1. Field of the Invention
The present invention concerns a method for reducing cupping artifacts in cone beam CT image data sets.
2. Description of the Prior Art
In cone beam computed tomography (CT), a fan-shaped x-ray beam is not used, but rather a conical x-ray beam. The reconstruction is based on the technique known as filtered back projection, which is also applied in other CT modalities, for example fan ray CT. Filtered back projection involves a convolution or filter algorithm that significantly influences the image character, for example the spatial resolution and noise. In the back-projection itself, the filtered raw data of the individual 2-D projections are projected back corresponding to their angular position in the image matrix. Conventionally, low-contrast applications (representation of soft tissues) was only conditionally possible. Due to newly developed area detectors and powerful generators, 3-D reconstructions of soft tissues with sufficient image quality are now possible. The visualization of soft tissues requires a particularly small or hard windowing due to low contrast differences. This means that a relatively small grey value or CT value range is spread over the entire grey value range of the monitor image. In the most important representation, namely axial reconstruction, cupping artifacts frequently appear. These are thereby a lightening or darkening in the boundary region of a subject. A constant component that prevents the application of a small windowing is added to the actual image signal. The physical cause of these artifacts can be, for example, radiation hardening, inadequate water normalization, sub-optimal pre-filtering or sub-optimal truncation correction. The cupping artifacts are conventionally eliminated or at least reduced by appropriate correction of the cited causes. In many cases, however, a viable correction is not entirely possible due insufficient system hardware performance, inadequate subject information or inadequate algorithms, etc.
An object of the present invention is to provide a method for reducing cupping artifacts in cone beam CT image data sets that can be implemented in a simple manner and without large hardware expenditure.
This object is achieved according to the invention by processing the image data set containing a cupping artifact with an automatically electronically implemented harmonization procedure. Harmonization is known for adaptation of the dynamic range in 2-D x-ray imaging and mammography for the purpose of optimally compensating the various tissue thicknesses (and thereby compensating global image brightenings) in an x-ray image in order to generate an equally-distributed image brightness for the diagnosis. The invention is based on the general idea of a symptomatic artifact correction, in contrast to conventional methods that focus, often a very elaborate manner, or the causes for cupping artifacts. It has been shown that artifacts of the type discussed herein can be eliminated or reduced by the use of a harmonization method that is known for other purposes, at least insofar as that the visualization of an image data set allows a reliable diagnosis. The harmonization is advantageously (because it is possible with relatively low calculation outlay) effected in 2D image data sets or a 3D reconstruction. It is also possible to implement the harmonization in the voxel data of a 3-D image data set. With regard to cupping artifacts, a completely corrected (thus artifact-free) 3D data set then exists from which arbitrary slices can be generated.
Two cupping artifacts, namely a darkening of the upper region 1 and a brightening of the lower subject region 2, are present the axial slice of a human pelvic region in
The cupping artifact of the subject region 2 is explained in
The suitable, known harmonization described in, for example, K. Wiesent et al., “Enhanced 3-D-Reconstruction Algorithm for C-arm Systems Suitable for Interventional Procedures”, IEEE Trans. on Medical Imaging, Vol. 19, No. 5, May 2000 is explained briefly in the following:
The harmonization algorithm reduces the low frequency portion (the aforementioned constant component) while obtaining the detail contrast of the image. This allows a smaller grey value window and therefore a further contrast intensification. A region g of the low-pass-filtered signal is subtracted from the original input signal s. In order to reproduce the background brightness mapping, a term g·LP{s3}(xROI, YROI) is added. This is the average value of a region of interest (ROI), whereby xROI and YROI are the coordinates of this range. A harmonized signal can be reproduced by the following formula:
s4(x, y)=s3(x, y)−g·LP{s3}(x, y)+g·LP{s3}(xROI, yROI).
The low-pass operation is implemented by a convolution or filtering of the original image data set with a quadratic (in terms of magnitude) convolution kernel, for example a 60×60 pixel matrix. Due to the large size of the convolution kernel, an expansion of the image signal is required across its image borders. This is achieved by a mirroring (reflection) of the signal at the image borders.
Although modifications and changes may be suggested by those skilled in the art, it is the intention of the inventors to embody within the patent warranted hereon all changes and modifications as reasonably and properly come within the scope of their contribution to the art.
Number | Date | Country | Kind |
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10 2005 003 227.3 | Jan 2005 | DE | national |