In Coronary Blood Flowmentioning

confidence: 98%

Cardiac Hemodynamics, Coronary Circulation and Interventional Cardiology

2005

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Microcirculation is the functional end of the coronary circulation and it plays a key role in the regulation of coronary blood flow, both on the local and global scales. A good understanding of its function under physiological and pathophysiological conditions is crucial but, because of its micro-scale, access to this part of the coronary circulation is extremely difficult and requires a considerable amount of innovation and new technologies. Dynamics of the coronary circulation provide the true vehicle by which blood supply reaches the myocardium- coronary vasculature is only the conducting component of that vehicle. It is highly unlikely that the pulsatile nature of the flow, the capacitance of the conducting vessels and the constant pounding of coronary vasculature by surrounding tissue are not part of the design, regulation, and function of the coronary circulation. Interventions, whether to assess or to correct coronary stenosis, continue to be the main clinical avenue to dealing with coronary heart disease. Clinical decisions rely heavily on the ability to determine the true morphology of an occlusive lesion, to predict the future course of that lesion and to assess the functional toll on coronary blood supply which it will inflict at each stage.

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System for the analysis and visualization of large 3D anatomical trees

Yu¹,

Ritman²,

Higgins³

2007

Computers in Biology and Medicine

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Modern micro-CT and multi-detector helical CT scanners can produce high-resolution 3D digital images of various anatomical trees. The large size and complexity of these trees make it essentially impossible to define them interactively. Automatic approaches have been proposed for a few specific problems, but none of these approaches guarantee extracting geometrically accurate multi-generational tree structures. This paper proposes an interactive system for defining and visualizing large anatomical trees and for subsequent quantitative data mining. The system consists of a large number of tools for automatic image analysis, semi-automatic and interactive tree editing, and an assortment of visualization tools. Results are presented for a variety of 3D high-resolution images.

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Toward reliable multigenerational analysis of anatomical trees in 3D high-resolution CT images

Cited by 8 publications

References 0 publications

System for 3D visualization and data mining of large vascular trees

System for 3D visualization and data mining of large vascular trees

Cardiac Hemodynamics, Coronary Circulation and Interventional Cardiology

System for the analysis and visualization of large 3D anatomical trees

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