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Flat panel ---nihms864608

M
Maria Vergakh

This document summarizes a study that estimated and removed scatter and anti-scatter grid line artifacts from images of anthropomorphic head phantoms taken with a high resolution detector and stationary anti-scatter grid. Scatter profiles were estimated by imaging the phantoms with lead markers and interpolating grayscale values under the markers. Iteratively modifying the scatter profiles minimized structured noise across the field of view, almost totally eliminating grid line artifacts. Images before and after correction showed improved contrast and contrast-to-noise ratio, demonstrating that computational tools can correct for grid artifacts even in dynamic imaging sequences.

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Scatter estimation and removal of anti-scatter grid-line artifacts from anthropomorphic head phantom images taken with a high resolution image detector R. Rana, A. Jain, A. Shankar, D.R. Bednarek, and S. Rudin Toshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214 Abstract 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. Keywords high resolution detector; CMOS detector; x-ray imaging; anti-scatter grid; grid artifacts; scatter estimation; anthropomorphic head phantom; iterative artifact removal 1. INTRODUCTION In digital radiographic imaging, the image quality is degraded substantially by the scatter produced when the primary beam passes through an object. Different techniques such as the use of air-gaps1, scanning beams2, collimation, moving grids3 and stationary grids may be implemented to control the amount of scatter. Due to its compact design and simplicity compared to scanning beams or moving grids, stationary grids have usually proved to be the most practical choice for fluoroscopy. The grid enables adequate control of scatter without HHS Public Access Author manuscript Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Published in final edited form as: Proc SPIE Int Soc Opt Eng. 2016 February 27; 9783: . doi:10.1117/12.2216833. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
increasing geometric un-sharpness as in the case of air-gap techniques and hence they are widely used in projection x-ray radiography to reduce scatter radiation and improve image contrast. High resolution capabilities are also essential for an efficient, accurate, and successful endovascular interventional procedure4. However, when grids are used with these high resolution imaging detectors, the images contain a fixed-structure pattern noise or grid line artifacts and moiré patterns5. When these anti-scatter grids are used with a standard FPD, the grid lines are not very apparent because of the lower spatial resolution of the detector, which results in an averaging or blurring of the lines. However, for high resolution detectors, this fixed- pattern noise grid artifact must be removed from the images before being acceptable for clinical use. Grid-line removal could be done by log subtracting a mask containing the fixed pattern grid- line artifact; however residual scatter prevents complete cancellation of the pattern. The scatter component must thus be estimated and linearly subtracted first. The purpose of this work is to estimate the scatter distribution of complex realistic structured images where the amount of scatter can vary across the FOV so that the method of using the flat field obtained with the grid can be used to remove the anti-scatter grid-line artifacts in complex images, such as obtained during clinical interventions. 2. METHOD AND MATERIALS In this study in the set-up shown in Figure 1, we used a stationary Smit-Rӧntgen x-ray grid with a high resolution Dexela 1207 CMOS X-ray detector (pixel size 75 μm and sensitivity area 11.5cm × 6.5cm) (Fig. 2) to image anthropomorphic head phantoms: SK-150, The Phantom Laboratory, NY (Fig 3) and RS-240T, Radiology Support Devices Inc., CA (Fig. 4). Studies previously reported by us involved a simulated artery block phantom with a uniform frontal head equivalent phantom used as the scattering source to investigate the effectiveness of the method to remove the anti-scatter grid-line artifacts when a grid is used with a Flat Panel Detector (FPD) and high resolution CMOS detector6, 7. Grid lines were quite prominent when anthropomorphic head phantoms, SK-150 and RS-240T, were imaged with the high resolution CMOS detector with grid placed in front of the detector. Dividing by the flat-field image obtained with the grid does not effectively remove those grid-line artifacts because there is residual scatter that is additive while primary x-ray attenuation is a multiplicative factor. Hence, it is important to estimate and subtract the scatter in the image before dividing by the flat-field image. Scatter Estimation and Image Corrections In order to estimate this residual scatter, we placed round lead markers (1 mm thick with 3 mm diameter) under the SK-150 anthropomorphic head phantom at different locations and imaged it using the high resolution CMOS detector with a grid placed in front of the detector. Theoretically, there should not be any signal on the image under the lead markers Rana et al. Page 2 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
as these markers are thick enough to block all the incident x-rays. Hence, if any signal under the lead markers is observed, that is nothing but scatter. Grayscale values under all the lead markers were obtained at different location of the image. Since scatter has a very low spatial frequency distribution, these grayscale values under the lead markers were interpolated between markers to get an estimated scatter profile over the whole image. This estimated scatter profile is taken as the starting point for the iterative correction process. In the iteration process of estimating the scatter, the image to be corrected and the estimated scatter profile is divided into 25 small parts. Then each part of the image is corrected individually by iteratively varying the scatter value in the respective section of the scatter profile, to minimize the standard deviation of the grayscale values in that part of the image. In the previous study, we showed that as the grid lines (structure pattern) are removed from the image, the standard deviation of pixel values in the image also goes down8. Once all the parts are corrected, they are combined back to form the corrected original image. Approximately, 8–9 iterations were required to get the corrected image and the time taken was approximately 0.7 seconds per iteration. However, by using powerful computing systems and parallel programming techniques, the iteration time can be reduced a lot and hence this method can be used effectively with dynamic and changing fields such as used in neuro-endovascular image-guided interventional procedures. In order to further evaluate the effectiveness of this method, we corrected the images of an RS-240T anthropomorphic head phantom taken with the high resolution CMOS detector with grid in place. For correcting these images of the RS-240T phantom, we did not obtain the separate scatter profile by placing lead under the RS-240T phantom, but rather used the already estimated scatter profile (the one we obtained by placing lead in the beam for SK-150 anthropomorphic head phantom) as the starting point for the iteration method. Once again, we observed that the grid pattern was removed quite successfully, establishing the point that only one estimation of the scatter profile is needed and then the same profile can be used successfully as the starting point of iteration method for different heads. A total of 9 iteration were required to get the corrected image of second head phantom. The grid used in this study is the standard grid presently used for the FPD. The following Table 1 shows the relevant specifications of the grid: The images were taken in three different situations, explained below: 1. Table with grid (Grid mask image): We started first by “Table with grid” image acquisition. We kept the frontal head phantom (with the uniform section of the artery block inserted) on the x-ray tube (in order to keep filtration of the x-ray beam consistent). The grid is placed in the front of the CMOS detector and patient table is in the beam. 2. Object with grid (Image to be corrected): Second set of images taken were “Object with grid”. In this case, we carefully removed the frontal head phantom from the x-ray tube and placed one of the anthropomorphic head phantoms in the beam. Rana et al. Page 3 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
3. Object without grid: Then we took “Object without grid” images for the comparison purposes. In this case, we carefully removed the grid from the front of the CMOS detector keeping the rest of the set-up exactly the same as “Object with grid”. Exposure parameters used for imaging were 100 kVp, 100 mA and 12 ms, and they were kept the same for all acquisitions. Hence, all the exposures were the same in all the images, with or without the grid. The FOV used was 15 cm × 15 cm at the image receptor. 3. RESULTS AND DISCUSSION Fig 5 shows the image of the SK-150 anthropomorphic head phantom imaged with the FPD detector. This phantom shows the bone structure of the head. The dotted region shows the portion of the RS-240T head phantom which is imaged by the smaller FOV of the CMOS detector as shown in Fig 6. This region is around the base of the skull and the Circle of Willis is behind it. Grid lines were quite prominent when the anthropomorphic head phantoms, SK-150 and RS-240T, were imaged with the high resolution CMOS detector with grid placed in front of the detector (Fig 6). However, after following the earlier mentioned method, we successfully removed the residual grid lines. Fig 6 shows the image of the SK-150 anthropomorphic head phantom obtained with the high resolution CMOS detector, with grid placed in front of the detector. In order to show the effectiveness of the correction method, we zoomed in into three different regions of Fig. 6 and show them separately in Figs. 7, 8, 9 and 10. We tried to choose those regions of the image in which the grayscale value is varying throughout the region, so that the effectiveness of the method of removing the grid-line artifacts can be tested in those portions of the image where there are a lot of anatomical features/details. We have compared the following four cases in the zoomed regions. 1. Object with grid. 2. Object with grid: Table and Grid correction – In this case, we divided the “Object with grid” image by the “Grid reference image”. No scatter is subtracted in this case. 3. Object with grid: Table, Grid and Scatter correction – In this case, we first subtracted the scatter (Fig. 7) from the “Object with grid” image, before dividing it by the “Grid reference image”. 4. Object without grid. We also calculated the contrast and contrast–to-noise ratio (CNR) in the zoomed-in images for quantitative comparison purposes using the following equations: Rana et al. Page 4 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
In order to calculate the contrast and CNR, we chose two regions in the image as ‘signal’ and ‘background’. A rectangular box (7 pixels × 9 pixels) was selected in small darker regions to serve as ‘signal’ and the same size box was selected in a somewhat lighter region close by as ‘background’. The solid box and dotted box represent the signal region and the background region respectively in the images of Figs. 8, 9, and 10. The Contrast and CNR is then calculated and compared in the same regions for all the above mentioned four cases. We observed that the improvement in contrast in all the images is quite large as compared to the respective CNR improvement. It is mainly because the exposure parameters for all the images were kept the same, irrespective of whether grid is used or not. Without the grid we get more scatter. However, when the grid is used, we not only reduce the scatter and increase structures noise but also increase quantum noise because of the fewer primary photons that can get through the grid. Fig. 11 shows the image of the RS-240 anthropomorphic head phantom imaged taken with the FPD detector. This phantom shows the iodine-filled vessels in the brain. Some of the important arteries like the Anterior Cerebral Artery (ACA), Middle Cerebral Artery (MCA), Internal Carotid Artery (ICA) and Petro Cavernous Artery are identified in Fig. 11. The dotted region shows the portion of the RS-240T head phantom which is imaged by the CMOS detector as shown in Fig. 12. Fig. 12 shows the image of the RS-240T anthropomorphic head phantom imaged with the CMOS detector with the grid in place. Figs. 13, 14 and 15 show the zoomed images of three different regions in the image. Fig 13 shows the portion of Internal Carotid artery. Fig 14 focuses on portion of the petro cavernous artery. Fig 15 shows the bone of the nose. 4. CONCLUSIONS We demonstrated that the images of anthropomorphic head phantoms taken with a grid using a high resolution CMOS detector can be corrected for anti-scatter grid line artifacts if we accurately estimate the scatter distribution present across the image. We estimated the scatter iteratively for the complex images of head phantoms by determining the scatter value providing a minimum pixel variance in selected regions in the image when the grid- correction method (i.e. division by the reference uniform field grid image) was used. We demonstrated an improvement in contrast and CNR of the images taken with the grid and corrected for the anti-scatter grid pattern, as compared to the images taken without a grid. Thus, with the use of the described method and advance computational tools, we should be able to correct the images for anti-scatter grid-line artifacts, even during dynamic sequences such as used in neuro-endovascular image-guided interventional procedures. Acknowledgments This study was supported in part by NIH Grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp. Rana et al. Page 5 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
References 1. Neitzel U. Grids or air gaps for scatter reduction in digital radiography: a model calculation. Medical physics. 1992; 19(2):475–481. http://www.ncbi.nlm.nih.gov/pubmed/1584148. [PubMed: 1584148] 2. Barnes GT. Contrast and scatter in x-ray imaging. Radiographics : a review publication of the Radiological Society of North America Inc. 1991; 11(2):307–323. http://www.ncbi.nlm.nih.gov/ pubmed/2028065. 3. Bednarek DR, Rudin S, Wong R. Artifacts produced by moving grids. Radiology. 1983; 147(1):255– 258. http://www.ncbi.nlm.nih.gov/pubmed/6828740. [PubMed: 6828740] 4. Rudin S, Bednarek DR, Hoffman KR. Endovascular image-guided interventions (EIGIs). Med Phys. 2008; 35(1):301–309. http://www.pubmedcentral.gov/articlerender.fcgi?artid=2669303. [PubMed: 18293585] 5. Gauntt DM, Barnes GT. Grid line artifact formation: A comprehensive theory. Medical physics. 2006; 33(6):1668–1677. http://www.ncbi.nlm.nih.gov/pubmed/16872074. [PubMed: 16872074] 6. Singh, V., Jain, A., Bednarek, DR., Rudin, S. Limitations of anti-scatter grids when used with high resolution image detectors. Proceedings SPIE (Medical Imaging). 2014. http:// www.ncbi.nlm.nih.gov/pmc/articles/PMC4189125/ 7. Rana R, Singh V, Jain A, Bednarek DR, Rudin S. Anti-scatter grid artifact elimination for high resolution x-ray imaging CMOS detectors. Proceedings SPIE (Medical Imaging). 2015 8. Rana R, Bednarek DR, Rudin S. Grid-line artifact minimization for high resolution detectors using iterative residual scatter corrections. Medical Physics. 2015; 42(6):3695. http://scitation.aip.org/ content/aapm/journal/medphys/42/6/10.1118/1.4926090. Rana et al. Page 6 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 1. Rana et al. Page 7 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 2. External view of CMOS detector Rana et al. Page 8 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 3. SK-150 Rana et al. Page 9 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 4. RS-240T Rana et al. Page 10 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 5. SK-150 anthropomorphic head phantom imaged with the FPD. The dotted region shows the portion of the head phantom imaged by the CMOS detector as shown in Fig 6. Rana et al. Page 11 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 6. SK-150 phantom imaged with grid attached to CMOS detector. Rana et al. Page 12 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 7. Final scatter distribution that was subtracted from Fig 6 to remove the residual anti-scatter grid lines (brighter indicates higher scatter). Rana et al. Page 13 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 8. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 14 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 9. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 15 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 10. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 16 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 11. RS-240T anthropomorphic head phantom imaged with the FPD. The dotted region shows the portion of the head phantom imaged by the CMOS detector as shown in Fig 12. Rana et al. Page 17 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 12. RS-240T phantom imaged with the grid attached to the CMOS detector Rana et al. Page 18 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 13. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 19 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 14. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 20 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Fig 15. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 21 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Author Manuscript Author Manuscript Author Manuscript Author Manuscript Rana et al. Page 22 Table 1 Grid specifications Type number 989601061091 Line rate 70 line/cm Grid ratio 13 : 1 Absorption material Lead, 27.5 μ Interspace material Fiber Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23.

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Flat panel ---nihms864608

  • 1. Scatter estimation and removal of anti-scatter grid-line artifacts from anthropomorphic head phantom images taken with a high resolution image detector R. Rana, A. Jain, A. Shankar, D.R. Bednarek, and S. Rudin Toshiba Stroke and Vascular Research Center, University at Buffalo, Buffalo, NY 14214 Abstract 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. Keywords high resolution detector; CMOS detector; x-ray imaging; anti-scatter grid; grid artifacts; scatter estimation; anthropomorphic head phantom; iterative artifact removal 1. INTRODUCTION In digital radiographic imaging, the image quality is degraded substantially by the scatter produced when the primary beam passes through an object. Different techniques such as the use of air-gaps1, scanning beams2, collimation, moving grids3 and stationary grids may be implemented to control the amount of scatter. Due to its compact design and simplicity compared to scanning beams or moving grids, stationary grids have usually proved to be the most practical choice for fluoroscopy. The grid enables adequate control of scatter without HHS Public Access Author manuscript Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Published in final edited form as: Proc SPIE Int Soc Opt Eng. 2016 February 27; 9783: . doi:10.1117/12.2216833. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 2. increasing geometric un-sharpness as in the case of air-gap techniques and hence they are widely used in projection x-ray radiography to reduce scatter radiation and improve image contrast. High resolution capabilities are also essential for an efficient, accurate, and successful endovascular interventional procedure4. However, when grids are used with these high resolution imaging detectors, the images contain a fixed-structure pattern noise or grid line artifacts and moiré patterns5. When these anti-scatter grids are used with a standard FPD, the grid lines are not very apparent because of the lower spatial resolution of the detector, which results in an averaging or blurring of the lines. However, for high resolution detectors, this fixed- pattern noise grid artifact must be removed from the images before being acceptable for clinical use. Grid-line removal could be done by log subtracting a mask containing the fixed pattern grid- line artifact; however residual scatter prevents complete cancellation of the pattern. The scatter component must thus be estimated and linearly subtracted first. The purpose of this work is to estimate the scatter distribution of complex realistic structured images where the amount of scatter can vary across the FOV so that the method of using the flat field obtained with the grid can be used to remove the anti-scatter grid-line artifacts in complex images, such as obtained during clinical interventions. 2. METHOD AND MATERIALS In this study in the set-up shown in Figure 1, we used a stationary Smit-Rӧntgen x-ray grid with a high resolution Dexela 1207 CMOS X-ray detector (pixel size 75 μm and sensitivity area 11.5cm × 6.5cm) (Fig. 2) to image anthropomorphic head phantoms: SK-150, The Phantom Laboratory, NY (Fig 3) and RS-240T, Radiology Support Devices Inc., CA (Fig. 4). Studies previously reported by us involved a simulated artery block phantom with a uniform frontal head equivalent phantom used as the scattering source to investigate the effectiveness of the method to remove the anti-scatter grid-line artifacts when a grid is used with a Flat Panel Detector (FPD) and high resolution CMOS detector6, 7. Grid lines were quite prominent when anthropomorphic head phantoms, SK-150 and RS-240T, were imaged with the high resolution CMOS detector with grid placed in front of the detector. Dividing by the flat-field image obtained with the grid does not effectively remove those grid-line artifacts because there is residual scatter that is additive while primary x-ray attenuation is a multiplicative factor. Hence, it is important to estimate and subtract the scatter in the image before dividing by the flat-field image. Scatter Estimation and Image Corrections In order to estimate this residual scatter, we placed round lead markers (1 mm thick with 3 mm diameter) under the SK-150 anthropomorphic head phantom at different locations and imaged it using the high resolution CMOS detector with a grid placed in front of the detector. Theoretically, there should not be any signal on the image under the lead markers Rana et al. Page 2 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 3. as these markers are thick enough to block all the incident x-rays. Hence, if any signal under the lead markers is observed, that is nothing but scatter. Grayscale values under all the lead markers were obtained at different location of the image. Since scatter has a very low spatial frequency distribution, these grayscale values under the lead markers were interpolated between markers to get an estimated scatter profile over the whole image. This estimated scatter profile is taken as the starting point for the iterative correction process. In the iteration process of estimating the scatter, the image to be corrected and the estimated scatter profile is divided into 25 small parts. Then each part of the image is corrected individually by iteratively varying the scatter value in the respective section of the scatter profile, to minimize the standard deviation of the grayscale values in that part of the image. In the previous study, we showed that as the grid lines (structure pattern) are removed from the image, the standard deviation of pixel values in the image also goes down8. Once all the parts are corrected, they are combined back to form the corrected original image. Approximately, 8–9 iterations were required to get the corrected image and the time taken was approximately 0.7 seconds per iteration. However, by using powerful computing systems and parallel programming techniques, the iteration time can be reduced a lot and hence this method can be used effectively with dynamic and changing fields such as used in neuro-endovascular image-guided interventional procedures. In order to further evaluate the effectiveness of this method, we corrected the images of an RS-240T anthropomorphic head phantom taken with the high resolution CMOS detector with grid in place. For correcting these images of the RS-240T phantom, we did not obtain the separate scatter profile by placing lead under the RS-240T phantom, but rather used the already estimated scatter profile (the one we obtained by placing lead in the beam for SK-150 anthropomorphic head phantom) as the starting point for the iteration method. Once again, we observed that the grid pattern was removed quite successfully, establishing the point that only one estimation of the scatter profile is needed and then the same profile can be used successfully as the starting point of iteration method for different heads. A total of 9 iteration were required to get the corrected image of second head phantom. The grid used in this study is the standard grid presently used for the FPD. The following Table 1 shows the relevant specifications of the grid: The images were taken in three different situations, explained below: 1. Table with grid (Grid mask image): We started first by “Table with grid” image acquisition. We kept the frontal head phantom (with the uniform section of the artery block inserted) on the x-ray tube (in order to keep filtration of the x-ray beam consistent). The grid is placed in the front of the CMOS detector and patient table is in the beam. 2. Object with grid (Image to be corrected): Second set of images taken were “Object with grid”. In this case, we carefully removed the frontal head phantom from the x-ray tube and placed one of the anthropomorphic head phantoms in the beam. Rana et al. Page 3 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 4. 3. Object without grid: Then we took “Object without grid” images for the comparison purposes. In this case, we carefully removed the grid from the front of the CMOS detector keeping the rest of the set-up exactly the same as “Object with grid”. Exposure parameters used for imaging were 100 kVp, 100 mA and 12 ms, and they were kept the same for all acquisitions. Hence, all the exposures were the same in all the images, with or without the grid. The FOV used was 15 cm × 15 cm at the image receptor. 3. RESULTS AND DISCUSSION Fig 5 shows the image of the SK-150 anthropomorphic head phantom imaged with the FPD detector. This phantom shows the bone structure of the head. The dotted region shows the portion of the RS-240T head phantom which is imaged by the smaller FOV of the CMOS detector as shown in Fig 6. This region is around the base of the skull and the Circle of Willis is behind it. Grid lines were quite prominent when the anthropomorphic head phantoms, SK-150 and RS-240T, were imaged with the high resolution CMOS detector with grid placed in front of the detector (Fig 6). However, after following the earlier mentioned method, we successfully removed the residual grid lines. Fig 6 shows the image of the SK-150 anthropomorphic head phantom obtained with the high resolution CMOS detector, with grid placed in front of the detector. In order to show the effectiveness of the correction method, we zoomed in into three different regions of Fig. 6 and show them separately in Figs. 7, 8, 9 and 10. We tried to choose those regions of the image in which the grayscale value is varying throughout the region, so that the effectiveness of the method of removing the grid-line artifacts can be tested in those portions of the image where there are a lot of anatomical features/details. We have compared the following four cases in the zoomed regions. 1. Object with grid. 2. Object with grid: Table and Grid correction – In this case, we divided the “Object with grid” image by the “Grid reference image”. No scatter is subtracted in this case. 3. Object with grid: Table, Grid and Scatter correction – In this case, we first subtracted the scatter (Fig. 7) from the “Object with grid” image, before dividing it by the “Grid reference image”. 4. Object without grid. We also calculated the contrast and contrast–to-noise ratio (CNR) in the zoomed-in images for quantitative comparison purposes using the following equations: Rana et al. Page 4 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 5. In order to calculate the contrast and CNR, we chose two regions in the image as ‘signal’ and ‘background’. A rectangular box (7 pixels × 9 pixels) was selected in small darker regions to serve as ‘signal’ and the same size box was selected in a somewhat lighter region close by as ‘background’. The solid box and dotted box represent the signal region and the background region respectively in the images of Figs. 8, 9, and 10. The Contrast and CNR is then calculated and compared in the same regions for all the above mentioned four cases. We observed that the improvement in contrast in all the images is quite large as compared to the respective CNR improvement. It is mainly because the exposure parameters for all the images were kept the same, irrespective of whether grid is used or not. Without the grid we get more scatter. However, when the grid is used, we not only reduce the scatter and increase structures noise but also increase quantum noise because of the fewer primary photons that can get through the grid. Fig. 11 shows the image of the RS-240 anthropomorphic head phantom imaged taken with the FPD detector. This phantom shows the iodine-filled vessels in the brain. Some of the important arteries like the Anterior Cerebral Artery (ACA), Middle Cerebral Artery (MCA), Internal Carotid Artery (ICA) and Petro Cavernous Artery are identified in Fig. 11. The dotted region shows the portion of the RS-240T head phantom which is imaged by the CMOS detector as shown in Fig. 12. Fig. 12 shows the image of the RS-240T anthropomorphic head phantom imaged with the CMOS detector with the grid in place. Figs. 13, 14 and 15 show the zoomed images of three different regions in the image. Fig 13 shows the portion of Internal Carotid artery. Fig 14 focuses on portion of the petro cavernous artery. Fig 15 shows the bone of the nose. 4. CONCLUSIONS We demonstrated that the images of anthropomorphic head phantoms taken with a grid using a high resolution CMOS detector can be corrected for anti-scatter grid line artifacts if we accurately estimate the scatter distribution present across the image. We estimated the scatter iteratively for the complex images of head phantoms by determining the scatter value providing a minimum pixel variance in selected regions in the image when the grid- correction method (i.e. division by the reference uniform field grid image) was used. We demonstrated an improvement in contrast and CNR of the images taken with the grid and corrected for the anti-scatter grid pattern, as compared to the images taken without a grid. Thus, with the use of the described method and advance computational tools, we should be able to correct the images for anti-scatter grid-line artifacts, even during dynamic sequences such as used in neuro-endovascular image-guided interventional procedures. Acknowledgments This study was supported in part by NIH Grant R01EB002873 and an equipment grant from Toshiba Medical Systems Corp. Rana et al. Page 5 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 6. References 1. Neitzel U. Grids or air gaps for scatter reduction in digital radiography: a model calculation. Medical physics. 1992; 19(2):475–481. http://www.ncbi.nlm.nih.gov/pubmed/1584148. [PubMed: 1584148] 2. Barnes GT. Contrast and scatter in x-ray imaging. Radiographics : a review publication of the Radiological Society of North America Inc. 1991; 11(2):307–323. http://www.ncbi.nlm.nih.gov/ pubmed/2028065. 3. Bednarek DR, Rudin S, Wong R. Artifacts produced by moving grids. Radiology. 1983; 147(1):255– 258. http://www.ncbi.nlm.nih.gov/pubmed/6828740. [PubMed: 6828740] 4. Rudin S, Bednarek DR, Hoffman KR. Endovascular image-guided interventions (EIGIs). Med Phys. 2008; 35(1):301–309. http://www.pubmedcentral.gov/articlerender.fcgi?artid=2669303. [PubMed: 18293585] 5. Gauntt DM, Barnes GT. Grid line artifact formation: A comprehensive theory. Medical physics. 2006; 33(6):1668–1677. http://www.ncbi.nlm.nih.gov/pubmed/16872074. [PubMed: 16872074] 6. Singh, V., Jain, A., Bednarek, DR., Rudin, S. Limitations of anti-scatter grids when used with high resolution image detectors. Proceedings SPIE (Medical Imaging). 2014. http:// www.ncbi.nlm.nih.gov/pmc/articles/PMC4189125/ 7. Rana R, Singh V, Jain A, Bednarek DR, Rudin S. Anti-scatter grid artifact elimination for high resolution x-ray imaging CMOS detectors. Proceedings SPIE (Medical Imaging). 2015 8. Rana R, Bednarek DR, Rudin S. Grid-line artifact minimization for high resolution detectors using iterative residual scatter corrections. Medical Physics. 2015; 42(6):3695. http://scitation.aip.org/ content/aapm/journal/medphys/42/6/10.1118/1.4926090. Rana et al. Page 6 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 7. Fig 1. Rana et al. Page 7 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 8. Fig 2. External view of CMOS detector Rana et al. Page 8 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 9. Fig 3. SK-150 Rana et al. Page 9 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 10. Fig 4. RS-240T Rana et al. Page 10 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 11. Fig 5. SK-150 anthropomorphic head phantom imaged with the FPD. The dotted region shows the portion of the head phantom imaged by the CMOS detector as shown in Fig 6. Rana et al. Page 11 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 12. Fig 6. SK-150 phantom imaged with grid attached to CMOS detector. Rana et al. Page 12 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 13. Fig 7. Final scatter distribution that was subtracted from Fig 6 to remove the residual anti-scatter grid lines (brighter indicates higher scatter). Rana et al. Page 13 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 14. Fig 8. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 14 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 15. Fig 9. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 15 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 16. Fig 10. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 16 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 17. Fig 11. RS-240T anthropomorphic head phantom imaged with the FPD. The dotted region shows the portion of the head phantom imaged by the CMOS detector as shown in Fig 12. Rana et al. Page 17 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 18. Fig 12. RS-240T phantom imaged with the grid attached to the CMOS detector Rana et al. Page 18 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 19. Fig 13. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 19 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 20. Fig 14. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 20 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 21. Fig 15. (a) Object with grid, (b) Object with grid: Table and Grid corrected, (c) Object with grid – Table, Grid & Scatter corrected (d) Object without grid Rana et al. Page 21 Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
  • 22. Author Manuscript Author Manuscript Author Manuscript Author Manuscript Rana et al. Page 22 Table 1 Grid specifications Type number 989601061091 Line rate 70 line/cm Grid ratio 13 : 1 Absorption material Lead, 27.5 μ Interspace material Fiber Proc SPIE Int Soc Opt Eng. Author manuscript; available in PMC 2017 June 23.