Biomedical subjects

J D Hoford

Publications and source records attributed to J D Hoford.

4 recordsLinked to original sources

PubMed1995

Measurement of three-dimensional lung tree structures by using computed tomography.

A method was devised to computationally segment and measure three-dimensional pulmonary trees in situ. Bronchi and pulmonary vessels were computationally extracted from volumetric computed tomography data based on radiopacity differences between airway wall and airway lumen and between blood and parenchyma, respectively. The tree was reduced to a central axis to facilitate measurement of branch segment length and angle. Cross-sectional area was measured on a reconstructed computed tomography slice perpendicular to this central axis. The method was validated by scanning two Plexiglas phantoms and an intact lung. Reconstructed diameters in the phantoms were accurate for branches > 2 mm. In the lung airway branches between 1 and 2 mm in diameter were often unresolved when their angle of orientation with respect to the axis of the scanner was > 45 degrees. However, if a branch was resolved, its reconstructed diameter was little affected by orientation. This method represents a significant improvement in the analysis of complex pulmonary structures in three dimensions.

Algorithms↗

PubMed1993

Tool box-based cardiac volumes: visualization and quantitation by computed tomography.

Volumetric image display and analysis techniques have been under development to support x-ray computed tomographic (CT) imaging of the heart and lungs since the mid 1970s when investigators began to understand the image analysis requirements for the Dynamic Spatial Reconstructor. With the spread of Imatron's C-100 scanners (Imatron, South San Francisco, CA) around the world along with the development of slower helical scanners that generate volumetric information, there is an increased interest in the use of volume visualization and analysis tools to study the cardiopulmonary system. An historic overview of the development of such volume visualization for x-ray CT scanning is given along with a discussion of techniques for data acquisition, volumetric display, and image quantitation. We further show throughout the discussion how the integration of tools into a comprehensive image display and analysis software package (the tool box) enhances the utility of the individual tools. An example of such a tool box is given in a discussion of an X Windows-based package dubbed VIDA.

Cardiac Volume↗

PubMedDate not supplied

A method for measurement of cross sectional area, segment length, and branching angle of airway tree structures in situ.

Accurate quantitative measurements of airway and vascular dimensions are essential for evaluating function in both the normal and in the diseased lung. This report describes a new integrated method for three-dimensional (3D) extraction and analysis of pulmonary tree structures using data from High Resolution Computed Tomography (HRCT). Serially scanned two-dimensional (2D) slices of the lower left lobe of isolated dog lungs were stacked to create a volume of data. Airway and vascular trees were extracted using a 3D seeded region-growing algorithm based on differences in CT number between wall and lumen. In the region-growing step, voxels in the lumen are tagged with a distance descriptor to identify points along the tree structure equidistant from the seed point. To obtain quantitative data, we reduced each tree to its central axis. From the central axis, branch length was measured as the distance between two successive branch points, branch angle was measured as the angle produced by two daughter branches, and cross-sectional area was measured from a plane perpendicular to the central axis point. Data derived from these methods can be used to localize and quantify structural differences both during different physiologic conditions and in pathologic lungs.

Algorithms↗

PubMedDate not supplied

IMPROMPTU: a system for automatic 3D medical image-analysis.

The utility of three-dimensional (3D) medical imaging is hampered by difficulties in extracting anatomical regions and making measurements in 3D images. Presently, a user is generally forced to use time-consuming, subjective, manual methods, such as slice tracing and region painting, to define regions of interest. Automatic image-analysis methods can ameliorate the difficulties of manual methods. This paper describes a graphical user interface (GUI) system for constructing automatic image-analysis processes for 3D medical-imaging applications. The system, referred to as IMPROMPTU, provides a user-friendly environment for prototyping, testing and executing complex image-analysis processes. IMPROMPTU can stand alone or it can interact with an existing graphics-based 3D medical image-analysis package (VIDA), giving a strong environment for 3D image-analysis, consisting of tools for visualization, manual interaction, and automatic processing. IMPROMPTU links to a large library of 1D, 2D, and 3D image-processing functions, referred to as VIPLIB, but a user can easily link in custom-made functions. 3D applications of the system are given for left-ventricular chamber, myocardial, and upper-airway extractions.

Computer Graphics↗