Impromptu: a system for automatic 3D medical image-analysis

Sundaramoorthy, Gopal; Hoford, John; Hoffman, Eric A.; Higgins, William E.

doi:10.1016/0895-6111(94)00042-5

Cited by 14 publications

(4 citation statements)

References 17 publications

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“…This applies equally to the fetal sac and its contents. As manual segmentation is a time-consuming, tedious and impractical procedure (19), several semiautomatic and automatic software packages with capabilities for different types of volume visualization and analysis have been developed and are available on the market (20,21). The use of advanced software in data processing may add considerably to the accuracy and usefulness of volume determination based on manual segmentation.…”

Section: Discussionmentioning

confidence: 99%

Magnetic resonance imaging compared to ultrasonography in fetal weight and volume estimation in diabetic and normal pregnancy

UOTILA¹,

DASTIDAR²,

HEINONEN³

et al. 2000

Acta Obstet Gynecol Scand

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High-resolution magnetic resonance imaging combined with semiautomatic segmentation software was found to be accurate in determining fetal volume and, consequently, better than conventional ultrasound-based techniques in estimating fetal weight. The use of magnetic resonance imaging in fetal weight estimation may be recommended for clinical situations where an accurate weight estimate is considered essential.

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Section: Discussionmentioning

confidence: 99%

Magnetic resonance imaging compared to ultrasonography in fetal weight and volume estimation in diabetic and normal pregnancy

UOTILA¹,

DASTIDAR²,

HEINONEN³

et al. 2000

Acta Obstet Gynecol Scand

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“…Optical sectioning permits faster, less invasive, more thorough digital analysis and 3D rendering than is possible with physical sectioning. Large upper airways can be analyzed with modern techniques such as magnetic resonance microscopy (24,60) or optical coherence tomography (20); functional imaging of the lung by CT and MRI has recently been summarized by van Beek and Hoffman (63). Laser scanning confocal microscopy provides sufficient resolution to image fine-scale acinar detail, but there have been very few 3D acinar reconstruction studies using this method.…”

Section: Historical Perspectivementioning

confidence: 99%

Finite element 3D reconstruction of the pulmonary acinus imaged by synchrotron X-ray tomography

Tsuda¹,

Filipović²,

Haberthür³

et al. 2008

Journal of Applied Physiology

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The alveolated structure of the pulmonary acinus plays a vital role in gas exchange function. Three-dimensional (3D) analysis of the parenchymal region is fundamental to understanding this structure-function relationship, but only a limited number of attempts have been conducted in the past because of technical limitations. In this study, we developed a new image processing methodology based on finite element (FE) analysis for accurate 3D structural reconstruction of the gas exchange regions of the lung. Stereologically well characterized rat lung samples (Pediatr Res 53: 72-80, 2003) were imaged using high-resolution synchrotron radiation-based X-ray tomographic microscopy. A stack of 1,024 images (each slice: 1024 x 1024 pixels) with resolution of 1.4 mum(3) per voxel were generated. For the development of FE algorithm, regions of interest (ROI), containing approximately 7.5 million voxels, were further extracted as a working subunit. 3D FEs were created overlaying the voxel map using a grid-based hexahedral algorithm. A proper threshold value for appropriate segmentation was iteratively determined to match the calculated volume density of tissue to the stereologically determined value (Pediatr Res 53: 72-80, 2003). The resulting 3D FEs are ready to be used for 3D structural analysis as well as for subsequent FE computational analyses like fluid dynamics and skeletonization.

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“…Invoked either from the Edit option or toolbar, it enables the construction and invocation of a script used for performing Stage-1 and Stage-2 automated analysis. A script consist of a sequence of selected operations to perform a specified image-processing task [28]. Over 100 operations are available in the following general categories: (a) image enhancement; (b) mathematical morphology operations for shape-based image analysis; (c) topological operations for defining connected components, deleting interior cavities, extracting and manipulating central-axes structures, etc.…”

Section: D Image-processing Toolboxmentioning

confidence: 99%

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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Impromptu: a system for automatic 3D medical image-analysis

Cited by 14 publications

References 17 publications

Magnetic resonance imaging compared to ultrasonography in fetal weight and volume estimation in diabetic and normal pregnancy

Magnetic resonance imaging compared to ultrasonography in fetal weight and volume estimation in diabetic and normal pregnancy

Finite element 3D reconstruction of the pulmonary acinus imaged by synchrotron X-ray tomography

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

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