In radiography, one of the best methods to eliminate image-degrading scatter radiation is the use of anti-scatter grids. However, with high-resolution dynamic imaging detectors, stationary anti-scatter grids can leave grid-line shadows and moiré patterns on the image, depending upon the line density of the grid and the sampling frequency of the x-ray detector. Such artifacts degrade the image quality and may mask small but important details such as small vessels and interventional device features. Appearance of these artifacts becomes increasingly severe as the detector spatial resolution is improved. We have previously demonstrated that, to remove these artifacts by dividing out a reference grid image, one must first subtract the residual scatter that penetrates the grid; however, for objects with anatomic structure, scatter varies throughout the FOV and a spatially differing amount of scatter must be subtracted. In this study, a standard stationary Smit-Rontgen X-ray grid (line density - 70 lines/cm, grid ratio - 13:1) was used with a high-resolution CMOS detector, the Dexela 1207 (pixel size - 75 micron) to image anthropomorphic head phantoms. For a 15 × 15cm FOV, scatter profiles of the anthropomorphic head phantoms were estimated then iteratively modified to minimize the structured noise due to the varying grid-line artifacts across the FOV. Images of the anthropomorphic head phantoms taken with the grid, before and after the corrections, were compared demonstrating almost total elimination of the artifact over the full FOV. Hence, with proper computational tools, anti-scatter grid artifacts can be corrected, even during dynamic sequences.

Higher resolution in dynamic radiological imaging such as angiography is increasingly being demanded by clinicians; however, when standard anti-scatter grids are used with such new high resolution detectors, grid-line artifacts become more apparent resulting in increased structured noise that may overcome the contrast signal improvement benefits of the scatter-reducing grid. Although grid-lines may in theory be eliminated by dividing the image of a patient taken with the grid by a flat-field image taken with the grid obtained prior to the clinical image, unless the remaining additive scatter contribution is subtracted in real-time from the dynamic clinical image sequence before the division by the reference image, severe grid-line artifacts may remain. To investigate grid-line elimination, a stationary Smit Röntgen X-ray grid (line density: 70 lines/cm, grid ratio 13:1) was used with both a 75 micron-pixel CMOS detector and a standard 194 micron-pixel flat panel detector (FPD) to image an artery block insert placed in a modified uniform frontal head phantom for a 20 × 20cm FOV (approximately). Contrast and contrast-to-noise ratio (CNR) were measured with and without scatter subtraction prior to grid-line correction. The fixed pattern noise caused by the grid was substantially higher for the CMOS detector compared to the FPD and caused a severe reduction of CNR. However, when the scatter subtraction corrective method was used, the removal of the fixed pattern noise (grid artifacts) became evident resulting in images with improved CNR.

Purpose: Anti‐scatter grid‐line artifacts are more prominent for high‐resolution x‐ray detectors since the fraction of a pixel blocked by the grid septa is large. Direct logarithmic subtraction of the artifact pattern is limited by residual scattered radiation and we investigate an iterative method for scatter correction. Methods: A stationary Smit‐Rοntgen anti‐scatter grid was used with a high resolution Dexela 1207 CMOS X‐ray detector (75 µm pixel size) to image an artery block (Nuclear Associates, Model 76‐705) placed within a uniform head equivalent phantom as the scattering source. The image of the phantom was divided by a flat‐field image obtained without scatter but with the grid to eliminate grid‐line artifacts. Constant scatter values were subtracted from the phantom image before dividing by the averaged flat‐field‐with‐grid image. The standard deviation of pixel values for a fixed region of the resultant images with different subtracted scatter values provided a measure of the remaining grid‐line artifacts. Results: A plot of the standard deviation of image pixel values versus the subtracted scatter value shows that the image structure noise reaches a minimum before going up again as the scatter value is increased. This minimum corresponds to a minimization of the grid‐line artifacts as demonstrated in line profile plots obtained through each of the images perpendicular to the grid lines. Artifact‐free images of the artery block were obtained with the optimal scatter value obtained by this iterative approach. Conclusion: Residual scatter subtraction can provide improved grid‐line artifact elimination when using the flat‐field with grid “subtraction” technique. The standard deviation of image pixel values can be used to determine the optimal scatter value to subtract to obtain a minimization of grid line artifacts with high resolution x‐ray imaging detectors. This study was supported by NIH Grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp.

Purpose: A method to reduce noise resulting from the use of higher resolution x‐ray detectors being developed to meet the demands of image guided vascular interventions is demonstrated. Methods: New direct detectors based on amorphous Se can have MTFs that remain high even at their Nyquist frequency. Since such detectors can be made with smaller pixels than may be required for even the high resolution requirements of many neurovascular applications, the resulting over‐sampled images can be convolved with various functions to lower the noise. The effect on resolution can then be compared with a simple pixel binning. The general method proposed by Cunningham et al as the apodized‐aperture pixel (AAP) design was compared with the Result for various simple 1D convolution spread functions with the effects on total noise and MTF compared to that of the binning case for a 25 μm aSe CMOS detector's MTF published by the University of Waterloo group lead by KS Karim. Results: Assuming a white noise image, various convolution kernels resulted in similar reductions of total standard deviation. Detailed comparisons were made with the simple the 2x binning case. While reducing noise, the over‐sampling convolution method using simple convolution low pass filters did not show advantage over 2x binning with regard to modifying the MTF; however, significant improvement was evidenced for the more complex sinc function used in the AAP design. Conclusion: As higher resolution detectors are being developed to meet the increasing demands for improved images to guide finer vascular interventions, use of super‐sampled aSe detectors where resolution is maintained with reduced noise may well fill this requirement. Partial support from NIH Grant R01EB002873 and Toshiba Medical Systems Equipment Grant

Scatter is one of the most important factors effecting image quality in radiography. One of the best scatter reduction methods in dynamic imaging is an anti-scatter grid. However, when used with high resolution imaging detectors these grids may leave grid-line artifacts with increasing severity as detector resolution improves. The presence of such artifacts can mask important details in the image and degrade image quality. We have previously demonstrated that, in order to remove these artifacts, one must first subtract the residual scatter that penetrates through the grid followed by dividing out a reference grid image; however, this correction must be done fast so that corrected images can be provided in real-time to clinicians. In this study, a standard stationary Smit-Rontgen x-ray grid (line density – 70 lines/cm, grid ratio – 13:1) was used with a high-resolution CMOS detector, the Dexela 1207 (pixel size – 75 micron) to image anthropomorphic head phantoms. For a 15 × 15 cm field-of-view (FOV), scatter profiles of the anthropomorphic head phantoms were estimated then iteratively modified to minimize the structured noise due to the varying grid-line artifacts across the FOV. Images of the head phantoms taken with the grid, before and after the corrections, were compared, demonstrating almost total elimination of the artifact over the full FOV. This correction is done fast using Graphics Processing Units (GPUs), with 7–8 iterations and total time taken to obtain the corrected image of only 87 ms, hence, demonstrating the virtually real-time implementation of the grid-artifact correction technique.