Cone-Beam Micro-CT System Based on LabVIEW Software

Ionita, Ciprian N.; Hoffmann, Kenneth R.; Bednarek, Daniel R.; Chityala, Ravishankar; Rudin, Stephen

doi:10.1007/s10278-007-9024-9

Cited by 33 publications

(25 citation statements)

References 14 publications

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“…We used a custom built micro-CT system [25] as shown in Figure (2). The system consists of a high resolution micro angiographic fluoroscope (MAF) detector [26] developed in our lab and a micro-focus Ultrabright Oxford x-ray tube with XYZ rotary stage for the sample mounting purpose.…”

Section: Methodsmentioning

confidence: 99%

Micro-computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model

et al. 2015

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High-resolution 3D bone-tissue structure measurements may provide information critical to the understanding of the bone regeneration processes and to the bone strength assessment. Tissue engineering studies rely on such nondestructive measurements to monitor bone graft regeneration area. In this study, we measured bone yield, fractal dimension and trabecular thickness through micro-CT slices for different grafts and controls. Eight canines underwent surgery to remove a bone volume (defect) in the canine’s jaw at a total of 44 different locations. We kept 11 defects empty for control and filled the remaining ones with three regenerative materials; NanoGen (NG), a FDA-approved material (n=11), a novel NanoCalcium Sulfate (NCS) material (n=11) and NCS alginate (NCS+alg) material (n=11). After a minimum of four and eight weeks, the canines were sacrificed and the jaw samples were extracted. We used a custom-built micro-CT system to acquire the data volume and developed software to measure the bone yield, fractal dimension and trabecular thickness. The software used a segmentation algorithm based on histograms derived from volumes of interest indicated by the operator. Using bone yield and fractal dimension as indices we are able to differentiate between the control and regenerative material (p<0.005). Regenerative material NCS showed an average 63.15% bone yield improvement over the control sample, NCS+alg showed 55.55% and NanoGen showed 37.5%. The bone regeneration process and quality of bone were dependent upon the position of defect and time period of healing. This study presents one of the first quantitative comparisons using non-destructive Micro-CT analysis for bone regenerative material in a large animal with a critical defect model. Our results indicate that Micro-CT measurement could be used to monitor in-vivo bone regeneration studies for greater regenerative process understanding.

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Section: Methodsmentioning

confidence: 99%

Micro-computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model

et al. 2015

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“…The first plane will be mostly trabecular bone requiring high resolution to properly visualize, and the second plane will be made up of cortical bone. Image acquisition was carried out using tube voltage of 60 kVp and wattage of 40 W with our micro-CT unit 14 . Exposure time was set to 1000 ms per projection, and 0.5 mm aluminum was placed in the beam.…”

Section: Methodsmentioning

confidence: 99%

Use of a CMOS-based micro-CT system to validate a novel ring artifact correction algorithm on low-dose image data

Podgorsak

Nagesh

Bednarek

et al. 2018

Medical Imaging 2018: Physics of Medical Imaging

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The imaging of objects using high-resolution detectors coupled to CT systems may be made challenging due to the presence of ring artifacts in the reconstructed data. Not only are the artifacts qualitatilvely distracting, they reduce the SNR of the reconstructed data and may lead to a reduction in the clinical utility of the image data. To address these challenges, we introduce a multistep algorithm that greatly reduces the impact of the ring artifacts on the reconstructed data through image processing in the sinogram space. First, for a single row of detectors corresponding to one slice, we compute the mean of every detector element in the row across all projection view angles and place the reciprocal values in a vector with length equal to the number of detector elements in a row. This vector is then multiplied with each detector element value for each projection view angle, obtaining a normalized or corrected sinogram. This sinogram is subtracted from the original uncorrected sinogram of the slice to obtain a difference map, which is then blurred with a median filter along the row direction. This blurred difference map is summed back to the corrected sinogram, to obtain the final sinogram, which can be back projected to obtain an axial slice of the scanned object, with a greatly reduced presence of ring artifacts. This process is done for each detector row corresponding to each slice. The performance of this algorithm was assessed using images of a mouse femur. These images were acquired using a micro-CT system coupled to a high-resolution CMOS detector. We found that the use of this algorithm led to an increase in SNR and a more uniform line-profile, as a result of the reduction in the presence of the ring artifacts.

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“…A projection image of the model prior to the addition of the contrast agent can be found in Figure 2. Image data acquisition of this phantom was performed with our in-house developed micro-CT system 11 coupled to a 49.5 μm CMOS detector made by Teledyne DALSA. As this is a dual-energy method, two consecutive scans of the object were performed, with care taken not to move the object at all between the two to ensure good registration.…”

Section: Methodsmentioning

confidence: 99%

Use of material decomposition in the context of neurovascular intervention using standard flat panel and a high-resolution CMOS detector

Podgorsak

Venkataraman

Nagesh

et al. 2018

Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging

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The imaging of endovascular devices during neurovascular procedures such as the coiling of aneurysms guided with CBCT imaging may be challenging due to the presence of highly attenuating materials such as platinum in the coil and stent marker, nickel-titanium in the stent, iodine in the contrast agent, and tantalum in the embolization agent. The use of dual-energy imaging followed by a basis material decomposition image processing-scheme may improve the feature separation and recognition. Two sets of testing were performed to validate this concept. The first trial was the acquisition of dual-energy micro-CBCT data of a 3D-printed simple aneurysm model using a 49.5 μm pixel size CMOS detector (Teledyne DALSA, Waterloo, ON.). Two sets of projection data were acquired using beam energies of 35 kVp and 70 kVp. Axial slices were reconstructed and used to carry out the material decomposition processing. The second trial was the acquisition of dual-energy CBCT images of a RS-240T angiographic head phantom (Radiology Support Devices Inc., CA.) with an iodine vascular insert using a Toshiba Infinix BiPlane C-arm system coupled to a flat panel detector. Two sets of image data were acquired using beam energies of 80 kVp and 120 kVp. Following image reconstruction, slices of the phantom were decomposed using the same processing as previously. The resulting image data over both trials indicate that the decomposition process was successful in separating the kinds of materials commonly used during a neurovascular intervention, such as platinum, cobalt-chromium, and iodine. The normalized root mean square error metric was used to quantitatively assess this. This indicates a basis for future more clinically relevant testing of our methods.

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Cone-Beam Micro-CT System Based on LabVIEW Software

Cited by 33 publications

References 14 publications

Micro-computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model

Micro-computed tomography (CT) based assessment of dental regenerative therapy in the canine mandible model

Use of a CMOS-based micro-CT system to validate a novel ring artifact correction algorithm on low-dose image data

Use of material decomposition in the context of neurovascular intervention using standard flat panel and a high-resolution CMOS detector

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