X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
2002-08-05
2003-12-02
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S094000
Reexamination Certificate
active
06658080
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention relates to the setting of visualization parameter boundaries, such as color and opacity boundaries, for displaying images, in particular two-dimensional (2D) projections from three-dimensional (3D) data sets.
When displaying an image, such as in medical imaging applications, it is known to associate particular signal values with particular colors and opacities (known as visualization parameters) to assist visualization. This mapping is done when using data from a 3D data set (voxel data set) to compute a 2D data set (pixel data set) representing a 2D projection of the voxel data set for display on a computer screen or other conventional 2D display apparatus. This process is known as rendering.
The 2D data set is more amenable to user interpretation if different colors and opacities are allocated to different signal values in the 3D data set. The details of the mapping of signal values to colors and opacities are stored in a look-up table which is often referred to as the RGBA color table (R, G, B and A referring to red, green, blue and alpha (for opacity) respectively). The color table can be defined such that an entire color and opacity range is uniformly distributed between the minimum and maximum signal values in the voxel data set, as in a gray scale. Alternatively, the color table can be defined by attributing different discrete colors and opacities to different signal value ranges. In more sophisticated approaches, different sub-ranges are ascribed different colors (e.g. red) and the shade of the color is smoothly varied across each sub-range (e.g. crimson to scarlet).
When displaying data such as in medical imaging, the signal values comprising the data set do not usually correspond to what would normally be regarded as visual properties, such as color or intensity, but instead correspond to detected signal values from the measuring system used, such as computer-assisted tomography (CT) scanners, magnetic resonance (MR) scanners, ultrasound scanners and positron-emission-tomography (PET) systems. As an example, signal values from CT scanning will represent tissue opacity, i.e. X-ray attenuation. In order to improve the ease of interpretation of such images it is known to map different colors and opacities to different ranges of display value such that particular features, e.g. bone (which will generally have a relatively high opacity) can be more clearly distinguished from soft tissue (which will generally have a relatively low opacity).
When displaying a 2D projection of a 3D data set, in addition to attributing distinct ranges of color to voxels having particular signal value ranges, voxels within the 3D data set may also be selected for removal from the projected 2D image to reveal other more interesting features. The choice of which voxels are to be removed, or sculpted, from the projected image can also be based on the signal value associated with particular voxels. For example, those voxels having signal values which correspond to soft tissue can be sculpted, i.e. not rendered and therefore “invisible”, thereby revealing those voxels having signal values corresponding to bone which would otherwise be visually obscured by the soft tissue.
The determination of the most appropriate color table (known in the art as a preset) to apply to an image derived from a particular 3D data set is not trivial and is dependent on many features of the 3D data set. For example, the details of a suitable color table will depend on the subject, what type of data is being represented, whether (and if so, how) the data are calibrated and what particular features of the 3D data set the user might wish to highlight, which will depend on the clinical application. It can therefore be a difficult and laborious task to produce a displayed image that is clinically useful. Furthermore, there is inevitably an element of user-subjectivity in manually defining a color table and this can create difficulties in comparing and interpreting images created by different users, or even supposedly similar images created by a single user. In addition, the user will generally base the choice of color table on a specific 2D projection of the 3D data set rather than on characteristics of the overall 3D data set. A color table chosen for application to one particular projected image will not necessarily be appropriate to another projection of the same 3D data set. A color table which is objectively based on characteristics of the 3D data set rather than a single projection would be preferred.
Accordingly, there is a need in the art for a method of automatically determining appropriate color table presets when displaying medical image data.
SUMMARY OF THE INVENTION
According to the invention there is provided a method of setting visualization parameter boundaries for displaying an image from a 3D data set comprising a plurality of voxels, each with an associated signal value, comprising: selecting a volume of interest (VOI) within the 3D data set; generating a histogram of signal values from voxels that are within the VOI; applying a numerical analysis method to the histogram to determine a visualization threshold; and setting at least one of a plurality of boundaries for a visualization parameter according to the visualization threshold.
By restricting the histogram to voxels taken from the VOI, a numerical analysis method can be applied to the histogram which is sensitive to subtle variations in signal value and can reliably identify significant boundaries within the 3D data set for visualization. This allows the visualization parameter boundaries to be set automatically, which is especially useful for 3D data sets for which the signal values have no calibration, as is the case for MR scans.
In some embodiments, a first visualization parameter boundary is set at the visualization threshold. In other embodiments, first and second visualization parameter boundaries are set either side of the visualization threshold. This latter approach can be advantageous if an opacity curve interpolation algorithm is used to calculate an opacity curve between the visualization parameter boundaries.
The numerical analysis method may be applied once to determine only one visualization threshold. Remaining visualization parameter boundaries can then be set manually. Alternatively, the numerical analysis method can be applied iteratively to the histogram to determine a plurality of visualization thresholds and corresponding visualization parameter boundaries.
A significance test may be applied to visualization thresholds and, according to the outcome of the significance test, a significance marker can be ascribed for those ones of the voxels having signal values at or adjacent the visualization threshold, wherein the significance marker indicates significance or insignificance of the visualization threshold.
If two visualization parameter boundaries are set, one each side of the visualization threshold, and the visualization threshold is determined to be significant, then it is convenient to mark as significant only the voxels having signal values at one of the two visualization parameter boundaries. In one example, if a visualization threshold is calculated by the numerical analysis method to lie at a signal value of 54, and visualization parameter boundaries are set at 54±3, i.e. at 51 and 57, then the voxels with signal values of 57 can be marked as significant, and the voxels with signal values of 51 as insignificant.
The significance test can be used to distinguish between visualization parameter boundaries used as enhancements to visualizations of a single tissue type (known as cosmetic boundaries) and those used to identify different tissue-types for the purpose of segmentation (known as significant boundaries). Accordingly, the method may further comprise applying a selection tool to the 3D data set, wherein the selection tool is sensitive to the significance markers. One or more of the selection tools can be designed to ignore voxels that have been marked as insignificant.
Bissell Andrew John
Poole Ian
Bruce David V.
Renner , Otto, Boisselle & Sklar, LLP
Voxar Limited
LandOfFree
Displaying image data using automatic presets does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Displaying image data using automatic presets, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Displaying image data using automatic presets will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3140541