Three-dimensional PSF characterization of circle-plus-arc cone-beam computed tomography

The three-dimensional (3D) imaging performance of a cone-beam computed tomography (CBCT) system can be quantitatively characterized by its 3D point spread function (PSF). To avoid the pitfalls associated with 3D PSF measurement through the use of a micro point phantom, we adopt an edge-based technique, which iteratively blurs a step edge into a spread edge with a Gaussian blurring kernel. In experiment, a small Teflon solid ball (diameter ~6mm) is used to provide step edges along the scanlines across the ball center, in terms of x-ray linear attenuation coefficient. Correspondingly, the spread edge profiles are extracted from the digital volume ball reconstructed by a CBCT system. From a spread edge profile, a step edge can be established by a rectification procedure (essentially an edge identification). A 1D PSF along a scanline is modeled as a Gaussian distribution, which is determined by iterative edge-blurring technique. The 1D PSFs on a cross section of the ball constitute a 2D PSF, and the 2D PSFs at three orthogonal cross sections are used to represent the 3D PSF at the position of the ball. By repositioning the ball phantom and repeating the procedure, we measured the 3D PSFs at 126 positions over half of the support space. Experiment shows that a CBCT system is of spatial variance and anisotropy in terms of FWHMs (full width at half maximum) of the blurring kernel. Both numerical and graphical presentations of PSF results are provided. As a result, the FWHM of the 3D PSF in our CBCT system varies in the range between 0.66 mm and 1.39 mm.

For cone-beam computed tomography (CBCT) systems, we propose a sphere phantom based method to estimate the full three-dimensional (3D) modulation transfer function (MTF). The FDK reconstruction of CBCT system in a local region was modeled by a triple convolution operator. Afterward, we calculated the directional projections of ideal and reconstructed sphere phantoms into a two-dimensional (2D) plane for multiple views. To estimate the projected 3D point spread function (PSF), we applied the 2D Richardson-Lucy deconvolution with Tikhonov-Miller (RL-TM). After estimating the projected 3D PSF from multiple views, the full 3D PSF was estimated by performing filtered backprojection. Then, the full 3D MTF was calculated by taking the modulus of the Fourier transform of the estimated 3D PSF. To validate the proposed method, we reconstructed sphere phantoms from simulation and experiment data. We simulated ideal 3D MTFs and compared them with the estimated 3D MTFs along the -, -, and -directions. The full-width at half-maximum (FWHM) and full-width at tenth-maximum (FWTM) values were compared between ideal and estimated 3D MTFs. The estimated 3D MTFs from both the simulation and experiment results show qualitative similarity in their shapes with the ideal 3D MTFs; FWHM and FWTM results quantitatively show that the proposed method provides reliable estimation performance. In particular, the estimated 3D MTF in a missing cone region was correctly matched with the corresponding ideal 3D MTF. In this work, we proposed a full 3D MTF estimation method for CBCT systems. Based on the results, we believe that the proposed method can be used to evaluate the spatial resolution performance of CBCT systems.

Cone Beam Computed Tomography (CBCT) has gained a broad acceptance in dentomaxillofacial imaging. Computed Tomography (CT) is another imaging modality for diagnosis and preoperative assessments of the head and neck region. Considering the increased radiation exposure and high cost of CT, this study sought to subjectively assess the image quality of CBCT and Multi Slice CT (MSCT). A dry human mandible was scanned by five CBCT systems (New Tom 3G, Scanora, CRANEX 3D, Promax and Galileos) and one MSCT system. Three independent oral and maxillofacial radiologists reviewed the CBCT and MSCT scans for the quality of 10 landmarks namely mental foramen, trabecular bone, Periodontal Ligament (PDL), dentin, incisive canal, mandibular canal, dental pulp, enamel, lamina dura and cortical bone using a five-point scale. Significant differences were found between MSCT and CBCT and among the five CBCT systems (p<0.05) in visualization of different anatomical structures. A fine structure such as the incisive canal was significantly less visible and more variable among the systems in comparison with other anatomical landmarks such as the mental foramen, mandibular canal, cortical bone, dental pulp, enamel and dentin (p<0.05). The Cranex 3D and Promax systems were superior to MSCT and all other CBCT systems in visualizing anatomical structures. The CBCT image quality was superior to that of MSCT even though some variability existed among different CBCT systems in visualizing fine structures. Considering the low radiation dose and high resolution, CBCT may be beneficial for dentomaxillofacial imaging.

The cone beam computed tomography (CBCT) guided small animal radiation research platform (SARRP) has been developed for focal tumor irradiation, allowing laboratory researchers to test basic biological hypotheses that can modify radiotherapy outcomes in ways that were not feasible previously. CBCT provides excellent bone to soft tissue contrast, but is incapable of differentiating tumors from surrounding soft tissue. Bioluminescence tomography (BLT), in contrast, allows direct visualization of even subpalpable tumors and quantitative evaluation of tumor response. Integration of BLT with CBCT offers complementary image information, with CBCT delineating anatomic structures and BLT differentiating luminescent tumors. This study is to develop a systematic method to calibrate an integrated CBCT and BLT imaging system which can be adopted onboard the SARRP to guide focal tumor irradiation. The integrated imaging system consists of CBCT, diffuse optical tomography (DOT), and BLT. The anatomy acquired from CBCT and optical properties acquired from DOT serve as a priori information for the subsequent BLT reconstruction. Phantoms were designed and procedures were developed to calibrate the CBCT, DOT/BLT, and the entire integrated system. Geometrical calibration was performed to calibrate the CBCT system. Flat field correction was performed to correct the nonuniform response of the optical imaging system. Absolute emittance calibration was performed to convert the camera readout to the emittance at the phantom or animal surface, which enabled the direct reconstruction of the bioluminescence source strength. Phantom and mouse imaging were performed to validate the calibration. All calibration procedures were successfully performed. Both CBCT of a thin wire and a euthanized mouse revealed no spatial artifact, validating the accuracy of the CBCT calibration. The absolute emittance calibration was validated with a 650 nm laser source, resulting in a 3.0% difference between simulated and measured signal. The calibration of the entire system was confirmed through the CBCT and BLT reconstruction of a bioluminescence source placed inside a tissue-simulating optical phantom. Using a spatial region constraint, the source position was reconstructed with less than 1 mm error and the source strength reconstructed with less than 24% error. A practical and systematic method has been developed to calibrate an integrated x-ray and optical tomography imaging system, including the respective CBCT and optical tomography system calibration and the geometrical calibration of the entire system. The method can be modified and adopted to calibrate CBCT and optical tomography systems that are operated independently or hybrid x-ray and optical tomography imaging systems.

The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The method increases localization accuracy by ~60% with compare to regular Gaussian fitting, and improves minimal resolvable distance between overlapping PSFs by ~50%. The algorithm was tested both on simulated data and experimentally. This work presets a novel use of the nonlinear image decomposition technique called K-factor that reshapes the three dimensional (3D) point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The experimentally obtained PSF of a Z-stack raw data that is acquired by a widefield microscope has a more elaborate shape that is given by the Gibson and Lanni model. This shape increases the computational complexity associated with the localization routine, when used in localization microscopy techniques. Furthermore, due to its nature, this PSF spreads over a larger volume, making the problem of overlapping emitters detection more pronounced. The ability to use Gaussian fitting with high accuracy on 3D data can facilitate the computational complexity, hence reduce the processing time required for the generation of the 3D superresolved image. In addition it allows the detection of overlapping PSFs and reduces the effects of the penetration of out of focus PSFs into in focused PSFs, therefore enables the increase in the activated fluorophore density by ~50%. The algorithm was tested both on simulated data and experimentally, where it yielded an increase in the localization accuracy by ~60% with compare to regular Gaussian fitting, and improved the minimal resolvable distance between overlapping PSFs by ~50%, making it extremely applicable to the field of 3D biomedical imaging,

BackgroundImage‐guided particle therapy (IGPT) has significantly advanced in recent years, particularly in the context of proton therapy. However, imaging solutions for carbon‐ion radiotherapy (C‐ion RT) remain limited.PurposeThis study introduces sliding‐gantry cone‐beam computed tomography (CBCT) and dual‐panel digital radiography (DR) systems, both mechanically independent of carbon‐ion delivery nozzles. We aim to evaluate the image quality metrics and verify the positioning accuracy of the imaging systems.MethodsImage quality was evaluated in terms of spatial resolution, low contrast resolution, image uniformity, and effective imaging area using a multi‐purpose imaging phantom, Catphan 700 phantom, and ImageJ software. The influences of planning computed tomography (CT) slice thicknesses (1–5 mm), radiation quality settings (90–130 kV), and registration algorithms (bony, grayscale, and fiducial marker registrations) on positioning accuracy were assessed using anthropomorphic head‐neck and thoracoabdominal phantom images. The clinical feasibility of both systems was validated in 22 enrolled patients.ResultsThe CBCT exhibited a lower in‐plane spatial resolution (2.50 line pairs per millimeter (lp/mm)) than DR (2.80 lp/mm). Spatial resolution of the CBCT system was measured at 0.90 lp/mm using the CTP 714 module of the Catphan 700 phantom. Both systems achieved a low contrast resolution of 2.30%. DR provided superior image uniformity (1.12%–1.40%) compared with CBCT (2.20%). The effective imaging areas were comparable between the CBCT and DR systems (99.30%–99.50%). Positioning accuracy varied with planning CT slice thicknesses, radiation quality settings, and registration algorithms, showing mean translation displacements ranging from 0.01 to 0.48 mm. CBCT achieved inter‐fraction translational positioning errors within 2 mm in 42.3% (22/52) of fractions and rotational positioning errors within 2° in 80.8% (42/52) of fractions, and DR achieved 33.8% (24/71) and 73.2% (52/71), respectively.ConclusionThe developed CBCT and DR systems achieved superior image quality and sub‐0.5 mm positioning accuracy. These findings support the clinical feasibility of integrating CBCT and DR imaging systems into the C‐ion RT workflow.

Three-dimensional images of confocal laser scanning microscopy suffer from a depth-variant blur, due to refractive index mismatch between the different mediums composing the system as well as the specimen, leading to optical aberrations. Our goal is to develop an image restoration method for 3D confocal microscopy taking into account the blur variation with depth. The difficulty is that optical aberrations depend on the refractive index of the biological specimen. The depth-variant blur function or the Point Spread Function (PSF) is thus different for each observation. A blind or semi-blind restoration method needs to be developed for this system. For that purpose, we use a previously developed algorithm for the joint estimation of the specimen function (original image) and the 3D PSF, the continuously depth-variant PSF is approximated by a convex combination of a set of space-invariant PSFs taken at different depths. We propose to add to that algorithm a pupil-phase constraint for the PSF estimation, given by the the optical instrument geometry. We thus define a blind estimation algorithm by minimizing a regularized criterion in which we integrate the Gerchberg-Saxton algorithm allowing to include these physical constraints. We show the efficiency of this method relying on some numerical tests.

Cone-beam computed tomography (CBCT) based upon large-area flat-panel imager (FPI) technology is a flexible and adaptable technology that offers large field-of-view (FOV), high spatial resolution, and soft-tissue imaging. The imaging performance of FPI-based cone-beam CT has been evaluated on a computer-controlled bench-top system using an early prototype FPI with a small FOV (20.5 X 20.5 cm<SUP>2</SUP>). These investigations demonstrate the potential of this exciting technology. In this report, imaging performance is evaluated using a production grade large-area FPI (41 X 41 cm<SUP>2</SUP>) for which the manufacturer has achieved a significant reduction in additive noise. This reduction in additive noise results in a substantial improvement in detective quantum efficiency (DQE) at low exposures. The spatial resolution over the increased FOV of the cone-beam CT system is evaluated by imaging a fine steel wire placed at various locations within the volume of reconstruction. The measured modulation transfer function (MTF) of the system demonstrates spatial frequency pass beyond 1 mm-1 (10% modulation) with a slight degradation at points off the source plane. In addition to investigations of imaging performance, progress has also been made in the integration of this technology with a medical linear accelerator for on-line image-guided radiation therapy. Unlike the bench-top system, this implementation must contend with significant geometric non-idealities caused by gravity-induced flex of the x-ray tube and FPI support assemblies. A method of characterizing and correcting these non-idealities has been developed. Images of an anthropomorphic head phantom qualitatively demonstrate the excellent spatial resolution and large FOV achievable with the cone-beam approach in the clinical implementation.

In image guided radiotherapy (IGRT), cone beam computed tomography (CBCT) is an important tool for patient positioning and verification before treatment. Therefore, the CBCT system has become an essential part and significant component of radiation therapy because it is a development that facilitates more accurate delivery of the prescribed dose to the treatment sites. However, the CBCT system uses ionizing radiation to acquire images for patient setup. Historically, the significance of this imaging dose has been overlooked as it is relatively small in quantity when compared to therapeutic doses used to patients for treatment purposes. In recent years, several works have been made to estimate the dose delivered from CBCT imaging using Monte Carlo simulations in phantoms and patients, thermoluminescence dosimetry (TLD) as well as a variety of other dosimetry methods. The aim of this chapter is to summarize the results from international literature concerning the additional imaging dose delivered to patients due to the usage of Cone Beam CT during radiation therapy, as well as to discuss the future work necessary in order to arrive at a clinically relevant personalized dose estimation protocol.

Cone-beam computed tomography (CBCT) is widely used for pre-treatment verification and patient setup in image-guided radiation therapy (IGRT). CBCT imaging is employed daily and several times per patient, resulting in potentially high cumulative imaging doses to healthy tissues that surround exposed target organs. Computed tomography dose index (CTDI) is the parameter used by CBCT equipment as indication of the radiation output to patients. This study aimed to increase the knowledge on the relation between CBCT organ doses and weighted CTDI (CTDIW) for a thorax scanning protocol. A CBCT system was modelled using the Monte Carlo (MC) radiation transport program MCNPX2.7.0. Simulation results were validated against half-value layer (HVL), axial beam profile, patient skin dose (PSD) and CTDI measurements. For organ dose calculations, a male voxel phantom ("Golem") was implemented with the CBCT scanner computational model. After a successful MC model validation with measurements, a systematic comparison was performed between organ doses (and their distribution) and CTDI dosimetry concepts [CTDIW and cumulative dose quantities f100(150) and [Formula: see text]]. The results obtained show that CBCT organ doses vary between 1.2 ± 0.1mGy and 3.3 ± 0.2mGy for organs located within the primary beam. It was also verified that CTDIW allows prediction of absorbed doses to tissues at distances of about 5cm from the isocentre of the CBCT system, whereas f100(150) allows prediction of organ doses at distances of about 10cm from the isocentre, independently from its location. This study demonstrates that these dosimetric concepts are suitable methods that easily allow a good approximation of the additional CBCT imaging doses during a typical lung cancer IGRT treatment.

Background:The accuracy of three-dimensional (3D) reconstructions from cone-beam computed tomography (CBCT) has been particularly important in dentistry, which will affect the effectiveness of diagnosis, treatment plan, and outcome in clinical practice. The aims of this study were to assess the linear, volumetric, and geometric accuracy of 3D reconstructions from CBCT and to investigate the influence of voxel size and CBCT system on the reconstructions results.Methods:Fifty teeth from 18 orthodontic patients were assigned to three groups as NewTom VG 0.15 mm group (NewTom VG; voxel size: 0.15 mm; n = 17), NewTom VG 0.30 mm group (NewTom VG; voxel size: 0.30 mm; n = 16), and VATECH DCTPRO 0.30 mm group (VATECH DCTPRO; voxel size: 0.30 mm; n = 17). The 3D reconstruction models of the teeth were segmented from CBCT data manually using Mimics 18.0 (Materialise Dental, Leuven, Belgium), and the extracted teeth were scanned by 3Shape optical scanner (3Shape A/S, Denmark). Linear and volumetric deviations were separately assessed by comparing the length and volume of the 3D reconstruction model with physical measurement by paired t-test. Geometric deviations were assessed by the root mean square value of the imposed 3D reconstruction and optical models by one-sample t-test. To assess the influence of voxel size and CBCT system on 3D reconstruction, analysis of variance (ANOVA) was used (α = 0.05).Results:The linear, volumetric, and geometric deviations were −0.03 ± 0.48 mm, −5.4 ± 2.8%, and 0.117 ± 0.018 mm for NewTom VG 0.15 mm group; −0.45 ± 0.42 mm, −4.5 ± 3.4%, and 0.116 ± 0.014 mm for NewTom VG 0.30 mm group; and −0.93 ± 0.40 mm, −4.8 ± 5.1%, and 0.194 ± 0.117 mm for VATECH DCTPRO 0.30 mm group, respectively. There were statistically significant differences between groups in terms of linear measurement (P < 0.001), but no significant difference in terms of volumetric measurement (P = 0.774). No statistically significant difference were found on geometric measurement between NewTom VG 0.15 mm and NewTom VG 0.30 mm groups (P = 0.999) while a significant difference was found between VATECH DCTPRO 0.30 mm and NewTom VG 0.30 mm groups (P = 0.006).Conclusions:The 3D reconstruction from CBCT data can achieve a high linear, volumetric, and geometric accuracy. Increasing voxel resolution from 0.30 to 0.15 mm does not result in increased accuracy of 3D tooth reconstruction while different systems can affect the accuracy.

ObjectivesThe aim of this study was to determine the diagnostic accuracy of cone beam computed tomography (CBCT) in the detection of approximal and occlusal noncavitated carious lesions.MethodsA total of 135 extracted human posterior teeth were used. They were radiographed using the following: conventional film (Kodak Insight), a digital system (PSP plates Digora Optime, Soredex), and a CBCT system (NewTom 3G, Quantitative Radiology). All the images were assessed by two independent observers twice. Receiver operating characteristic analysis (Az) was used.ResultsNewTom 3G 9″ CBCT was statistically inferior to conventional film and a digital system for the detection of approximal caries. NewTom 3G 9″ had significantly higher Az values than PSP plate (p < 0.05), but there were no statistically significant differences between the Az values for CBCT and film (p > 0.33) for occlusal surface caries.ConclusionThe diagnostic accuracy of all three tested radiographic systems is low, and it is necessary to use other methods to improve early caries detection.Clinical relevanceCBCT has found a wide application in different fields of dentistry. The report from a CBCT examination performed for any of these reasons should include all abnormal findings, and the detection of noncavitated caries lesions is especially important because it facilitates the use of noninvasive treatment.

Purpose:To present a cone beam computed tomography (CBCT) system, which uses a synchronized moving grid (SMOG) to reduce and correct scatter, an inter‐projection sensor fusion (IPSF) algorithm to estimate the missing information blocked by the grid, and a probability total variation (pTV) algorithm to reconstruct the CBCT image.Methods:A prototype SMOG‐equipped CBCT system was developed, and was used to acquire gridded projections with complimentary grid patterns in two neighboring projections. Scatter was reduced by the grid, and the remaining scatter was corrected by measuring it under the grid. An IPSF algorithm was used to estimate the missing information in a projection from data in its 2 neighboring projections. Feldkamp‐Davis‐Kress (FDK) algorithm was used to reconstruct the initial CBCT image using projections after IPSF processing for pTV. A probability map was generated depending on the confidence of estimation in IPSF for the regions of missing data and penumbra. pTV was finally used to reconstruct the CBCT image for a Catphan, and was compared to conventional CBCT image without using SMOG, images without using IPSF (SMOG + FDK and SMOG + mask‐TV), and image without using pTV (SMOG + IPSF + FDK).Results:The conventional CBCT without using SMOG shows apparent scatter‐induced cup artifacts. The approaches with SMOG but without IPSF show severe (SMOG + FDK) or additional (SMOG + TV) artifacts, possibly due to using projections of missing data. The 2 approaches with SMOG + IPSF removes the cup artifacts, and the pTV approach is superior than the FDK by substantially reducing the noise. Using the SMOG also reduces half of the imaging dose.Conclusion:The proposed technique is promising in improving CBCT image quality while reducing imaging dose.

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In cone-beam computed tomography (CBCT), reconstructed images are inherently degraded, restricting its image performance, due mainly to imperfections in the imaging process resulting from detector resolution, noise, X-ray tube's focal spot, and reconstruction procedure as well. Thus, the recovery of CBCT images from their degraded version is essential for improving image quality. In this study, we investigated a compressed-sensing (CS)-based blind deconvolution method to solve the blurring problem in CBCT where both the image to be recovered and the blur kernel (or point-spread function) of the imaging system are simultaneously recursively identified. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate the feasibility of using the algorithm for image deblurring in dental CBCT. In the experiment, we used a commercially available dental CBCT system that consisted of an X-ray tube, which was operated at 90kVp and 5mA, and a CMOS flat-panel detector with a 200-μm pixel size. The image characteristics were quantitatively investigated in terms of the image intensity, the root-mean-square error, the contrast-to-noise ratio, and the noise power spectrum. The results indicate that our proposed method effectively reduced the image blur in dental CBCT, excluding repetitious measurement of the system's blur kernel.