Using anti-scatter grids with high-resolution imaging detectors could result in grid-line artifacts, with increasing severity as detector resolution improves. Grid-line mask subtraction can result in residual artifacts that are due to residual scatter penetrating the grid and not subtracted. By subtracting this residual scatter, the grid artifacts can be minimized. In the previous works, an initial residual-scatter estimate was derived by placing lead markers on a test object; however, any change in the object geometry requires a new scatter estimate. Such a method is impractical to implement during a clinical procedure. In this work, we present a new method to derive the initial scatter estimate to eliminate grid-line artifacts during a procedure. A standard stationary Smit-Roentgen x-ray grid (line density - 70 lines/cm, grid ratio - 13:1) was used with a high-resolution CMOS detector (Dexela Model 1207, pixel size - 75 μm) to image an anthropomorphic head phantom. The initial scatter estimate was derived from the image itself and the grid artifacts were eliminated using recursive correction estimation; this result was compared to that with the estimate derived from placing lead markers on the phantom. In both cases, the contrast-to-noise ratio (CNR) was improved compared to the original image with grid artifacts. Percentage differences in CNR’s for three regions between the images corrected with the two estimates were less than 5%. With the new method no a priori scatter distribution profiles are needed, eliminating the need to have libraries of pre-calculated scatter profiles and making the implementation more clinically practical.
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 x 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.
Small pixel high resolution direct x-ray detectors have the advantage of higher spatial sampling and decreased blurring characteristic. The limiting factors for such systems becomes the degradation due to the focal spot size. One solution is a smaller focal spot; however, this can limit the output of the x-ray tube. Here a software solution of deconvolving with an estimated focal spot blur is presented. To simulate images from a direct detector affected with focal-spot blur, first a set of high-resolution stent images (FRED from Microvention, Inc., Tustin, CA) were acquired using a 75μm pixel size Dexela-Perkin-Elmer detector and frame averaged to reduce quantum noise. Then the averaged image was blurred with a known Gaussian blur. To add noise to the blurred image a flat-field image was multiplied with the blurred image. Both the ideal and the noisy-blurred images were then deconvolved with the known Gaussian function using either threshold-based inverse filtering or Weiner deconvolution. The blur in the ideal image was removed and the details were recovered successfully. However, the inverse filtering deconvolution process is extremely susceptible to noise. The Weiner deconvolution process was able to recover more of the details of the stent from the noisy-blurred image, but for noisier images, stent details are still lost in the recovery process.
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 x 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, antiscatter 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 Rӧntgen 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 x 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.
Endovascular image-guided intervention (EIGI) has become the primary interventional therapy for the most
widespread vascular diseases. These procedures involve the insertion of a catheter into the femoral artery, which is
then threaded under fluoroscopic guidance to the site of the pathology to be treated. Flat Panel Detectors (FPDs) are
normally used for EIGIs; however, once the catheter is guided to the pathological site, high-resolution imaging
capabilities can be used for accurately guiding a successful endovascular treatment. The Micro-Angiographic
Fluoroscope (MAF) detector provides needed high-resolution, high-sensitivity, and real-time imaging capabilities.
An experimental MAF enabled with a Control, Acquisition, Processing, Image Display and Storage (CAPIDS)
system was installed and aligned on a detector changer attached to the C-arm of a clinical angiographic unit. The
CAPIDS system was developed and implemented using LabVIEW software and provides a user-friendly interface
that enables control of several clinical radiographic imaging modes of the MAF including: fluoroscopy, roadmap,
radiography, and digital-subtraction-angiography (DSA). Using the automatic controls, the MAF detector can be
moved to the deployed position, in front of a standard FPD, whenever higher resolution is needed during
angiographic or interventional vascular imaging procedures. To minimize any possible negative impact to image
guidance with the two detector systems, it is essential to have a well-designed workflow that enables smooth
deployment of the MAF at critical stages of clinical procedures. For the ultimate success of this new imaging
capability, a clear understanding of the workflow design is essential. This presentation provides a detailed description
and demonstration of such a workflow design.
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