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Sample records for ct reconstruction estimation

  1. Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

    SciTech Connect

    Wang, Jing; Gu, Xuejun

    2013-10-15

    Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstruction to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion

  2. Dose reconstruction for real-time patient-specific dose estimation in CT

    SciTech Connect

    De Man, Bruno Yin, Zhye; Wu, Mingye; FitzGerald, Paul; Kalra, Mannudeep

    2015-05-15

    Purpose: Many recent computed tomography (CT) dose reduction approaches belong to one of three categories: statistical reconstruction algorithms, efficient x-ray detectors, and optimized CT acquisition schemes with precise control over the x-ray distribution. The latter category could greatly benefit from fast and accurate methods for dose estimation, which would enable real-time patient-specific protocol optimization. Methods: The authors present a new method for volumetrically reconstructing absorbed dose on a per-voxel basis, directly from the actual CT images. The authors’ specific implementation combines a distance-driven pencil-beam approach to model the first-order x-ray interactions with a set of Gaussian convolution kernels to model the higher-order x-ray interactions. The authors performed a number of 3D simulation experiments comparing the proposed method to a Monte Carlo based ground truth. Results: The authors’ results indicate that the proposed approach offers a good trade-off between accuracy and computational efficiency. The images show a good qualitative correspondence to Monte Carlo estimates. Preliminary quantitative results show errors below 10%, except in bone regions, where the authors see a bigger model mismatch. The computational complexity is similar to that of a low-resolution filtered-backprojection algorithm. Conclusions: The authors present a method for analytic dose reconstruction in CT, similar to the techniques used in radiation therapy planning with megavoltage energies. Future work will include refinements of the proposed method to improve the accuracy as well as a more extensive validation study. The proposed method is not intended to replace methods that track individual x-ray photons, but the authors expect that it may prove useful in applications where real-time patient-specific dose estimation is required.

  3. Image artefact propagation in motion estimation and reconstruction in interventional cardiac C-arm CT

    NASA Astrophysics Data System (ADS)

    Müller, K.; Maier, A. K.; Schwemmer, C.; Lauritsch, G.; De Buck, S.; Wielandts, J.-Y.; Hornegger, J.; Fahrig, R.

    2014-06-01

    The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical

  4. Reconstruction of difference in sequential CT studies using penalized likelihood estimation

    NASA Astrophysics Data System (ADS)

    Pourmorteza, A.; Dang, H.; Siewerdsen, J. H.; Stayman, J. W.

    2016-03-01

    Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data. Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical

  5. Reconstruction of difference in sequential CT studies using penalized likelihood estimation

    PubMed Central

    Pourmorteza, A; Dang, H; Siewerdsen, J H; Stayman, J W

    2016-01-01

    Characterization of anatomical change and other differences is important in sequential computed tomography (CT) imaging, where a high-fidelity patient-specific prior image is typically present, but is not used, in the reconstruction of subsequent anatomical states. Here, we introduce a penalized likelihood (PL) method called reconstruction of difference (RoD) to directly reconstruct a difference image volume using both the current projection data and the (unregistered) prior image integrated into the forward model for the measurement data. The algorithm utilizes an alternating minimization to find both the registration and reconstruction estimates. This formulation allows direct control over the image properties of the difference image, permitting regularization strategies that inhibit noise and structural differences due to inconsistencies between the prior image and the current data.Additionally, if the change is known to be local, RoD allows local acquisition and reconstruction, as opposed to traditional model-based approaches that require a full support field of view (or other modifications). We compared the performance of RoD to a standard PL algorithm, in simulation studies and using test-bench cone-beam CT data. The performances of local and global RoD approaches were similar, with local RoD providing a significant computational speedup. In comparison across a range of data with differing fidelity, the local RoD approach consistently showed lower error (with respect to a truth image) than PL in both noisy data and sparsely sampled projection scenarios. In a study of the prior image registration performance of RoD, a clinically reasonable capture ranges were demonstrated. Lastly, the registration algorithm had a broad capture range and the error for reconstruction of CT data was 35% and 20% less than filtered back-projection for RoD and PL, respectively. The RoD has potential for delivering high-quality difference images in a range of sequential clinical

  6. Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

    SciTech Connect

    Gang, Grace J.; Stayman, J. Webster; Zbijewski, Wojciech; Siewerdsen, Jeffrey H.

    2014-08-15

    Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP

  7. Breast volume estimation from systematic series of CT scans using the Cavalieri principle and 3D reconstruction.

    PubMed

    Erić, Mirela; Anderla, Andraš; Stefanović, Darko; Drapšin, Miodrag

    2014-01-01

    Preoperative breast volume estimation is very important for the success of the breast surgery. In the present study, two different breast volume determination methods, Cavalieri principle and 3D reconstruction were compared. Consecutive sections were taken in slice thickness of 5 mm. Every 2nd breast section in a set of consecutive sections was selected. We marked breast tissue with blue line on each selected section, and so prepared CT scans used for breast volume estimation. The volumes of the 60 breasts were estimated using the Cavalieri principle and 3D reconstruction. The mean breast volume value was established to be 467.79 ± 188.90 cm(3) with Cavalieri method and 465.91 ± 191.41 cm(3) with 3D reconstruction. The mean CE for the estimates in this study was calculated as 0.25%. Skin-sparing volume was about 91.64% of the whole breast volume. Both methods are very accurate and have a strong linear association. Our results suggest that the calculation of breast volume or its part in vivo from systematic series of CT scans using the Cavalieri principle or 3D breast reconstruction is accurate enough to have a significant clinical benefit in planning reconstructive breast surgery. These methods can help the surgeon guide the choice of the most appropriate implant or/and flap preoperatively. Copyright © 2014 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

  8. SU-E-I-99: Estimation of Effective Charge Distribution by Dual-Energy CT Reconstruction

    SciTech Connect

    Sakata, D; Kida, S; Nakano, M; Masutani, Y; Nakagawa, K; Haga, A

    2014-06-01

    Purpose: Computed Tomography (CT) is a method to produce slice image of specific volume from the scanned x-ray projection images. The contrast of CT image is correlated with the attenuation coefficients of the x-ray in the object. The attenuation coefficient is strongly dependent on the x-ray energy and the effective charge of the material. The purpose of this presentation is to show the effective charge distribution predicted by CT images reconstructed with kilovoltage(kV) and megavoltage(MV) x-ray energy. Methods: The attenuation coefficients of x-ray can be characterized by cross section of photoionization and Compton scattering for the specific xray energy. In particular, the photoionization cross section is strongly correlated with the effective charge of the object. Hence we can calculate effective charge by solving the coupled equation between the attenuation coefficient and the theoretical cross section. For this study, we use the megavoltage (MV) and kilovoltage (kV) x-rays of Elekta Synergy as the dual source x-ray, and CT image of the Phantom Laboratory CatPhan is reconstructed by the filtered back projection (FBP) and iterative algorithm for cone-beam CT (CBCT). Results: We report attenuation coefficients of each component of the CatPhan specified by each x-ray source. Also the effective charge distribution is evaluated by the MV and kV dual x-ray sources. The predicted effective charges are comparable with the nominal ones. Conclusion: We developed the MV and kV dual-source CBCT reconstruction to yield the effective charge distribution. For more accuracy, it is critical to remove an effect of the scattering photon in the CBCT reconstruction algorithm. The finding will be fine reference of the effective charge of tissue and lead to the more realistic absorbed-dose calculation. This work was partly supported by the JSPS Core-to-Core Program(No. 23003), and this work was partly supported by JSPS KAKENHI 24234567.

  9. Hybrid spectral CT reconstruction

    PubMed Central

    Clark, Darin P.

    2017-01-01

    Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

  10. Hybrid spectral CT reconstruction.

    PubMed

    Clark, Darin P; Badea, Cristian T

    2017-01-01

    Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

  11. dPIRPLE: A Joint Estimation Framework for Deformable Registration and Penalized-Likelihood CT Image Reconstruction using Prior Images

    PubMed Central

    Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

    2014-01-01

    Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc.). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration

  12. dPIRPLE: a joint estimation framework for deformable registration and penalized-likelihood CT image reconstruction using prior images

    NASA Astrophysics Data System (ADS)

    Dang, H.; Wang, A. S.; Sussman, Marc S.; Siewerdsen, J. H.; Stayman, J. W.

    2014-09-01

    Sequential imaging studies are conducted in many clinical scenarios. Prior images from previous studies contain a great deal of patient-specific anatomical information and can be used in conjunction with subsequent imaging acquisitions to maintain image quality while enabling radiation dose reduction (e.g., through sparse angular sampling, reduction in fluence, etc). However, patient motion between images in such sequences results in misregistration between the prior image and current anatomy. Existing prior-image-based approaches often include only a simple rigid registration step that can be insufficient for capturing complex anatomical motion, introducing detrimental effects in subsequent image reconstruction. In this work, we propose a joint framework that estimates the 3D deformation between an unregistered prior image and the current anatomy (based on a subsequent data acquisition) and reconstructs the current anatomical image using a model-based reconstruction approach that includes regularization based on the deformed prior image. This framework is referred to as deformable prior image registration, penalized-likelihood estimation (dPIRPLE). Central to this framework is the inclusion of a 3D B-spline-based free-form-deformation model into the joint registration-reconstruction objective function. The proposed framework is solved using a maximization strategy whereby alternating updates to the registration parameters and image estimates are applied allowing for improvements in both the registration and reconstruction throughout the optimization process. Cadaver experiments were conducted on a cone-beam CT testbench emulating a lung nodule surveillance scenario. Superior reconstruction accuracy and image quality were demonstrated using the dPIRPLE algorithm as compared to more traditional reconstruction methods including filtered backprojection, penalized-likelihood estimation (PLE), prior image penalized-likelihood estimation (PIPLE) without registration, and

  13. Cervical vertebrae maturation index estimates on cone beam CT: 3D reconstructions vs sagittal sections

    PubMed Central

    Bonfim, Marco A E; Costa, André L F; Ximenez, Michel E L; Cotrim-Ferreira, Flávio A; Ferreira-Santos, Rívea I

    2016-01-01

    Objectives: The aim of this study was to evaluate the performance of CBCT three-dimensional (3D) reconstructions and sagittal sections for estimates of cervical vertebrae maturation index (CVMI). Methods: The sample consisted of 72 CBCT examinations from patients aged 8–16 years (45 females and 27 males) selected from the archives of two private clinics. Two calibrated observers (kappa scores: ≥0.901) interpreted the CBCT settings twice. Intra- and interobserver agreement for both imaging exhibition modes was analyzed by kappa statistics, which was also used to analyze the agreement between 3D reconstructions and sagittal sections. Correlations between cervical vertebrae maturation estimates and chronological age, as well as between the assessments by 3D reconstructions and sagittal sections, were analyzed using gamma Goodman–Kruskal coefficients (α = 0.05). Results: The kappa scores evidenced almost perfect agreement between the first and second assessments of the cervical vertebrae by 3D reconstructions (0.933–0.983) and sagittal sections (0.983–1.000). Similarly, the agreement between 3D reconstructions and sagittal sections was almost perfect (kappa index: 0.983). In most divergent cases, the difference between 3D reconstructions and sagittal sections was one stage of CVMI. Strongly positive correlations (>0.8, p < 0.001) were found not only between chronological age and CVMI but also between the estimates by 3D reconstructions and sagittal sections (p < 0.001). Conclusions: Although CBCT imaging must not be used exclusively for this purpose, it may be suitable for skeletal maturity assessments. PMID:26509559

  14. Cardiorespiratory motion-compensated micro-CT image reconstruction using an artifact model-based motion estimation.

    PubMed

    Brehm, Marcus; Sawall, Stefan; Maier, Joscha; Sauppe, Sebastian; Kachelrieß, Marc

    2015-04-01

    Cardiac in vivo micro-CT imaging of small animals typically requires double gating due to long scan times and high respiratory rates. The simultaneous respiratory and cardiac gating can either be done prospectively or retrospectively. In any case, for true 5D imaging, i.e., three spatial dimensions plus one respiratory-temporal dimension plus one cardiac temporal dimension, the amount of information corresponding to a given respiratory and cardiac phase is orders of magnitude lower than the total amount of information acquired. Achieving similar image quality for 5D than for usual 3D investigations would require increasing the amount of data and thus the applied dose to the animal. Therefore, the goal is phase-correlated imaging with high image quality but without increasing the dose level. To achieve this, the authors propose a new image reconstruction algorithm that makes use of all available projection data, also of that corresponding to other motion windows. In particular, the authors apply a motion-compensated image reconstruction approach that sequentially compensates for respiratory and cardiac motion to decrease the impact of sparsification. In that process, all projection data are used no matter which motion phase they were acquired in. Respiratory and cardiac motion are compensated for by using motion vector fields. These motion vector fields are estimated from initial phase-correlated reconstructions based on a deformable registration approach. To decrease the sensitivity of the registration to sparse-view artifacts, an artifact model-based approach is used including a cyclic consistent nonrigid registration algorithm. The preliminary results indicate that the authors' approach removes the sparse-view artifacts of conventional phase-correlated reconstructions while maintaining temporal resolution. In addition, it achieves noise levels and spatial resolution comparable to that of nongated reconstructions due to the improved dose usage. By using the

  15. Reconstruction of limited-angle dual-energy CT using mutual learning and cross-estimation (MLCE)

    NASA Astrophysics Data System (ADS)

    Zhang, Huayu; Xing, Yuxiang

    2016-03-01

    Dual-energy CT (DECT) imaging has gained a lot of attenuation because of its capability to discriminate materials. We proposes a flexible DECT scan strategy which can be realized on a system with general X-ray sources and detectors. In order to lower dose and scanning time, our DECT acquires two projections data sets on two arcs of limited-angular coverage (one for each energy) respectively. Meanwhile, a certain number of rays from two data sets form conjugate sampling pairs. Our reconstruction method for such a DECT scan mainly tackles the consequent limited-angle problem. Using the idea of artificial neural network, we excavate the connection between projections at two different energies by constructing a relationship between the linear attenuation coefficient of the high energy and that of the low one. We use this relationship to cross-estimate missing projections and reconstruct attenuation images from an augmented data set including projections at views covered by itself (projections collected in scanning) and by the other energy (projections estimated) for each energy respectively. Validated by our numerical experiment on a dental phantom with rather complex structures, our DECT is effective in recovering small structures in severe limited-angle situations. This DECT scanning strategy can much broaden DECT design in reality.

  16. Limited view angle iterative CT reconstruction

    NASA Astrophysics Data System (ADS)

    Kisner, Sherman J.; Haneda, Eri; Bouman, Charles A.; Skatter, Sondre; Kourinny, Mikhail; Bedford, Simon

    2012-03-01

    Computed Tomography (CT) is widely used for transportation security to screen baggage for potential threats. For example, many airports use X-ray CT to scan the checked baggage of airline passengers. The resulting reconstructions are then used for both automated and human detection of threats. Recently, there has been growing interest in the use of model-based reconstruction techniques for application in CT security systems. Model-based reconstruction offers a number of potential advantages over more traditional direct reconstruction such as filtered backprojection (FBP). Perhaps one of the greatest advantages is the potential to reduce reconstruction artifacts when non-traditional scan geometries are used. For example, FBP tends to produce very severe streaking artifacts when applied to limited view data, which can adversely affect subsequent processing such as segmentation and detection. In this paper, we investigate the use of model-based reconstruction in conjunction with limited-view scanning architectures, and we illustrate the value of these methods using transportation security examples. The advantage of limited view architectures is that it has the potential to reduce the cost and complexity of a scanning system, but its disadvantage is that limited-view data can result in structured artifacts in reconstructed images. Our method of reconstruction depends on the formulation of both a forward projection model for the system, and a prior model that accounts for the contents and densities of typical baggage. In order to evaluate our new method, we use realistic models of baggage with randomly inserted simple simulated objects. Using this approach, we show that model-based reconstruction can substantially reduce artifacts and improve important metrics of image quality such as the accuracy of the estimated CT numbers.

  17. Estimation of non-solid lung nodule volume with low-dose CT protocols: effect of reconstruction algorithm and measurement method

    NASA Astrophysics Data System (ADS)

    Gavrielides, Marios A.; DeFilippo, Gino; Berman, Benjamin P.; Li, Qin; Petrick, Nicholas; Schultz, Kurt; Siegelman, Jenifer

    2017-03-01

    Computed tomography is primarily the modality of choice to assess stability of nonsolid pulmonary nodules (sometimes referred to as ground-glass opacity) for three or more years, with change in size being the primary factor to monitor. Since volume extracted from CT is being examined as a quantitative biomarker of lung nodule size, it is important to examine factors affecting the performance of volumetric CT for this task. More specifically, the effect of reconstruction algorithms and measurement method in the context of low-dose CT protocols has been an under-examined area of research. In this phantom study we assessed volumetric CT with two different measurement methods (model-based and segmentation-based) for nodules with radiodensities of both nonsolid (-800HU and -630HU) and solid (-10HU) nodules, sizes of 5mm and 10mm, and two different shapes (spherical and spiculated). Imaging protocols included CTDIvol typical of screening (1.7mGy) and sub-screening (0.6mGy) scans and different types of reconstruction algorithms across three scanners. Results showed that radio-density was the factor contributing most to overall error based on ANOVA. The choice of reconstruction algorithm or measurement method did not affect substantially the accuracy of measurements; however, measurement method affected repeatability with repeatability coefficients ranging from around 3-5% for the model-based estimator to around 20-30% across reconstruction algorithms for the segmentation-based method. The findings of the study can be valuable toward developing standardized protocols and performance claims for nonsolid nodules.

  18. Maximum-likelihood joint image reconstruction and motion estimation with misaligned attenuation in TOF-PET/CT

    NASA Astrophysics Data System (ADS)

    Bousse, Alexandre; Bertolli, Ottavia; Atkinson, David; Arridge, Simon; Ourselin, Sébastien; Hutton, Brian F.; Thielemans, Kris

    2016-02-01

    This work is an extension of our recent work on joint activity reconstruction/motion estimation (JRM) from positron emission tomography (PET) data. We performed JRM by maximization of the penalized log-likelihood in which the probabilistic model assumes that the same motion field affects both the activity distribution and the attenuation map. Our previous results showed that JRM can successfully reconstruct the activity distribution when the attenuation map is misaligned with the PET data, but converges slowly due to the significant cross-talk in the likelihood. In this paper, we utilize time-of-flight PET for JRM and demonstrate that the convergence speed is significantly improved compared to JRM with conventional PET data.

  19. Resolution-enhancing hybrid, spectral CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Badea, C. T.

    2016-04-01

    Spectral x-ray imaging based on photon-counting x-ray detectors (PCXD) is an area of growing interest. By measuring the energy of x-ray photons, a spectral CT system can better differentiate elements using a single scan. However, the spatial resolution achievable with most PCXDs limits their application, particularly in preclinical CT imaging. Consequently, our group is developing a hybrid micro-CT scanner based on a high-resolution, energy-integrating (EID) detector and a lower-resolution, PCXD. To complement this system, we propose and demonstrate a hybrid, spectral CT reconstruction algorithm which robustly combines the spectral contrast of the PCXD with the spatial resolution of the EID. Specifically, the high-resolution, spectrally resolved data (X) is recovered as the sum of two matrices: one with low column rank (XL) determined from the EID data and one with intensity gradient sparse columns (XS) corresponding to the upsampled spectral contrast obtained from the PCXD data. We test the proposed algorithm in a feasibility study focused on molecular imaging of atherosclerotic plaque using activatable iodine and gold nanoparticles. The results show accurate estimation of material concentrations at increased spatial resolution for a voxel size ratio between the PCXD and the EID of 500 μm3:100 μm3. Specifically, regularized, iterative reconstruction of the MOBY mouse phantom around the K-edges of iodine (33.2 keV) and gold (80.7 keV) reduces the reconstruction error by more than a factor of three relative to least-squares, algebraic reconstruction. Likewise, the material decomposition accuracy into iodine, gold, calcium, and water improves by more than a factor of two.

  20. Localized and efficient cardiac CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Badea, C. T.

    2017-03-01

    The superiority of iterative reconstruction techniques over classic analytical ones is well documented in a variety of CT imaging applications where radiation dose and sampling time are limiting factors. However, by definition, the iterative nature of advanced reconstruction techniques is accompanied by a substantial increase in data processing time. This problem is further exacerbated in temporal and spectral CT reconstruction problems where the gap between the amount of data acquired and the amount of data to be reconstructed is exaggerated within the framework of compressive sensing. Two keys to overcoming this barrier include (1) advancements in parallel-computing technology and (2) advancements in data-efficient reconstruction. In this work, we propose a novel, two-stage strategy for 4D cardiac CT reconstruction which leverages these two keys by (1) exploiting GPU computing hardware and by (2) reconstructing temporal contrast on a limited spatial domain. Following a review of the proposed algorithm, we demonstrate its application in retrospectively gated cardiac CT reconstruction using the 4D MOBY mouse phantom. Quantitatively, reconstructing the temporal contrast on a limited domain reduces the overall reconstruction error by 20% and the reconstruction error within the dynamic portion of the phantom by 15% (root-mean-square error metric). A complementary in vivo mouse experiment demonstrates a suitable reconstruction fidelity to allow the measurement of cardiac functional metrics while reducing computation time by 75% relative to direct reconstruction of ten phases of the cardiac cycle. We believe that the proposed algorithm will serve as the basis for novel, data-efficient, multi-dimensional CT reconstruction techniques.

  1. Iterative image reconstruction in spectral CT

    NASA Astrophysics Data System (ADS)

    Hernandez, Daniel; Michel, Eric; Kim, Hye S.; Kim, Jae G.; Han, Byung H.; Cho, Min H.; Lee, Soo Y.

    2012-03-01

    Scan time of spectral-CTs is much longer than conventional CTs due to limited number of x-ray photons detectable by photon-counting detectors. However, the spectral pixel information in spectral-CT has much richer information on physiological and pathological status of the tissues than the CT-number in conventional CT, which makes the spectral- CT one of the promising future imaging modalities. One simple way to reduce the scan time in spectral-CT imaging is to reduce the number of views in the acquisition of projection data. But, this may result in poorer SNR and strong streak artifacts which can severely compromise the image quality. In this work, spectral-CT projection data were obtained from a lab-built spectral-CT consisting of a single CdTe photon counting detector, a micro-focus x-ray tube and scan mechanics. For the image reconstruction, we used two iterative image reconstruction methods, the simultaneous iterative reconstruction technique (SIRT) and the total variation minimization based on conjugate gradient method (CG-TV), along with the filtered back-projection (FBP) to compare the image quality. From the imaging of the iodine containing phantoms, we have observed that SIRT and CG-TV are superior to the FBP method in terms of SNR and streak artifacts.

  2. Quantitative image quality evaluation for cardiac CT reconstructions

    NASA Astrophysics Data System (ADS)

    Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.; Balhorn, William; Okerlund, Darin R.

    2016-03-01

    Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.

  3. Beam hardening correction for sparse-view CT reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Wenlei; Rong, Junyan; Gao, Peng; Liao, Qimei; Lu, HongBing

    2015-03-01

    Beam hardening, which is caused by spectrum polychromatism of the X-ray beam, may result in various artifacts in the reconstructed image and degrade image quality. The artifacts would be further aggravated for the sparse-view reconstruction due to insufficient sampling data. Considering the advantages of the total-variation (TV) minimization in CT reconstruction with sparse-view data, in this paper, we propose a beam hardening correction method for sparse-view CT reconstruction based on Brabant's modeling. In this correction model for beam hardening, the attenuation coefficient of each voxel at the effective energy is modeled and estimated linearly, and can be applied in an iterative framework, such as simultaneous algebraic reconstruction technique (SART). By integrating the correction model into the forward projector of the algebraic reconstruction technique (ART), the TV minimization can recover images when only a limited number of projections are available. The proposed method does not need prior information about the beam spectrum. Preliminary validation using Monte Carlo simulations indicates that the proposed method can provide better reconstructed images from sparse-view projection data, with effective suppression of artifacts caused by beam hardening. With appropriate modeling of other degrading effects such as photon scattering, the proposed framework may provide a new way for low-dose CT imaging.

  4. SU-E-T-143: Effect of X-Ray and Cone Beam CT Reconstruction Parameters On Estimation of Bone Volume of Mice Used in Aging Research

    SciTech Connect

    Russ, M; Pang, M; Troen, B; Rudin, S; Ionita, C

    2014-06-01

    Purpose: To investigate the variations in bone volume calculations in mice involved in aging research when changing cone beam micro-CT x-ray and reconstruction parameters. Methods: Mouse spines were placed on an indexed turn table that rotated 0.5° per projection and imaged by a self-built micro CT machine containing a CCD-based high-resolution x-ray detector. After the full 360° rotation data set of object images was obtained, a standard filtered back-projection cone beam reconstruction was performed. Four different kVp's between 40–70 kVp in 10kVp increments were selected. For each kVp two mAs settings were used. Each acquisition was reconstructed using two voxel sizes (12 and 25μm) and two step angles, 0.5° and 1°, respectively. A LabView program was written to determine the total bone volume contained in the mouse's total spine volume (bone plus gaps) as a measure of spine health. First, the user selected the desired 512×512 reconstruction to view the whole spine volume which was then used to select a gray-level threshold that allowed for viewing of the bone structure, then another threshold to include gaps. The program returned bone volume, bone × gap volume, and their ratio, BVF. Results: The calculated bone volume fractions were compared as a function of tube potential. Cases with 25μm slice thickness showed trials with lower kVp's had greater image contrast, which resulted in higher calculated bone volume fractions. Cases with 12μm reconstructed slice thickness were significantly noisier, and showed no clear maximum BVF. Conclusion: Using the projection images and reconstructions acquired from the micro CT, it can be shown that the micro-CT x-ray and reconstruction parameters significantly affect the total bone volume calculations. When comparing mice cohorts treated with different therapies researchers need to be aware of such details and use volumes which were acquired and processed in identical conditions.

  5. Can clinical CT data improve forensic reconstruction?

    PubMed

    Schuh, P; Scheurer, E; Fritz, K; Pavlic, M; Hassler, E; Rienmüller, R; Yen, K

    2013-05-01

    In accidents resulting in severe injuries, a clinical forensic examination is generally abandoned in the initial phase due to high-priority clinical needs. However, in many cases, data from clinical computed tomography (CT) examinations are available. The goals of this prospective study were (a) to evaluate clinical CT data as a basis for forensic reconstruction of the sequence of events, (b) to assess if forensic radiological follow-up reading improves the forensic diagnostic benefit compared to the written clinical radiological reports, and (c) to evaluate if full data storage including additional reconstructed 0.6-mm slices enhances forensic analysis. Clinical CT data of 15 living individuals with imaging of at least the head, thorax, and abdomen following polytrauma were examined regarding the forensic evaluation of the sequence of events. Additionally, 0.6-mm slices and 3D images were reconstructed for forensic purposes and used for the evaluation. At the forensic radiological readings, additional traumatic findings were observed in ten of the 15 patients. The main weakness of the clinical reports was that they were not detailed enough, particularly regarding the localization of injuries and description of wound morphology. In seven cases, however, forensic conclusions were possible on the basis of the written clinical reports, whereas in five cases forensic reconstruction required specific follow-up reading. The additional 0.6-mm slices were easily available and with improved 3D image quality and forensic diagnostics. In conclusion, the use of clinical CT data can considerably support forensic expertise regarding reconstruction issues. Forensic follow-up reading as well as the use of additional thin slices for 3D analysis can further improve its benefit for forensic reconstruction purposes.

  6. Filtered backprojection proton CT reconstruction along most likely paths

    SciTech Connect

    Rit, Simon; Dedes, George; Freud, Nicolas; Sarrut, David; Letang, Jean Michel

    2013-03-15

    Purpose: Proton CT (pCT) has the potential to accurately measure the electron density map of tissues at low doses but the spatial resolution is prohibitive if the curved paths of protons in matter is not accounted for. The authors propose to account for an estimate of the most likely path of protons in a filtered backprojection (FBP) reconstruction algorithm. Methods: The energy loss of protons is first binned in several proton radiographs at different distances to the proton source to exploit the depth-dependency of the estimate of the most likely path. This process is named the distance-driven binning. A voxel-specific backprojection is then used to select the adequate radiograph in the distance-driven binning in order to propagate in the pCT image the best achievable spatial resolution in proton radiographs. The improvement in spatial resolution is demonstrated using Monte Carlo simulations of resolution phantoms. Results: The spatial resolution in the distance-driven binning depended on the distance of the objects from the source and was optimal in the binned radiograph corresponding to that distance. The spatial resolution in the reconstructed pCT images decreased with the depth in the scanned object but it was always better than previous FBP algorithms assuming straight line paths. In a water cylinder with 20 cm diameter, the observed range of spatial resolutions was 0.7 - 1.6 mm compared to 1.0 - 2.4 mm at best with a straight line path assumption. The improvement was strongly enhanced in shorter 200 Degree-Sign scans. Conclusions: Improved spatial resolution was obtained in pCT images with filtered backprojection reconstruction using most likely path estimates of protons. The improvement in spatial resolution combined with the practicality of FBP algorithms compared to iterative reconstruction algorithms makes this new algorithm a candidate of choice for clinical pCT.

  7. Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

    SciTech Connect

    Evans, Joshua D. Yu, Yaduo; Williamson, Jeffrey F.; Whiting, Bruce R.; O’Sullivan, Joseph A.; Politte, David G.; Klahr, Paul H.

    2013-12-15

    Purpose: Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasivein vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. Methods: Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. Results: Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm{sup 3} grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean

  8. Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual-energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

    PubMed Central

    Evans, Joshua D.; Whiting, Bruce R.; O’Sullivan, Joseph A.; Politte, David G.; Klahr, Paul H.; Yu, Yaduo; Williamson, Jeffrey F.

    2013-01-01

    Purpose: Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasive in vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. Methods: Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. Results: Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm3 grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean

  9. Accuracy of quantitative reconstructions in SPECT/CT imaging

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Celler, A.; Belhocine, T.; van der Werf, R.; Driedger, A.

    2008-09-01

    The goal of this study was to determine the quantitative accuracy of our OSEM-APDI reconstruction method based on SPECT/CT imaging for Tc-99m, In-111, I-123, and I-131 isotopes. Phantom studies were performed on a SPECT/low-dose multislice CT system (Infinia-Hawkeye-4 slice, GE Healthcare) using clinical acquisition protocols. Two radioactive sources were centrally and peripherally placed inside an anthropometric Thorax phantom filled with non-radioactive water. Corrections for attenuation, scatter, collimator blurring and collimator septal penetration were applied and their contribution to the overall accuracy of the reconstruction was evaluated. Reconstruction with the most comprehensive set of corrections resulted in activity estimation with error levels of 3-5% for all the isotopes.

  10. Fast parallel algorithm for CT image reconstruction.

    PubMed

    Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2012-01-01

    In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).

  11. Reconstruction filters and contrast detail curves in CT

    NASA Astrophysics Data System (ADS)

    Huda, W.; Ogden, K. M.; Samei, E.; Scalzetti, E. M.; Lavallee, R. L.; Roskopf, M. L.; Groat, G. E.

    2008-03-01

    In this study, we investigated the effect of CT reconstruction filters in abdominal CT images of a male anthropomorphic phantom. A GE Light Speed CT 4-slice scanner was used to scan the abdomen of an adult Rando phantom. Cross sectional images of the phantom were reconstructed using four reconstruction filters: (1) soft tissue with the lowest noise; (2) detail (relative noise 1.7); (3) bone (relative noise 4.5); and (4) edge (relative noise 7.7). A two Alternate Forced Choice (AFC) experimental paradigm was used to estimate the intensity needed to achieve 92% correct (i.e., I 92%). Four observers measured detection performance for five lesions with size ranging from 2.5 to 12.5 mm for each of these four reconstruction filters. Contrast detail curves obtained in images of an anthropomorphic phantom were not straight lines, but best fitted to a second order polynomial. Results from four readers show similar trends with modest inter-observer differences with the measured coefficient of variation of the absolute performance levels of ~22%. All reconstruction filters had similar shaped contrast detail curves except for smallest details where the frequency response of filters differed most significantly. Increasing the noise level always reduced detection performance, and a doubling of image noise resulted in an average drop in detection performance of ~20%. The key findings of this study are that (a) the Rose model can provide reasonable predictions as to how changes in lesion size affect observer detection; (b) the shape of CT contrast detail curves is affected only very slightly with reconstruction filter; (c) changes in reconstruction filter noise can predict qualitative changes in observer detection performance, but are poor direct predictors of the quantitative changes of imaging performance.

  12. Parameter estimating state reconstruction

    NASA Technical Reports Server (NTRS)

    George, E. B.

    1976-01-01

    Parameter estimation is considered for systems whose entire state cannot be measured. Linear observers are designed to recover the unmeasured states to a sufficient accuracy to permit the estimation process. There are three distinct dynamics that must be accommodated in the system design: the dynamics of the plant, the dynamics of the observer, and the system updating of the parameter estimation. The latter two are designed to minimize interaction of the involved systems. These techniques are extended to weakly nonlinear systems. The application to a simulation of a space shuttle POGO system test is of particular interest. A nonlinear simulation of the system is developed, observers designed, and the parameters estimated.

  13. Model-based iterative reconstruction in ultra-low-dose pediatric chest CT: comparison with adaptive statistical iterative reconstruction.

    PubMed

    Kim, Hae Jin; Yoo, So-Young; Jeon, Tae Yeon; Kim, Ji Hye

    2016-01-01

    To evaluate image quality and dose reduction of ultra-low-dose pediatric chest CT reconstructed with model-based iterative reconstruction (MBIR), as compared with adaptive statistical iterative reconstruction (ASIR). Fifty-seven patients (mean age 14 years, M:F=31:26) who underwent ultra-low-dose chest CT reconstructed with both MBIR and ASIR were enrolled in the study. The subjective and objective image qualities of both reconstruction techniques were assessed by 3 radiologists, and compared using statistical analysis. We also evaluated radiation dose of ultra-low-dose chest CT as well as degree of dose reduction in comparison to the prior CT (either standard dose or reduced dose protocol) available in 36 patients. The image quality of MBIR was superior to ASIR both subjectively and objectively. While MBIR showed preserved diagnostic acceptability in 100%, ASIR showed 92% at mean 0.31 mSv (range, 0.13-0.57 mSv) ultra-low-dose CT. In the 36 patients who underwent the prior CT, mean decrease in size-specific dose estimate (SSDE) and dose length product (DLP) at ultra-low-dose CT was 88% (range, 34% - 98%) and 86% (range,42% - 99%), respectively. MBIR significantly improves image quality, as compared to ASIR. Furthermore, MBIR facilitates diagnostically acceptable ultra-low-dose chest CT with nearly 90% less radiation. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. CT reconstruction via denoising approximate message passing

    NASA Astrophysics Data System (ADS)

    Perelli, Alessandro; Lexa, Michael A.; Can, Ali; Davies, Mike E.

    2016-05-01

    In this paper, we adapt and apply a compressed sensing based reconstruction algorithm to the problem of computed tomography reconstruction for luggage inspection. Specifically, we propose a variant of the denoising generalized approximate message passing (D-GAMP) algorithm and compare its performance to the performance of traditional filtered back projection and to a penalized weighted least squares (PWLS) based reconstruction method. D-GAMP is an iterative algorithm that at each iteration estimates the conditional probability of the image given the measurements and employs a non-linear "denoising" function which implicitly imposes an image prior. Results on real baggage show that D-GAMP is well-suited to limited-view acquisitions.

  15. CT substitutes derived from MR images reconstructed with parallel imaging.

    PubMed

    Johansson, Adam; Garpebring, Anders; Asklund, Thomas; Nyholm, Tufve

    2014-08-01

    Computed tomography (CT) substitute images can be generated from ultrashort echo time (UTE) MRI sequences with radial k-space sampling. These CT substitutes can be used as ordinary CT images for PET attenuation correction and radiotherapy dose calculations. Parallel imaging allows faster acquisition of magnetic resonance (MR) images by exploiting differences in receiver coil element sensitivities. This study investigates whether non-Cartesian parallel imaging reconstruction can be used to improve CT substitutes generated from shorter examination times. The authors used gridding as well as two non-Cartesian parallel imaging reconstruction methods, SPIRiT and CG-SENSE, to reconstruct radial UTE and gradient echo (GE) data into images of the head for 23 patients. For each patient, images were reconstructed from the full dataset and from a number of subsampled datasets. The subsampled datasets simulated shorter acquisition times by containing fewer radial k-space spokes (1000, 2000, 3000, 5000, and 10,000 spokes) than the full dataset (30,000 spokes). For each combination of patient, reconstruction method, and number of spokes, the reconstructed UTE and GE images were used to generate a CT substitute. Each CT substitute image was compared to a real CT image of the same patient. The mean absolute deviation between the CT number in CT substitute and CT decreased when using SPIRiT as compared to gridding reconstruction. However, the reduction was small and the CT substitute algorithm was insensitive to moderate subsampling (≥ 5000 spokes) regardless of reconstruction method. For more severe subsampling (≤ 3000 spokes), corresponding to acquisition times less than a minute long, the CT substitute quality was deteriorated for all reconstruction methods but SPIRiT gave a reduction in the mean absolute deviation of down to 25 Hounsfield units compared to gridding. SPIRiT marginally improved the CT substitute quality for a given number of radial spokes as compared to

  16. Contralateral breast volume measurement during chest CT for postmastectomy breast reconstruction.

    PubMed

    Osman, Noha Mohamed; Botros, Samer Malak; Ghany, Ahmed Fathy Abdel; Farid, Ashraf Maher

    2015-02-01

    Successful breast reconstruction after mastectomy may be guided by knowledge of the contralateral breast volume. Three-dimensional (3D) reconstruction based on a CT examination was used to determine the volume of the contralateral normal breast before postmastectomy breast reconstruction. Seventeen female patients scheduled for postmastectomy breast reconstruction using silicon implant prostheses were using noncontrast CT scans of the chest for metastatic work-up. The CT scans were used to measure the volume of contralateral normal breast. The volume estimates were used to specify the proper implant size for cosmesis. The estimated CT volume was correlated with volume estimates obtained using water displacement, as well as anthropometric measurements performed by a plastic surgeon. Breast volume estimates obtained from CT scans were highly correlated with volumes measured by the two nonradiological methods, yielding a positive linear correlation coefficient (r = 0.99). Volume measurement of the intact breast should be added to reports of routine chest CT studies in patients who undergo mastectomy. CT imaging is a feasible method for contralateral normal breast volume measurement in these patients.

  17. Region-of-interest reconstruction for a cone-beam dental CT with a circular trajectory

    NASA Astrophysics Data System (ADS)

    Hu, Zhanli; Zou, Jing; Gui, Jianbao; Zheng, Hairong; Xia, Dan

    2013-04-01

    Dental CT is the most appropriate and accurate device for preoperative evaluation of dental implantation. It can demonstrate the quantity of bone in three dimensions (3D), the location of important adjacent anatomic structures and the quality of available bone with minimal geometric distortion. Nevertheless, with the rapid increase of dental CT examinations, we are facing the problem of dose reduction without loss of image quality. In this work, backprojection-filtration (BPF) and Feldkamp-Davis-Kress (FDK) algorithm was applied to reconstruct the 3D full image and region-of-interest (ROI) image from complete and truncated circular cone-beam data respectively by computer-simulation. In addition, the BPF algorithm was evaluated based on the 3D ROI-image reconstruction from real data, which was acquired from our developed circular cone-beam prototype dental CT system. The results demonstrated that the ROI-image quality reconstructed from truncated data using the BPF algorithm was comparable to that reconstructed from complete data. The FDK algorithm, however, created artifacts while reconstructing ROI-image. Thus it can be seen, for circular cone-beam dental CT, reducing scanning angular range of the BPF algorithm used for ROI-image reconstruction are helpful for reducing the radiation dose and scanning time. Finally, an analytical method was developed for estimation of the ROI projection area on the detector before CT scanning, which would help doctors to roughly estimate the total radiation dose before the CT examination.

  18. Accelerated augmented Lagrangian method for few-view CT reconstruction

    NASA Astrophysics Data System (ADS)

    Wu, Junfeng; Mou, Xuanqin

    2012-03-01

    Recently iterative reconstruction algorithms with total variation (TV) regularization have shown its tremendous power in image reconstruction from few-view projection data, but it is much more demanding in computation. In this paper, we propose an accelerated augmented Lagrangian method (ALM) for few-view CT reconstruction with total variation regularization. Experimental phantom results demonstrate that the proposed method not only reconstruct high quality image from few-view projection data but also converge fast to the optimal solution.

  19. Cardiac cone-beam CT volume reconstruction using ART

    SciTech Connect

    Nielsen, T.; Manzke, R.; Proksa, R.; Grass, M.

    2005-04-01

    Modern computed tomography systems allow volume imaging of the heart. Up to now, approximately two-dimensional (2D) and 3D algorithms based on filtered backprojection are used for the reconstruction. These algorithms become more sensitive to artifacts when the cone angle of the x-ray beam increases as it is the current trend of computed tomography (CT) technology. In this paper, we investigate the potential of iterative reconstruction based on the algebraic reconstruction technique (ART) for helical cardiac cone-beam CT. Iterative reconstruction has the advantages that it takes the cone angle into account exactly and that it can be combined with retrospective cardiac gating fairly easily. We introduce a modified ART algorithm for cardiac CT reconstruction. We apply it to clinical cardiac data from a 16-slice CT scanner and compare the images to those obtained with a current analytical reconstruction method. In a second part, we investigate the potential of iterative reconstruction for a large area detector with 256 slices. For the clinical cases, iterative reconstruction produces excellent images of diagnostic quality. For the large area detector, iterative reconstruction produces images superior to analytical reconstruction in terms of cone-beam artifacts.

  20. A biological phantom for evaluation of CT image reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

    2014-03-01

    In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

  1. Iterative CT reconstruction via minimizing adaptively reweighted total variation.

    PubMed

    Zhu, Lei; Niu, Tianye; Petrongolo, Michael

    2014-01-01

    Iterative reconstruction via total variation (TV) minimization has demonstrated great successes in accurate CT imaging from under-sampled projections. When projections are further reduced, over-smoothing artifacts appear in the current reconstruction especially around the structure boundaries. We propose a practical algorithm to improve TV-minimization based CT reconstruction on very few projection data. Based on the theory of compressed sensing, the L-0 norm approach is more desirable to further reduce the projection views. To overcome the computational difficulty of the non-convex optimization of the L-0 norm, we implement an adaptive weighting scheme to approximate the solution via a series of TV minimizations for practical use in CT reconstruction. The weight on TV is initialized as uniform ones, and is automatically changed based on the gradient of the reconstructed image from the previous iteration. The iteration stops when a small difference between the weighted TV values is observed on two consecutive reconstructed images. We evaluate the proposed algorithm on both a digital phantom and a physical phantom. Using 20 equiangular projections, our method reduces reconstruction errors in the conventional TV minimization by a factor of more than 5, with improved spatial resolution. By adaptively reweighting TV in iterative CT reconstruction, we successfully further reduce the projection number for the same or better image quality.

  2. Reconstructing misaligned x-ray CT data

    SciTech Connect

    Divin, C. J.

    2016-10-24

    Misalignment errors for x-ray computed tomography (CT) systems can manifest as artifacts and a loss of spatial and contrast resolution. To mitigate artifacts, significant effort is taken to determine the system geometry and minimizing any residual error in the system alignment. This project improved our ability to post-correct data which was acquired on a misaligned CT system.

  3. Initial analysis of the middle problem in CT image reconstruction.

    PubMed

    Yang, Jiansheng; Yu, Hengyong; Wang, Ge

    2017-04-05

    The interior and exterior problems have been extensively studied in the field of reconstruction of computed tomography (CT) images, which lead to important theoretical and practical results. In this study, we formulate a middle problem of CT image reconstruction, which is more challenging than either the interior or exterior problems. In the middle problem of CT image reconstruction, projection data are measured through and only through the middle dough-like region, so that each projection profile misses data not only internally but also on both sides. For an object with a radially symmetric exterior, we proved that the middle problem could be uniquely solved if the middle ring-shaped zone is piecewise constant or there is a known sub-region inside this middle region. Then, we designed and evaluated a POCS-based algorithm for middle tomography, which is to reconstruct a middle image only from the available data. Finally, the remaining issues are also discussed for further research.

  4. Limited-view Neutron CT Reconstruction with Sample Boundary

    NASA Astrophysics Data System (ADS)

    Wang, Hu; Zou, Yubin; Lu, Yuanrong; Guo, Zhiyu

    Reconstruction of limited-view CT is an ill-posed inversion problem. In order to suppress the artefacts and improve the image quality, it has been proved to be a good method toincorporatesome aprioriinformation of the sample(refers to as constraint in this paper) to the iterative process. In this paper, sample boundary is considered as a constraint and SART algorithm is chosen to test the performance of the constraint. Reconstructions from different number of projections of the famous Shepp-Logan head phantom with different levels of noise were simulated; projection data of a spark plug was acquired on the cold neutron CT platform of China Advanced Research Reactor (CARR) and the spark plug was reconstructed as well. Both the simulation and experimental results show that SART algorithm with sample boundary constraint leads to remarkable improvement of image quality and convergence speed for limited-view CT reconstruction when the noise level of projection data is less than 5%.

  5. Spectral CT metal artifact reduction with an optimization-based reconstruction algorithm

    NASA Astrophysics Data System (ADS)

    Gilat Schmidt, Taly; Barber, Rina F.; Sidky, Emil Y.

    2017-03-01

    Metal objects cause artifacts in computed tomography (CT) images. This work investigated the feasibility of a spectral CT method to reduce metal artifacts. Spectral CT acquisition combined with optimization-based reconstruction is proposed to reduce artifacts by modeling the physical effects that cause metal artifacts and by providing the flexibility to selectively remove corrupted spectral measurements in the spectral-sinogram space. The proposed Constrained `One-Step' Spectral CT Image Reconstruction (cOSSCIR) algorithm directly estimates the basis material maps while enforcing convex constraints. The incorporation of constraints on the reconstructed basis material maps is expected to mitigate undersampling effects that occur when corrupted data is excluded from reconstruction. The feasibility of the cOSSCIR algorithm to reduce metal artifacts was investigated through simulations of a pelvis phantom. The cOSSCIR algorithm was investigated with and without the use of a third basis material representing metal. The effects of excluding data corrupted by metal were also investigated. The results demonstrated that the proposed cOSSCIR algorithm reduced metal artifacts and improved CT number accuracy. For example, CT number error in a bright shading artifact region was reduced from 403 HU in the reference filtered backprojection reconstruction to 33 HU using the proposed algorithm in simulation. In the dark shading regions, the error was reduced from 1141 HU to 25 HU. Of the investigated approaches, decomposing the data into three basis material maps and excluding the corrupted data demonstrated the greatest reduction in metal artifacts.

  6. Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

    NASA Astrophysics Data System (ADS)

    McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

    2006-03-01

    To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the

  7. Thin slice three dimentional (3D) reconstruction versus CT 3D reconstruction of human breast cancer

    PubMed Central

    Zhang, Yi; Zhou, Yan; Yang, Xinhua; Tang, Peng; Qiu, Quanguang; Liang, Yong; Jiang, Jun

    2013-01-01

    Background & objectives: With improvement in the early diagnosis of breast cancer, breast conserving therapy (BCT) is being increasingly used. Precise preoperative evaluation of the incision margin is, therefore, very important. Utilizing three dimentional (3D) images in a preoperative evaluation for breast conserving surgery has considerable significance, but the currently 3D CT scan reconstruction commonly used has problems in accurately displaying breast cancer. Thin slice 3D reconstruction is also widely used now to delineate organs and tissues of breast cancers. This study was aimed to compare 3D CT with thin slice 3D reconstruction in breast cancer patients to find a better technique for accurate evaluation of breast cancer. Methods: A total of 16-slice spiral CT scans and 3D reconstructions were performed on 15 breast cancer patients. All patients had been treated with modified radical mastectomy; 2D and 3D images of breast and tumours were obtained. The specimens were fixed and sliced at 2 mm thickness to obtain serial thin slice images, and reconstructed using 3D DOCTOR software to gain 3D images. Results: Compared with 2D CT images, thin slice images showed more clearly the morphological characteristics of tumour, breast tissues and the margins of different tissues in each slice. After 3D reconstruction, the tumour shapes obtained by the two reconstruction methods were basically the same, but the thin slice 3D reconstruction showed the tumour margins more clearly. Interpretation & conclusions: Compared with 3D CT reconstruction, thin slice 3D reconstruction of breast tumour gave clearer images, which could provide guidance for the observation and application of CT 3D reconstructed images and contribute to the accurate evaluation of tumours using CT imaging technology. PMID:23481052

  8. Image Reconstruction for Hybrid True-Color Micro-CT

    PubMed Central

    Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

    2013-01-01

    X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid “true-color” micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose. PMID:22481806

  9. Image reconstruction for hybrid true-color micro-CT.

    PubMed

    Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

    2012-06-01

    X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid "true-color" micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a "color diffusion" phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose.

  10. Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

    SciTech Connect

    Matenine, Dmitri Mascolo-Fortin, Julia; Goussard, Yves

    2015-11-15

    Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can

  11. Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

    PubMed

    Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

    2015-11-01

    The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of

  12. Post-reconstruction non-local means filtering methods using CT side information for quantitative SPECT.

    PubMed

    Chun, Se Young; Fessler, Jeffrey A; Dewaraja, Yuni K

    2013-09-07

    Quantitative SPECT techniques are important for many applications including internal emitter therapy dosimetry where accurate estimation of total target activity and activity distribution within targets are both potentially important for dose–response evaluations. We investigated non-local means (NLM) post-reconstruction filtering for accurate I-131 SPECT estimation of both total target activity and the 3D activity distribution. We first investigated activity estimation versus number of ordered-subsets expectation–maximization (OSEM) iterations. We performed simulations using the XCAT phantom with tumors containing a uniform and a non-uniform activity distribution, and measured the recovery coefficient (RC) and the root mean squared error (RMSE) to quantify total target activity and activity distribution, respectively. We observed that using more OSEM iterations is essential for accurate estimation of RC, but may or may not improve RMSE. We then investigated various post-reconstruction filtering methods to suppress noise at high iteration while preserving image details so that both RC and RMSE can be improved. Recently, NLM filtering methods have shown promising results for noise reduction. Moreover, NLM methods using high-quality side information can improve image quality further. We investigated several NLM methods with and without CT side information for I-131 SPECT imaging and compared them to conventional Gaussian filtering and to unfiltered methods. We studied four different ways of incorporating CT information in the NLM methods: two known (NLM CT-B and NLM CT-M) and two newly considered (NLM CT-S and NLM CT-H). We also evaluated the robustness of NLM filtering using CT information to erroneous CT. NLM CT-S and NLM CT-H yielded comparable RC values to unfiltered images while substantially reducing RMSE. NLM CT-S achieved −2.7 to 2.6% increase of RC compared to no filtering and NLM CT-H yielded up to 6% decrease in RC while other methods yielded lower

  13. Post-reconstruction non-local means filtering methods using CT side information for quantitative SPECT

    NASA Astrophysics Data System (ADS)

    Chun, Se Young; Fessler, Jeffrey A.; Dewaraja, Yuni K.

    2013-09-01

    Quantitative SPECT techniques are important for many applications including internal emitter therapy dosimetry where accurate estimation of total target activity and activity distribution within targets are both potentially important for dose-response evaluations. We investigated non-local means (NLM) post-reconstruction filtering for accurate I-131 SPECT estimation of both total target activity and the 3D activity distribution. We first investigated activity estimation versus number of ordered-subsets expectation-maximization (OSEM) iterations. We performed simulations using the XCAT phantom with tumors containing a uniform and a non-uniform activity distribution, and measured the recovery coefficient (RC) and the root mean squared error (RMSE) to quantify total target activity and activity distribution, respectively. We observed that using more OSEM iterations is essential for accurate estimation of RC, but may or may not improve RMSE. We then investigated various post-reconstruction filtering methods to suppress noise at high iteration while preserving image details so that both RC and RMSE can be improved. Recently, NLM filtering methods have shown promising results for noise reduction. Moreover, NLM methods using high-quality side information can improve image quality further. We investigated several NLM methods with and without CT side information for I-131 SPECT imaging and compared them to conventional Gaussian filtering and to unfiltered methods. We studied four different ways of incorporating CT information in the NLM methods: two known (NLM CT-B and NLM CT-M) and two newly considered (NLM CT-S and NLM CT-H). We also evaluated the robustness of NLM filtering using CT information to erroneous CT. NLM CT-S and NLM CT-H yielded comparable RC values to unfiltered images while substantially reducing RMSE. NLM CT-S achieved -2.7 to 2.6% increase of RC compared to no filtering and NLM CT-H yielded up to 6% decrease in RC while other methods yielded lower RCs

  14. CEnPiT: Helical cardiac CT reconstruction

    SciTech Connect

    Bontus, Claas; Koken, Peter; Koehler, Thomas; Grass, Michael

    2006-08-15

    Computer tomography (CT) scanners with an increasing number of detector rows offer the potential of shorter scanning times. Nevertheless, the reconstruction problem becomes more challenging, since cone beam artifacts are likely to enter. Here, we consider helical cardiac CT. We analyze how a relationship can be established between exact reconstruction algorithms and the demand to perform a cardiac gating. Utilizing the redundancies requires the consideration of all kinds of Radon planes. For the reconstruction algorithm proposed here, we separate the data into two parts. The first part contains contributions of Radon planes, which are measured with a large number of redundancies. The second part contains the remaining contributions. As it turns out, the second part contributes rather to the low-frequency contents of trans-axial slices. Therefore, we propose to perform a gated back-projection only for the first part, while the second part is back-projected in an ungated way. Data from the complete source trajectory are employed in the reconstruction process in contrary to conventional helical cardiac reconstruction methods. Moreover, all different types of Radon planes are taken into account in the reconstruction, though an ECG-dependent cardiac gating is applied. The reconstruction results, which we present for clinical and simulated data, demonstrate the high potential of CEnPiT for helical cardiac CT with large cone angle systems.

  15. Iterative reconstruction methods in X-ray CT.

    PubMed

    Beister, Marcel; Kolditz, Daniel; Kalender, Willi A

    2012-04-01

    Iterative reconstruction (IR) methods have recently re-emerged in transmission x-ray computed tomography (CT). They were successfully used in the early years of CT, but given up when the amount of measured data increased because of the higher computational demands of IR compared to analytical methods. The availability of large computational capacities in normal workstations and the ongoing efforts towards lower doses in CT have changed the situation; IR has become a hot topic for all major vendors of clinical CT systems in the past 5 years. This review strives to provide information on IR methods and aims at interested physicists and physicians already active in the field of CT. We give an overview on the terminology used and an introduction to the most important algorithmic concepts including references for further reading. As a practical example, details on a model-based iterative reconstruction algorithm implemented on a modern graphics adapter (GPU) are presented, followed by application examples for several dedicated CT scanners in order to demonstrate the performance and potential of iterative reconstruction methods. Finally, some general thoughts regarding the advantages and disadvantages of IR methods as well as open points for research in this field are discussed.

  16. Limited view CT reconstruction and segmentation via constrained metric labeling

    PubMed Central

    Singh, Vikas; Mukherjee, Lopamudra; Dinu, Petru M.; Xu, Jinhui; Hoffmann, Kenneth R.

    2008-01-01

    This paper proposes a new discrete optimization framework for tomographic reconstruction and segmentation of CT volumes when only a few projection views are available. The problem has important clinical applications in coronary angiographic imaging. We first show that the limited view reconstruction and segmentation problem can be formulated as a “constrained” version of the metric labeling problem. This lays the groundwork for a linear programming framework that brings metric labeling classification and classical algebraic tomographic reconstruction (ART) together in a unified model. If the imaged volume is known to be comprised of a finite set of attenuation coefficients (a realistic assumption), given a regular limited view reconstruction, we view it as a task of voxels reassignment subject to maximally maintaining consistency with the input reconstruction and the objective of ART simultaneously. The approach can reliably reconstruct (or segment) volumes with several multiple contrast objects. We present evaluations using experiments on cone beam computed tomography. PMID:19802346

  17. A data-driven regularization strategy for statistical CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Badea, C. T.

    2017-03-01

    There is an unmet need for CT image reconstruction algorithms that reliably provide diagnostic image quality at reduced radiation dose. Toward this end, we integrate a state-of-the-art statistical reconstruction algorithm, ordered subsets, and separable quadratic surrogates (OS-SQS) accelerated with Nesterov's method, with our own data-driven regularization strategy using the split Bregman method. The regularization enforces intensity-gradient sparsity by minimizing bilateral total variation through the application of bilateral filtration. Adding to the advantages of statistical reconstruction, our implementation of bilateral filtration dynamically varies the regularization strength based on the noise level algorithmically measured within the data, accommodating variations in patient size and photon flux. We refer to this modified form of OS-SQS as OS-SQS with bilateral filtration (OS-SQS-BF), and we apply it to reconstruct clinical, helical CT data provided to us as part of the Low Dose CT Grand Challenge. Specifically, we evaluate OS-SQS-BF for quarter-dose statistical reconstruction and compare its performance with quarter-dose and full-dose filtered backprojection reconstruction. We present results for both the American College of Radiology (ACR) phantom and an abdominal CT scan. Our algorithm reduces noise by approximately 52% relative to filtered backprojection in the ACR phantom, while maintaining contrast and spatial-resolution performance relative to commercial filtered backprojection reconstruction. The quarter-dose scan for the abdominal data set confirmed the identification of 3 liver lesions when using OS-SQS-BF. The reconstruction time is a limitation that we will address in the future.

  18. Tensor decomposition and nonlocal means based spectral CT reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Yanbo; Yu, Hengyong

    2016-10-01

    As one of the state-of-the-art detectors, photon counting detector is used in spectral CT to classify the received photons into several energy channels and generate multichannel projection simultaneously. However, the projection always contains severe noise due to the low counts in each energy channel. How to reconstruct high-quality images from photon counting detector based spectral CT is a challenging problem. It is widely accepted that there exists self-similarity over the spatial domain in a CT image. Moreover, because a multichannel CT image is obtained from the same object at different energy, images among channels are highly correlated. Motivated by these two characteristics of the spectral CT, we employ tensor decomposition and nonlocal means methods for spectral CT iterative reconstruction. Our method includes three basic steps. First, each channel image is updated by using the OS-SART. Second, small 3D volumetric patches (tensor) are extracted from the multichannel image, and higher-order singular value decomposition (HOSVD) is performed on each tensor, which can help to enhance the spatial sparsity and spectral correlation. Third, in order to employ the self-similarity in CT images, similar patches are grouped to reduce noise using the nonlocal means method. These three steps are repeated alternatively till the stopping criteria are met. The effectiveness of the developed algorithm is validated on both numerically simulated and realistic preclinical datasets. Our results show that the proposed method achieves promising performance in terms of noise reduction and fine structures preservation.

  19. Parametric boundary reconstruction algorithm for industrial CT metrology application.

    PubMed

    Yin, Zhye; Khare, Kedar; De Man, Bruno

    2009-01-01

    High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly

  20. Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Eck, Brendan L.; Fahmi, Rachid; Fuqua, Christopher; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

    2015-03-01

    Dynamic myocardial CT perfusion (CTP) can provide quantitative functional information for the assessment of coronary artery disease. However, x-ray dose in dynamic CTP is high, typically from 10mSv to >20mSv. We compared the dose reduction potential of advanced iterative reconstruction, Iterative Model Reconstruction (IMR, Philips Healthcare, Cleveland, Ohio) to hybrid iterative reconstruction (iDose4) and filtered back projection (FBP). Dynamic CTP scans were obtained using a porcine model with balloon-induced ischemia in the left anterior descending coronary artery to prescribed fractional flow reserve values. High dose dynamic CTP scans were acquired at 100kVp/100mAs with effective dose of 23mSv. Low dose scans at 75mAs, 50mAs, and 25mAs were simulated by adding x-ray quantum noise and detector electronic noise to the projection space data. Images were reconstructed with FBP, iDose4, and IMR at each dose level. Image quality in static CTP images was assessed by SNR and CNR. Blood flow was obtained using a dynamic CTP analysis pipeline and blood flow image quality was assessed using flow-SNR and flow-CNR. IMR showed highest static image quality according to SNR and CNR. Blood flow in FBP was increasingly over-estimated at reduced dose. Flow was more consistent for iDose4 from 100mAs to 50mAs, but was over-estimated at 25mAs. IMR was most consistent from 100mAs to 25mAs. Static images and flow maps for 100mAs FBP, 50mAs iDose4, and 25mAs IMR showed comparable, clear ischemia, CNR, and flow-CNR values. These results suggest that IMR can enable dynamic CTP at significantly reduced dose, at 5.8mSv or 25% of the comparable 23mSv FBP protocol.

  1. Volume estimation of multi-density nodules with thoracic CT

    NASA Astrophysics Data System (ADS)

    Gavrielides, Marios A.; Li, Qin; Zeng, Rongping; Myers, Kyle J.; Sahiner, Berkman; Petrick, Nicholas

    2014-03-01

    The purpose of this work was to quantify the effect of surrounding density on the volumetric assessment of lung nodules in a phantom CT study. Eight synthetic multidensity nodules were manufactured by enclosing spherical cores in larger spheres of double the diameter and with a different uniform density. Different combinations of outer/inner diameters (20/10mm, 10/5mm) and densities (100HU/-630HU, 10HU/- 630HU, -630HU/100HU, -630HU/-10HU) were created. The nodules were placed within an anthropomorphic phantom and scanned with a 16-detector row CT scanner. Ten repeat scans were acquired using exposures of 20, 100, and 200mAs, slice collimations of 16x0.75mm and 16x1.5mm, and pitch of 1.2, and were reconstructed with varying slice thicknesses (three for each collimation) using two reconstruction filters (medium and standard). The volumes of the inner nodule cores were estimated from the reconstructed CT data using a matched-filter approach with templates modeling the characteristics of the multi-density objects. Volume estimation of the inner nodule was assessed using percent bias (PB) and the standard deviation of percent error (SPE). The true volumes of the inner nodules were measured using micro CT imaging. Results show PB values ranging from -12.4 to 2.3% and SPE values ranging from 1.8 to 12.8%. This study indicates that the volume of multi-density nodules can be measured with relatively small percent bias (on the order of +/-12% or less) when accounting for the properties of surrounding densities. These findings can provide valuable information for understanding bias and variability in clinical measurements of nodules that also include local biological changes such as inflammation and necrosis.

  2. Algebraic reconstruction techniques in CT and their implementation

    NASA Astrophysics Data System (ADS)

    Sun, Fengrong; Liu, Jiren; Zhu, Benren

    2001-09-01

    In the paper, we analyze comprehensively the mathematics of the Algebraic Reconstruction Techniques (ART) in the Computerized Tomography (CT), obtain some illumining conclusions, and then we design the procedure of ART simulation. The experiment result is also presented in the paper.

  3. Tomographic image reconstruction via estimation of sparse unidirectional gradients.

    PubMed

    Polak, Adam G; Mroczka, Janusz; Wysoczański, Dariusz

    2017-02-01

    Since computed tomography (CT) was developed over 35 years ago, new mathematical ideas and computational algorithms have been continuingly elaborated to improve the quality of reconstructed images. In recent years, a considerable effort can be noticed to apply the sparse solution of underdetermined system theory to the reconstruction of CT images from undersampled data. Its significance stems from the possibility of obtaining good quality CT images from low dose projections. Among diverse approaches, total variation (TV) minimizing 2D gradients of an image, seems to be the most popular method. In this paper, a new method for CT image reconstruction via sparse gradients estimation (SGE), is proposed. It consists in estimating 1D gradients specified in four directions using the iterative reweighting algorithm. To investigate its properties and to compare it with TV and other related methods, numerical simulations were performed according to the Monte Carlo scheme, using the Shepp-Logan and more realistic brain phantoms scanned at 9-60 directions in the range from 0 to 179°, with measurement data disturbed by additive Gaussians noise characterized by the relative level of 0.1%, 0.2%, 0.5%, 1%, 2% and 5%. The accuracy of image reconstruction was assessed in terms of the relative root-mean-square (RMS) error. The results show that the proposed SGE algorithm has returned more accurate images than TV for the cases fulfilling the sparsity conditions. Particularly, it preserves sharp edges of regions representing different tissues or organs and yields images of much better quality reconstructed from a small number of projections disturbed by relatively low measurement noise.

  4. Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

    2015-09-01

    For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose

  5. Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms.

    PubMed

    Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M; Asma, Evren; Kinahan, Paul E; De Man, Bruno

    2015-10-07

    For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition.We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 s. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.043 75 mAs, were investigated. Both the analytical Feldkamp, Davis and Kress (FDK) algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality.With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels

  6. Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms

    PubMed Central

    Rui, Xue; Cheng, Lishui; Long, Yong; Fu, Lin; Alessio, Adam M.; Asma, Evren; Kinahan, Paul E.; De Man, Bruno

    2015-01-01

    For PET/CT systems, PET image reconstruction requires corresponding CT images for anatomical localization and attenuation correction. In the case of PET respiratory gating, multiple gated CT scans can offer phase-matched attenuation and motion correction, at the expense of increased radiation dose. We aim to minimize the dose of the CT scan, while preserving adequate image quality for the purpose of PET attenuation correction by introducing sparse view CT data acquisition. Methods We investigated sparse view CT acquisition protocols resulting in ultra-low dose CT scans designed for PET attenuation correction. We analyzed the tradeoffs between the number of views and the integrated tube current per view for a given dose using CT and PET simulations of a 3D NCAT phantom with lesions inserted into liver and lung. We simulated seven CT acquisition protocols with {984, 328, 123, 41, 24, 12, 8} views per rotation at a gantry speed of 0.35 seconds. One standard dose and four ultra-low dose levels, namely, 0.35 mAs, 0.175 mAs, 0.0875 mAs, and 0.04375 mAs, were investigated. Both the analytical FDK algorithm and the Model Based Iterative Reconstruction (MBIR) algorithm were used for CT image reconstruction. We also evaluated the impact of sinogram interpolation to estimate the missing projection measurements due to sparse view data acquisition. For MBIR, we used a penalized weighted least squares (PWLS) cost function with an approximate total-variation (TV) regularizing penalty function. We compared a tube pulsing mode and a continuous exposure mode for sparse view data acquisition. Global PET ensemble root-mean-squares-error (RMSE) and local ensemble lesion activity error were used as quantitative evaluation metrics for PET image quality. Results With sparse view sampling, it is possible to greatly reduce the CT scan dose when it is primarily used for PET attenuation correction with little or no measureable effect on the PET image. For the four ultra-low dose levels

  7. Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

    PubMed

    Li, Liang; Wang, Bigong; Wang, Ge

    2016-01-01

    In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

  8. Developing population estimates for dose reconstruction projects

    SciTech Connect

    Beck, D.M. )

    1991-01-01

    The Hanford Environmental Dose Reconstruction (HEDR) Project was established in 1987 to estimate radiation doses that people received from nuclear operations at the Hanford site since 1944. To achieve this objective, demographic information was developed that describes the study population in enough detail to allow researchers to identify potentially exposed groups and the number of people in each of those groups. This type of information is central to most dose reconstruction projects. The purpose of this paper is to detail how historical population estimates can be reconstructed in a reliable manner by comparing results using three different estimation methods.

  9. Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction.

    PubMed

    Grosser, Oliver S; Wybranski, Christian; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Pech, Maciej; Amthauer, Holger; Ricke, Jens

    2017-09-01

    The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p < 0.0001). Noise and readers' confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. • CTF is performed for image guidance in interventional radiology. • Patient exposure was estimated from DLP documented by the CT. • Iterative CT reconstruction is appropriate to reduce image noise in CTF. • Using iterative CT reconstruction, the effective dose was significantly reduced in abdominal interventions.

  10. Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

    PubMed Central

    Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Asma, Evren; Kinahan, Paul E.

    2015-01-01

    Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction was modeled as a Poisson log-likelihood with prior terms consisting of quadratic (Q) and mixture (M) distributions. The attenuation map is assumed to have values in 4 clusters: air+background, lung, soft tissue, and bone. Under this assumption, the MP was a mixture probability density function consisting of one exponential and three Gaussian distributions. The relative proportion of each cluster was jointly estimated during each voxel update of direct iterative coordinate decent (dICD) method. Noise-free data were generated from NCAT phantom and Poisson noise was added. Reconstruction with FBP (ramp filter) was performed on the noise-free (ground truth) and noisy data. For the noisy data, dICD reconstruction was performed with the combination of different prior strength parameters (β and γ) of Q- and M-penalties. The combined quadratic and mixture penalties reduces the RMSE by 18.7% compared to post-smoothed iterative reconstruction and only 0.7% compared to quadratic alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of quadratic and mixture priors offers regularization of both variance and bias and is a potential method to derive attenuation maps with negligible patient dose. However, the small improvement in quantitative accuracy relative to the substantial increase in algorithm complexity does not currently justify the use of mixture-based PET attenuation priors for reconstruction of CT

  11. Efficient iterative image reconstruction algorithm for dedicated breast CT

    NASA Astrophysics Data System (ADS)

    Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

    2016-03-01

    Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

  12. Spectrotemporal CT data acquisition and reconstruction at low dose

    SciTech Connect

    Clark, Darin P.; Badea, Cristian T.; Lee, Chang-Lung; Kirsch, David G.

    2015-11-15

    Purpose: X-ray computed tomography (CT) is widely used, both clinically and preclinically, for fast, high-resolution anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. The authors propose and demonstrate a projection acquisition and reconstruction strategy for 5D CT (3D + dual energy + time) which recovers spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. Methods: The authors approach the 5D reconstruction problem within the framework of low-rank and sparse matrix decomposition. Unlike previous work on rank-sparsity constrained CT reconstruction, the authors establish an explicit rank-sparse signal model to describe the spectral and temporal dimensions. The spectral dimension is represented as a well-sampled time and energy averaged image plus regularly undersampled principal components describing the spectral contrast. The temporal dimension is represented as the same time and energy averaged reconstruction plus contiguous, spatially sparse, and irregularly sampled temporal contrast images. Using a nonlinear, image domain filtration approach, the authors refer to as rank-sparse kernel regression, the authors transfer image structure from the well-sampled time and energy averaged reconstruction to the spectral and temporal contrast images. This regularization strategy strictly constrains the reconstruction problem while approximately separating the temporal and spectral dimensions. Separability results in a highly compressed representation for the 5D data in which projections are shared between the temporal and spectral reconstruction subproblems, enabling substantial undersampling. The authors solved the 5D reconstruction

  13. Fast reconstruction of low dose proton CT by sinogram interpolation

    NASA Astrophysics Data System (ADS)

    Hansen, David C.; Sangild Sørensen, Thomas; Rit, Simon

    2016-08-01

    Proton computed tomography (CT) has been demonstrated as a promising image modality in particle therapy planning. It can reduce errors in particle range calculations and consequently improve dose calculations. Obtaining a high imaging resolution has traditionally required computationally expensive iterative reconstruction techniques to account for the multiple scattering of the protons. Recently, techniques for direct reconstruction have been developed, but these require a higher imaging dose than the iterative methods. No previous work has compared the image quality of the direct and the iterative methods. In this article, we extend the methodology for direct reconstruction to be applicable for low imaging doses and compare the obtained results with three state-of-the-art iterative algorithms. We find that the direct method yields comparable resolution and image quality to the iterative methods, even at 1 mSv dose levels, while yielding a twentyfold speedup in reconstruction time over previously published iterative algorithms.

  14. Joint regularization for spectro-temporal CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Badea, C. T.

    2016-03-01

    X-ray CT is widely used, both clinically and preclinically, for fast, high-resolution, anatomic imaging; however, compelling opportunities exist to expand its use in functional imaging applications. For instance, spectral information combined with nanoparticle contrast agents enables quantification of tissue perfusion levels, while temporal information details cardiac and respiratory dynamics. In previous work, we proposed and demonstrated a projection acquisition and reconstruction strategy for 5D CT (3D + dual-energy + time) which recovered spectral and temporal information without substantially increasing radiation dose or sampling time relative to anatomic imaging protocols. The approach relied on the approximate separability of the temporal and spectral reconstruction sub-problems, which enabled substantial projection undersampling and effective regularization. Here, we extend this previous work to more general, nonseparable 5D CT reconstruction cases (3D + muti-energy + time) with applicability to K-edge imaging of exogenous contrast agents. We apply the newly proposed algorithm in phantom simulations using a realistic system and noise model for a photon counting x-ray detector with six energy thresholds. The MOBY mouse phantom used contains realistic concentrations of iodine, gold, and calcium in water. Relative to weighted least-squares reconstruction, the proposed 5D reconstruction algorithm improved reconstruction and material decomposition accuracy by 3-18 times. Furthermore, by exploiting joint, low rank image structure between time points and energies, ~80 HU of contrast associated with the Kedge of gold and ~35 HU of contrast associated with the blood pool and myocardium were recovered from more than 400 HU of noise.

  15. CT x-ray tube voltage optimisation and image reconstruction evaluation using visual grading analysis

    NASA Astrophysics Data System (ADS)

    Zheng, Xiaoming; Kim, Ted M.; Davidson, Rob; Lee, Seongju; Shin, Cheongil; Yang, Sook

    2014-03-01

    The purposes of this work were to find an optimal x-ray voltage for CT imaging and to determine the diagnostic effectiveness of image reconstruction techniques by using the visual grading analysis (VGA). Images of the PH-5 CT abdomen phantom (Kagaku Co, Kyoto) were acquired by the Toshiba Aquillion One 320 slices CT system with various exposures (from 10 to 580 mAs) under different tube peak voltages (80, 100 and 120 kVp). The images were reconstructed by employing the FBP and the AIDR 3D iterative reconstructions with Mild, Standard and Strong FBP blending. Image quality was assessed by measuring noise, contrast to noise ratio and human observer's VGA scores. The CT dose index CTDIv was obtained from the values displayed on the images. The best fit for the curves of the image quality VGA vs dose CTDIv is a logistic function from the SPSS estimation. A threshold dose Dt is defined as the CTDIv at the just acceptable for diagnostic image quality and a figure of merit (FOM) is defined as the slope of the standardised logistic function. The Dt and FOM were found to be 5.4, 8.1 and 9.1 mGy and 0.47, 0.51 and 0.38 under the tube voltages of 80, 100 and 120 kVp, respectively, from images reconstructed by the FBP technique. The Dt and FOM values were lower from the images reconstructed by the AIDR 3D in comparison with the FBP technique. The optimal xray peak voltage for the imaging of the PH-5 abdomen phantom by the Aquillion One CT system was found to be at 100 kVp. The images reconstructed by the FBP are more diagnostically effective than that by the AIDR 3D but with a higher dose Dt to the patients.

  16. Superiorization-based multi-energy CT image reconstruction

    NASA Astrophysics Data System (ADS)

    Yang, Q.; Cong, W.; Wang, G.

    2017-04-01

    The recently-developed superiorization approach is efficient and robust for solving various constrained optimization problems. This methodology can be applied to multi-energy CT image reconstruction with the regularization in terms of the prior rank, intensity and sparsity model (PRISM). In this paper, we propose a superiorized version of the simultaneous algebraic reconstruction technique (SART) based on the PRISM model. Then, we compare the proposed superiorized algorithm with the Split-Bregman algorithm in numerical experiments. The results show that both the Superiorized-SART and the Split-Bregman algorithms generate good results with weak noise and reduced artefacts.

  17. Endoscopic-CT: learning-based photometric reconstruction for endoscopic sinus surgery

    NASA Astrophysics Data System (ADS)

    Reiter, A.; Leonard, S.; Sinha, A.; Ishii, M.; Taylor, R. H.; Hager, G. D.

    2016-03-01

    In this work we present a method for dense reconstruction of anatomical structures using white light endoscopic imagery based on a learning process that estimates a mapping between light reflectance and surface geometry. Our method is unique in that few unrealistic assumptions are considered (i.e., we do not assume a Lambertian reflectance model nor do we assume a point light source) and we learn a model on a per-patient basis, thus increasing the accuracy and extensibility to different endoscopic sequences. The proposed method assumes accurate video-CT registration through a combination of Structure-from-Motion (SfM) and Trimmed-ICP, and then uses the registered 3D structure and motion to generate training data with which to learn a multivariate regression of observed pixel values to known 3D surface geometry. We demonstrate with a non-linear regression technique using a neural network towards estimating depth images and surface normal maps, resulting in high-resolution spatial 3D reconstructions to an average error of 0.53mm (on the low side, when anatomy matches the CT precisely) to 1.12mm (on the high side, when the presence of liquids causes scene geometry that is not present in the CT for evaluation). Our results are exhibited on patient data and validated with associated CT scans. In total, we processed 206 total endoscopic images from patient data, where each image yields approximately 1 million reconstructed 3D points per image.

  18. [Volumetric CT scanning: 2D and 3D reconstruction].

    PubMed

    Ferretti, G-R; Jankowski, A

    2010-12-01

    This review aims to present the 2D and 3D reconstructions derived from high-resolution volume CT acquisitions and to illustrate their thoracic applications, as well as showing the interest and limitations of these techniques. We present new applications for computer-assisted detection (CAD) and tools for quantification of pulmonary lesions. Copyright © 2010 SPLF. Published by Elsevier Masson SAS. All rights reserved.

  19. Tensor-based Dictionary Learning for Spectral CT Reconstruction

    PubMed Central

    Zhang, Yanbo; Wang, Ge

    2016-01-01

    Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

  20. Towards an inline reconstruction architecture for micro-CT systems

    NASA Astrophysics Data System (ADS)

    Brasse, David; Humbert, Bernard; Mathelin, Carole; Rio, Marie-Christine; Guyonnet, Jean-Louis

    2005-12-01

    Recent developments in micro-CT have revolutionized the ability to examine in vivo living experimental animal models such as mouse with a spatial resolution less than 50 µm. The main requirements of in vivo imaging for biological researchers are a good spatial resolution, a low dose induced to the animal during the full examination and a reduced acquisition and reconstruction time for screening purposes. We introduce inline acquisition and reconstruction architecture to obtain in real time the 3D attenuation map of the animal fulfilling the three previous requirements. The micro-CT system is based on commercially available x-ray detector and micro-focus x-ray source. The reconstruction architecture is based on a cluster of PCs where a dedicated communication scheme combining serial and parallel treatments is implemented. In order to obtain high performance transmission rate between the detector and the reconstruction architecture, a dedicated data acquisition system is also developed. With the proposed solution, the time required to filter and backproject a projection of 2048 × 2048 pixels inside a volume of 140 mega voxels using the Feldkamp algorithm is similar to 500 ms, the time needed to acquire the same projection. Patent no. FR 05 02564 deposited 15 March 2005.

  1. Gamma regularization based reconstruction for low dose CT.

    PubMed

    Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis

    2015-09-07

    Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution is flexible and provides a good balance between the regularizations based on l0-norm and l1-norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other norms.

  2. Filtered back-projection reconstruction for attenuation proton CT along most likely paths.

    PubMed

    Quiñones, C T; Létang, J M; Rit, S

    2016-05-07

    This work investigates the attenuation of a proton beam to reconstruct the map of the linear attenuation coefficient of a material which is mainly caused by the inelastic interactions of protons with matter. Attenuation proton computed tomography (pCT) suffers from a poor spatial resolution due to multiple Coulomb scattering (MCS) of protons in matter, similarly to the conventional energy-loss pCT. We therefore adapted a recent filtered back-projection algorithm along the most likely path (MLP) of protons for energy-loss pCT (Rit et al 2013) to attenuation pCT assuming a pCT scanner that can track the position and the direction of protons before and after the scanned object. Monte Carlo simulations of pCT acquisitions of density and spatial resolution phantoms were performed to characterize the new algorithm using Geant4 (via Gate). Attenuation pCT assumes an energy-independent inelastic cross-section, and the impact of the energy dependence of the inelastic cross-section below 100 MeV showed a capping artifact when the residual energy was below 100 MeV behind the object. The statistical limitation has been determined analytically and it was found that the noise in attenuation pCT images is 411 times and 278 times higher than the noise in energy-loss pCT images for the same imaging dose at 200 MeV and 300 MeV, respectively. Comparison of the spatial resolution of attenuation pCT images with a conventional straight-line path binning showed that incorporating the MLP estimates during reconstruction improves the spatial resolution of attenuation pCT. Moreover, regardless of the significant noise in attenuation pCT images, the spatial resolution of attenuation pCT was better than that of conventional energy-loss pCT in some studied situations thanks to the interplay of MCS and attenuation known as the West-Sherwood effect.

  3. Filtered back-projection reconstruction for attenuation proton CT along most likely paths

    NASA Astrophysics Data System (ADS)

    Quiñones, C. T.; Létang, J. M.; Rit, S.

    2016-05-01

    This work investigates the attenuation of a proton beam to reconstruct the map of the linear attenuation coefficient of a material which is mainly caused by the inelastic interactions of protons with matter. Attenuation proton computed tomography (pCT) suffers from a poor spatial resolution due to multiple Coulomb scattering (MCS) of protons in matter, similarly to the conventional energy-loss pCT. We therefore adapted a recent filtered back-projection algorithm along the most likely path (MLP) of protons for energy-loss pCT (Rit et al 2013) to attenuation pCT assuming a pCT scanner that can track the position and the direction of protons before and after the scanned object. Monte Carlo simulations of pCT acquisitions of density and spatial resolution phantoms were performed to characterize the new algorithm using Geant4 (via Gate). Attenuation pCT assumes an energy-independent inelastic cross-section, and the impact of the energy dependence of the inelastic cross-section below 100 MeV showed a capping artifact when the residual energy was below 100 MeV behind the object. The statistical limitation has been determined analytically and it was found that the noise in attenuation pCT images is 411 times and 278 times higher than the noise in energy-loss pCT images for the same imaging dose at 200 MeV and 300 MeV, respectively. Comparison of the spatial resolution of attenuation pCT images with a conventional straight-line path binning showed that incorporating the MLP estimates during reconstruction improves the spatial resolution of attenuation pCT. Moreover, regardless of the significant noise in attenuation pCT images, the spatial resolution of attenuation pCT was better than that of conventional energy-loss pCT in some studied situations thanks to the interplay of MCS and attenuation known as the West-Sherwood effect.

  4. Point estimates in phylogenetic reconstructions

    PubMed Central

    Benner, Philipp; Bačák, Miroslav; Bourguignon, Pierre-Yves

    2014-01-01

    Motivation: The construction of statistics for summarizing posterior samples returned by a Bayesian phylogenetic study has so far been hindered by the poor geometric insights available into the space of phylogenetic trees, and ad hoc methods such as the derivation of a consensus tree makeup for the ill-definition of the usual concepts of posterior mean, while bootstrap methods mitigate the absence of a sound concept of variance. Yielding satisfactory results with sufficiently concentrated posterior distributions, such methods fall short of providing a faithful summary of posterior distributions if the data do not offer compelling evidence for a single topology. Results: Building upon previous work of Billera et al., summary statistics such as sample mean, median and variance are defined as the geometric median, Fréchet mean and variance, respectively. Their computation is enabled by recently published works, and embeds an algorithm for computing shortest paths in the space of trees. Studying the phylogeny of a set of plants, where several tree topologies occur in the posterior sample, the posterior mean balances correctly the contributions from the different topologies, where a consensus tree would be biased. Comparisons of the posterior mean, median and consensus trees with the ground truth using simulated data also reveals the benefits of a sound averaging method when reconstructing phylogenetic trees. Availability and implementation: We provide two independent implementations of the algorithm for computing Fréchet means, geometric medians and variances in the space of phylogenetic trees. TFBayes: https://github.com/pbenner/tfbayes, TrAP: https://github.com/bacak/TrAP. Contact: philipp.benner@mis.mpg.de PMID:25161244

  5. Iterative CT reconstruction using shearlet-based regularization

    NASA Astrophysics Data System (ADS)

    Vandeghinste, Bert; Goossens, Bart; Van Holen, Roel; Vanhove, Christian; Pizurica, Aleksandra; Vandenberghe, Stefaan; Staelens, Steven

    2012-03-01

    In computerized tomography, it is important to reduce the image noise without increasing the acquisition dose. Extensive research has been done into total variation minimization for image denoising and sparse-view reconstruction. However, TV minimization methods show superior denoising performance for simple images (with little texture), but result in texture information loss when applied to more complex images. Since in medical imaging, we are often confronted with textured images, it might not be beneficial to use TV. Our objective is to find a regularization term outperforming TV for sparse-view reconstruction and image denoising in general. A recent efficient solver was developed for convex problems, based on a split-Bregman approach, able to incorporate regularization terms different from TV. In this work, a proof-of-concept study demonstrates the usage of the discrete shearlet transform as a sparsifying transform within this solver for CT reconstructions. In particular, the regularization term is the 1-norm of the shearlet coefficients. We compared our newly developed shearlet approach to traditional TV on both sparse-view and on low-count simulated and measured preclinical data. Shearlet-based regularization does not outperform TV-based regularization for all datasets. Reconstructed images exhibit small aliasing artifacts in sparse-view reconstruction problems, but show no staircasing effect. This results in a slightly higher resolution than with TV-based regularization.

  6. Validity of Paranasal CT Image Reconstruction for Finite Element Models in Otorhinolaryngology

    NASA Astrophysics Data System (ADS)

    Kunkel, Maria Elizete; Moral, Analia I.; Tingelhoff, Kathrin; Bootz, Friedrich; Wahl, Friedrich

    The purpose was to evaluate an approach for use of segmented computed tomography images in volumetric estimation of the paranasal sinuses cavities. Four hundred and fifty-two CT images were processed with the software Amira™ 4.1. The images were obtained from a dummy human head, which is used to rehearse the movements of the surgeon during endoscope nasal surgery. The volumes of the frontal, maxillar, sphenoidal and ethmoidal sinuses were examined both by material injection and by 3D-reconstruction of CT images. The volumes of the paranasal cavities were all in the respective ranges compared with previous reports. The precise knowledge of the geometric configuration of the paranasal regions is necessary because reconstruction on the paranasal sinuses will be used for the creation of finite element models for Endonasal surgery simulations.

  7. Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

    NASA Astrophysics Data System (ADS)

    Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

    2016-02-01

    Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

  8. Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

    PubMed

    Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

    2014-12-01

    To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers

  9. Reconstruction of 4D-CT data sets acquired during free breathing for the analysis of respiratory motion

    NASA Astrophysics Data System (ADS)

    Ehrhardt, Jan; Werner, Rene; Frenzel, Thorsten; Säring, Dennis; Lu, Wei; Low, Daniel; Handels, Heinz

    2006-03-01

    Respiratory motion is a significant source of error in radiotherapy treatment planning. 4D-CT data sets can be useful to measure the impact of organ motion caused by breathing. But modern CT scanners can only scan a limited region of the body simultaneously and patients have to be scanned in segments consisting of multiple slices. For studying free breathing motion multislice CT scans can be collected simultaneously with digital spirometry over several breathing cycles. The 4D data set is assembled by sorting the free breathing multislice CT scans according to the couch position and the tidal volume. But artifacts can occur because there are no data segments for exactly the same tidal volume and all couch positions. We present an optical flow based method for the reconstruction of 4D-CT data sets from multislice CT scans, which are collected simultaneously with digital spirometry. The optical flow between the scans is estimated by a non-linear registration method. The calculated velocity field is used to reconstruct a 4D-CT data set by interpolating data at user-defined tidal volumes. By this technique, artifacts can be reduced significantly. The reconstructed 4D-CT data sets are used for studying inner organ motion during the respiratory cycle. The procedures described were applied to reconstruct 4D-CT data sets for four tumour patients who have been scanned during free breathing. The reconstructed 4D data sets were used to quantify organ displacements and to visualize the abdominothoracic organ motion.

  10. An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging.

    PubMed

    Van Eyndhoven, Geert; Batenburg, K Joost; Kazantsev, Daniil; Van Nieuwenhove, Vincent; Lee, Peter D; Dobson, Katherine J; Sijbers, Jan

    2015-11-01

    The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.

  11. On proton CT reconstruction using MVCT-converted virtual proton projections

    SciTech Connect

    Wang Dongxu; Mackie, T. Rockwell; Tome, Wolfgang A.

    2012-06-15

    . If these images are used for treatment planning, the average proton range uncertainty is estimated to be less than 1.5% for an imaging dose in the milligray range. Conclusions: The proposed method can be used to convert x-ray projections into virtual proton projections. The converted proton projections can be blended with existing proton projections or can be used solely for pCT reconstruction, addressing the range limit problem of pCT using current therapeutic proton machines.

  12. Investigation of statistical iterative reconstruction for dedicated breast CT

    PubMed Central

    Makeev, Andrey; Glick, Stephen J.

    2013-01-01

    Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue. Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters. Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved

  13. Investigation of statistical iterative reconstruction for dedicated breast CT

    SciTech Connect

    Makeev, Andrey; Glick, Stephen J.

    2013-08-15

    Purpose: Dedicated breast CT has great potential for improving the detection and diagnosis of breast cancer. Statistical iterative reconstruction (SIR) in dedicated breast CT is a promising alternative to traditional filtered backprojection (FBP). One of the difficulties in using SIR is the presence of free parameters in the algorithm that control the appearance of the resulting image. These parameters require tuning in order to achieve high quality reconstructions. In this study, the authors investigated the penalized maximum likelihood (PML) method with two commonly used types of roughness penalty functions: hyperbolic potential and anisotropic total variation (TV) norm. Reconstructed images were compared with images obtained using standard FBP. Optimal parameters for PML with the hyperbolic prior are reported for the task of detecting microcalcifications embedded in breast tissue.Methods: Computer simulations were used to acquire projections in a half-cone beam geometry. The modeled setup describes a realistic breast CT benchtop system, with an x-ray spectra produced by a point source and an a-Si, CsI:Tl flat-panel detector. A voxelized anthropomorphic breast phantom with 280 μm microcalcification spheres embedded in it was used to model attenuation properties of the uncompressed woman's breast in a pendant position. The reconstruction of 3D images was performed using the separable paraboloidal surrogates algorithm with ordered subsets. Task performance was assessed with the ideal observer detectability index to determine optimal PML parameters.Results: The authors' findings suggest that there is a preferred range of values of the roughness penalty weight and the edge preservation threshold in the penalized objective function with the hyperbolic potential, which resulted in low noise images with high contrast microcalcifications preserved. In terms of numerical observer detectability index, the PML method with optimal parameters yielded substantially improved

  14. CT reconstruction techniques for improved accuracy of lung CT airway measurement

    SciTech Connect

    Rodriguez, A.; Ranallo, F. N.; Judy, P. F.; Gierada, D. S.; Fain, S. B.

    2014-11-01

    Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

  15. CT reconstruction techniques for improved accuracy of lung CT airway measurement

    PubMed Central

    Rodriguez, A.; Ranallo, F. N.; Judy, P. F.; Gierada, D. S.; Fain, S. B.

    2014-01-01

    Purpose: To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose. Methods: Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12–100 mA s current–time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women’s Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error. Results: WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD

  16. Investigation of a one-step spectral CT reconstruction algorithm for direct inversion into basis material images

    NASA Astrophysics Data System (ADS)

    Gilat Schmidt, Taly; Sidky, Emil Y.

    2015-03-01

    Photon-counting detectors with pulse-height analysis have shown promise for improved spectral CT imaging. This study investigated a novel spectral CT reconstruction method that directly estimates basis-material images from the measured energy-bin data (i.e., `one-step' reconstruction). The proposed algorithm can incorporate constraints to stabilize the reconstruction and potentially reduce noise. The algorithm minimizes the error between the measured energy-bin data and the data estimated from the reconstructed basis images. A total variation (TV) constraint was also investigated for additional noise reduction. The proposed one-step algorithm was applied to simulated data of an anthropomorphic phantom with heterogeneous tissue composition. Reconstructed water, bone, and gadolinium basis images were compared for the proposed one-step algorithm and the conventional `two-step' method of decomposition followed by reconstruction. The unconstrained algorithm provided a 30% to 60% reduction in noise standard deviation compared to the two-step algorithm. The fTV =0.8 constraint provided a small reduction in noise (˜ 1%) compared to the unconstrained reconstruction. Images reconstructed with the fTV =0.5 constraint demonstrated 77% to 94% standard deviation reduction compared to the two-step reconstruction, however with increased blurring. There were no significant differences in the mean values reconstructed by the investigated algorithms. Overall, the proposed one-step spectral CT reconstruction algorithm provided three-material-decomposition basis images with reduced noise compared to the conventional two-step approach. When using a moderate TV constraint factor (fTV = 0.8), a 30%-60% reduction in noise standard deviation was achieved while preserving the edge profile for this simulated phantom.

  17. Test of 3D CT reconstructions by EM + TV algorithm from undersampled data

    SciTech Connect

    Evseev, Ivan; Ahmann, Francielle; Silva, Hamilton P. da

    2013-05-06

    Computerized tomography (CT) plays an important role in medical imaging for diagnosis and therapy. However, CT imaging is connected with ionization radiation exposure of patients. Therefore, the dose reduction is an essential issue in CT. In 2011, the Expectation Maximization and Total Variation Based Model for CT Reconstruction (EM+TV) was proposed. This method can reconstruct a better image using less CT projections in comparison with the usual filtered back projection (FBP) technique. Thus, it could significantly reduce the overall dose of radiation in CT. This work reports the results of an independent numerical simulation for cone beam CT geometry with alternative virtual phantoms. As in the original report, the 3D CT images of 128 Multiplication-Sign 128 Multiplication-Sign 128 virtual phantoms were reconstructed. It was not possible to implement phantoms with lager dimensions because of the slowness of code execution even by the CORE i7 CPU.

  18. Line Integral Alternating Minimization Algorithm for Dual-Energy X-Ray CT Image Reconstruction.

    PubMed

    Chen, Yaqi; O'Sullivan, Joseph A; Politte, David G; Evans, Joshua D; Han, Dong; Whiting, Bruce R; Williamson, Jeffrey F

    2016-02-01

    We propose a new algorithm, called line integral alternating minimization (LIAM), for dual-energy X-ray CT image reconstruction. Instead of obtaining component images by minimizing the discrepancy between the data and the mean estimates, LIAM allows for a tunable discrepancy between the basis material projections and the basis sinograms. A parameter is introduced that controls the size of this discrepancy, and with this parameter the new algorithm can continuously go from a two-step approach to the joint estimation approach. LIAM alternates between iteratively updating the line integrals of the component images and reconstruction of the component images using an image iterative deblurring algorithm. An edge-preserving penalty function can be incorporated in the iterative deblurring step to decrease the roughness in component images. Images from both simulated and experimentally acquired sinograms from a clinical scanner were reconstructed by LIAM while varying the regularization parameters to identify good choices. The results from the dual-energy alternating minimization algorithm applied to the same data were used for comparison. Using a small fraction of the computation time of dual-energy alternating minimization, LIAM achieves better accuracy of the component images in the presence of Poisson noise for simulated data reconstruction and achieves the same level of accuracy for real data reconstruction.

  19. CT Image Reconstruction from Sparse Projections Using Adaptive TpV Regularization

    PubMed Central

    Chen, Zijia; Zhou, Linghong

    2015-01-01

    Radiation dose reduction without losing CT image quality has been an increasing concern. Reducing the number of X-ray projections to reconstruct CT images, which is also called sparse-projection reconstruction, can potentially avoid excessive dose delivered to patients in CT examination. To overcome the disadvantages of total variation (TV) minimization method, in this work we introduce a novel adaptive TpV regularization into sparse-projection image reconstruction and use FISTA technique to accelerate iterative convergence. The numerical experiments demonstrate that the proposed method suppresses noise and artifacts more efficiently, and preserves structure information better than other existing reconstruction methods. PMID:26089962

  20. Task-based optimization of image reconstruction in breast CT

    NASA Astrophysics Data System (ADS)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2014-03-01

    We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

  1. A feature refinement approach for statistical interior CT reconstruction.

    PubMed

    Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

    2016-07-21

    Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

  2. A feature refinement approach for statistical interior CT reconstruction

    NASA Astrophysics Data System (ADS)

    Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong

    2016-07-01

    Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.

  3. Automatic estimation of detector radial position for contoured SPECT acquisition using CT images on a SPECT/CT system

    SciTech Connect

    Liu Ruijie Rachel; Erwin, William D.

    2006-08-15

    An algorithm was developed to estimate noncircular orbit (NCO) single-photon emission computed tomography (SPECT) detector radius on a SPECT/CT imaging system using the CT images, for incorporation into collimator resolution modeling for iterative SPECT reconstruction. Simulated male abdominal (arms up), male head and neck (arms down) and female chest (arms down) anthropomorphic phantom, and ten patient, medium-energy SPECT/CT scans were acquired on a hybrid imaging system. The algorithm simulated inward SPECT detector radial motion and object contour detection at each projection angle, employing the calculated average CT image and a fixed Hounsfield unit (HU) threshold. Calculated radii were compared to the observed true radii, and optimal CT threshold values, corresponding to patient bed and clothing surfaces, were found to be between -970 and -950 HU. The algorithm was constrained by the 45 cm CT field-of-view (FOV), which limited the detected radii to {<=}22.5 cm and led to occasional radius underestimation in the case of object truncation by CT. Two methods incorporating the algorithm were implemented: physical model (PM) and best fit (BF). The PM method computed an offset that produced maximum overlap of calculated and true radii for the phantom scans, and applied that offset as a calculated-to-true radius transformation. For the BF method, the calculated-to-true radius transformation was based upon a linear regression between calculated and true radii. For the PM method, a fixed offset of +2.75 cm provided maximum calculated-to-true radius overlap for the phantom study, which accounted for the camera system's object contour detect sensor surface-to-detector face distance. For the BF method, a linear regression of true versus calculated radius from a reference patient scan was used as a calculated-to-true radius transform. Both methods were applied to ten patient scans. For -970 and -950 HU thresholds, the combined overall average root-mean-square (rms) error

  4. Radiation Dose Reduction in Paranasal Sinus CT: With Feasibility of Iterative Reconstruction Technique.

    PubMed

    Bang, Minseo; Choi, Seong Hoon; Park, Jongha; Kang, Byeong Seong; Kwon, Woon Jung; Lee, Tae Hoon; Nam, Jung Gwon

    2016-12-01

    To (1) compare the radiation dose of low-dose computed tomography (CT) to that of standard-dose CT, (2) determine the minimum optimal radiation dose for use in patients who need endoscopic sinus surgery, and (3) assess the reliability of iterative model reconstruction. Prospective single-institution study. Tertiary care center. We recruited 48 adults with medically refractory sinusitis. Each patient underwent 4 scans with different CT parameters: 120 kV and 100 mAs (standard dose), 100 kV and 40 mAs (low dose), 100 kV and 20 mAs (very low dose), and 100 kV and 10 mAs (ultra-low dose). All CT scans were reconstructed via filtered back-projection, and ultra-low dose scans were additionally reconstructed through iterative model reconstruction. Radiation dose, image quality, and diagnostic performance were compared among the scans. Radiation doses decreased to 6% (ultra-low dose), 12% (very low dose), and 22% (low dose) of the standard-dose CT. The image quality of low-dose CT was similar to that of standard-dose CT. Ultra-low-dose CT with iterative model reconstruction was inferior to standard-dose CT for identifying anatomic structures, except for the optic nerve. All CT scans had 100% agreement for diagnosing rhinosinusitis. With low-dose CT, the radiation dose can be decreased to 22% of that of standard-dose CT without affecting the image quality. Low-dose CT can be considered the minimum optimal radiation for patients who need surgery. Iterative model reconstruction is not useful for assessing the anatomic details of the paranasal sinus on CT. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

  5. Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

    PubMed Central

    Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger

    2015-01-01

    Background Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images. Methodology/Principal Findings Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001). Conclusion/Significance In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality. PMID:26390216

  6. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    PubMed Central

    Eck, Brendan L.; Fahmi, Rachid; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Miao, Jun; Wilson, David L.

    2015-01-01

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, PC. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and

  7. Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

    SciTech Connect

    Eck, Brendan L.; Fahmi, Rachid; Miao, Jun; Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun; Wilson, David L.

    2015-10-15

    Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit

  8. Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra.

    PubMed

    Xu, S; Uneri, A; Khanna, A Jay; Siewerdsen, J H; Stayman, J W

    2017-04-21

    Metal artifacts can cause substantial image quality issues in computed tomography. This is particularly true in interventional imaging where surgical tools or metal implants are in the field-of-view. Moreover, the region-of-interest is often near such devices which is exactly where image quality degradations are largest. Previous work on known-component reconstruction (KCR) has shown the incorporation of a physical model (e.g. shape, material composition, etc) of the metal component into the reconstruction algorithm can significantly reduce artifacts even near the edge of a metal component. However, for such approaches to be effective, they must have an accurate model of the component that include energy-dependent properties of both the metal device and the CT scanner, placing a burden on system characterization and component material knowledge. In this work, we propose a modified KCR approach that adopts a mixed forward model with a polyenergetic model for the component and a monoenergetic model for the background anatomy. This new approach called Poly-KCR jointly estimates a spectral transfer function associated with known components in addition to the background attenuation values. Thus, this approach eliminates both the need to know component material composition a prior as well as the requirement for an energy-dependent characterization of the CT scanner. We demonstrate the efficacy of this novel approach and illustrate its improved performance over traditional and model-based iterative reconstruction methods in both simulation studies and in physical data including an implanted cadaver sample.

  9. Polyenergetic known-component CT reconstruction with unknown material compositions and unknown x-ray spectra

    NASA Astrophysics Data System (ADS)

    Xu, S.; Uneri, A.; Khanna, A. Jay; Siewerdsen, J. H.; Stayman, J. W.

    2017-04-01

    Metal artifacts can cause substantial image quality issues in computed tomography. This is particularly true in interventional imaging where surgical tools or metal implants are in the field-of-view. Moreover, the region-of-interest is often near such devices which is exactly where image quality degradations are largest. Previous work on known-component reconstruction (KCR) has shown the incorporation of a physical model (e.g. shape, material composition, etc) of the metal component into the reconstruction algorithm can significantly reduce artifacts even near the edge of a metal component. However, for such approaches to be effective, they must have an accurate model of the component that include energy-dependent properties of both the metal device and the CT scanner, placing a burden on system characterization and component material knowledge. In this work, we propose a modified KCR approach that adopts a mixed forward model with a polyenergetic model for the component and a monoenergetic model for the background anatomy. This new approach called Poly-KCR jointly estimates a spectral transfer function associated with known components in addition to the background attenuation values. Thus, this approach eliminates both the need to know component material composition a prior as well as the requirement for an energy-dependent characterization of the CT scanner. We demonstrate the efficacy of this novel approach and illustrate its improved performance over traditional and model-based iterative reconstruction methods in both simulation studies and in physical data including an implanted cadaver sample.

  10. Integration of prior CT into CBCT reconstruction for improved image quality via reconstruction of difference: first patient studies

    NASA Astrophysics Data System (ADS)

    Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster

    2017-03-01

    Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.

  11. Impact of the Adaptive Statistical Iterative Reconstruction Technique on Radiation Dose and Image Quality in Bone SPECT/CT.

    PubMed

    Sibille, Louis; Chambert, Benjamin; Alonso, Sandrine; Barrau, Corinne; D'Estanque, Emmanuel; Al Tabaa, Yassine; Collombier, Laurent; Demattei, Christophe; Kotzki, Pierre-Olivier; Boudousq, Vincent

    2016-07-01

    The purpose of this study was to compare a routine bone SPECT/CT protocol using CT reconstructed with filtered backprojection (FBP) with an optimized protocol using low-dose CT images reconstructed with adaptive statistical iterative reconstruction (ASiR). In this prospective study, enrolled patients underwent bone SPECT/CT, with 1 SPECT acquisition followed by 2 randomized CT acquisitions: FBP CT (FBP; noise index, 25) and ASiR CT (70% ASiR; noise index, 40). The image quality of both attenuation-corrected SPECT and CT images was visually (5-point Likert scale, 2 interpreters) and quantitatively (contrast ratio [CR] and signal-to-noise ratio [SNR]) estimated. The CT dose index volume, dose-length product, and effective dose were compared. Seventy-five patients were enrolled in the study. Quantitative attenuation-corrected SPECT evaluation showed no inferiority for contrast ratio and SNR issued from FBP CT or ASiR CT (respectively, 13.41 ± 7.83 vs. 13.45 ± 7.99 and 2.33 ± 0.83 vs. 2.32 ± 0.84). Qualitative image analysis showed no difference between attenuation-corrected SPECT images issued from FBP CT or ASiR CT for both interpreters (respectively, 3.5 ± 0.6 vs. 3.5 ± 0.6 and 3.6 ± 0.5 vs. 3.6 ± 0.5). Quantitative CT evaluation showed no inferiority for SNR between FBP and ASiR CT images (respectively, 0.93 ± 0.16 and 1.07 ± 0.17). Qualitative image analysis showed no quality difference between FBP and ASiR CT images for both interpreters (respectively, 3.8 ± 0.5 vs. 3.6 ± 0.5 and 4.0 ± 0.1 vs. 4.0 ± 0.2). Mean CT dose index volume, dose-length product, and effective dose for ASiR CT (3.0 ± 2.0 mGy, 148 ± 85 mGy⋅cm, and 2.2 ± 1.3 mSv) were significantly lower than for FBP CT (8.5 ± 3.7 mGy, 365 ± 160 mGy⋅cm, and 5.5 ± 2.4 mSv). The use of 70% ASiR blending in bone SPECT/CT can reduce the CT radiation dose by 60%, with no sacrifice in attenuation-corrected SPECT and CT image quality, compared with the conventional protocol using FBP CT

  12. Statistical modeling challenges in model-based reconstruction for x-ray CT

    NASA Astrophysics Data System (ADS)

    Zhang, Ruoqiao; Chang, Aaron; Thibault, Jean-Baptiste; Sauer, Ken; Bouman, Charles

    2013-02-01

    Model- based iterative reconstruction (MBIR) is increasingly widely applied as an improvement over conventional, deterministic methods of image reconstruction in X-ray CT. A primary advantage of MBIR is potentially dras­ tically reduced dosage without diagnostic quality loss. Early success of the method has naturally led to growing numbers of scans at very low dose, presenting data which does not match well the simple statistical models heretofore considered adequate. This paper addresses several issues arising in limiting cases which call for refine­ ment of standard data models. The emergence of electronic noise as a significant contributor to uncertainty, and bias of sinogram values in photon-starved measurements are demonstrated to be important modeling problems in this new environment. We present also possible ameliorations to several of these low-dosage estimation issues.

  13. Optimal reconstruction and quantitative image features for computer-aided diagnosis tools for breast CT.

    PubMed

    Lee, Juhun; Nishikawa, Robert M; Reiser, Ingrid; Boone, John M

    2017-05-01

    The purpose of this study is to determine the optimal representative reconstruction and quantitative image feature set for a computer-aided diagnosis (CADx) scheme for dedicated breast computer tomography (bCT). We used 93 bCT scans that contain 102 breast lesions (62 malignant, 40 benign). Using an iterative image reconstruction (IIR) algorithm, we created 37 reconstructions with different image appearances for each case. In addition, we added a clinical reconstruction for comparison purposes. We used image sharpness, determined by the gradient of gray value in a parenchymal portion of the reconstructed breast, as a surrogate measure of the image qualities/appearances for the 38 reconstructions. After segmentation of the breast lesion, we extracted 23 quantitative image features. Using leave-one-out-cross-validation (LOOCV), we conducted the feature selection, classifier training, and testing. For this study, we used the linear discriminant analysis classifier. Then, we selected the representative reconstruction and feature set for the classifier with the best diagnostic performance among all reconstructions and feature sets. Then, we conducted an observer study with six radiologists using a subset of breast lesions (N = 50). Using 1000 bootstrap samples, we compared the diagnostic performance of the trained classifier to those of the radiologists. The diagnostic performance of the trained classifier increased as the image sharpness of a given reconstruction increased. Among combinations of reconstructions and quantitative image feature sets, we selected one of the sharp reconstructions and three quantitative image feature sets with the first three highest diagnostic performances under LOOCV as the representative reconstruction and feature set for the classifier. The classifier on the representative reconstruction and feature set achieved better diagnostic performance with an area under the ROC curve (AUC) of 0.94 (95% CI = [0.81, 0.98]) than those of the

  14. Deformable known component model-based reconstruction for coronary CT angiography

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Tilley, S.; Xu, S.; Mathews, A.; McVeigh, E. R.; Stayman, J. W.

    2017-03-01

    Purpose: Atherosclerosis detection remains challenging in coronary CT angiography for patients with cardiac implants. Pacing electrodes of a pacemaker or lead components of a defibrillator can create substantial blooming and streak artifacts in the heart region, severely hindering the visualization of a plaque of interest. We present a novel reconstruction method that incorporates a deformable model for metal leads to eliminate metal artifacts and improve anatomy visualization even near the boundary of the component. Methods: The proposed reconstruction method, referred as STF-dKCR, includes a novel parameterization of the component that integrates deformation, a 3D-2D preregistration process that estimates component shape and position, and a polyenergetic forward model for x-ray propagation through the component where the spectral properties are jointly estimated. The methodology was tested on physical data of a cardiac phantom acquired on a CBCT testbench. The phantom included a simulated vessel, a metal wire emulating a pacing lead, and a small Teflon sphere attached to the vessel wall, mimicking a calcified plaque. The proposed method was also compared to the traditional FBP reconstruction and an interpolation-based metal correction method (FBP-MAR). Results: Metal artifacts presented in standard FBP reconstruction were significantly reduced in both FBP-MAR and STF- dKCR, yet only the STF-dKCR approach significantly improved the visibility of the small Teflon target (within 2 mm of the metal wire). The attenuation of the Teflon bead improved to 0.0481 mm-1 with STF-dKCR from 0.0166 mm-1 with FBP and from 0.0301 mm-1 with FBP-MAR - much closer to the expected 0.0414 mm-1. Conclusion: The proposed method has the potential to improve plaque visualization in coronary CT angiography in the presence of wire-shaped metal components.

  15. WE-G-18A-03: Cone Artifacts Correction in Iterative Cone Beam CT Reconstruction

    SciTech Connect

    Yan, H; Folkerts, M; Jiang, S; Jia, X; Wang, X; Bai, T; Lu, W

    2014-06-15

    Purpose: For iterative reconstruction (IR) in cone-beam CT (CBCT) imaging, data truncation along the superior-inferior (SI) direction causes severe cone artifacts in the reconstructed CBCT volume images. Not only does it reduce the effective SI coverage of the reconstructed volume, it also hinders the IR algorithm convergence. This is particular a problem for regularization based IR, where smoothing type regularization operations tend to propagate the artifacts to a large area. It is our purpose to develop a practical cone artifacts correction solution. Methods: We found it is the missing data residing in the truncated cone area that leads to inconsistency between the calculated forward projections and measured projections. We overcome this problem by using FDK type reconstruction to estimate the missing data and design weighting factors to compensate the inconsistency caused by the missing data. We validate the proposed methods in our multi-GPU low-dose CBCT reconstruction system on multiple patients' datasets. Results: Compared to the FDK reconstruction with full datasets, while IR is able to reconstruct CBCT images using a subset of projection data, the severe cone artifacts degrade overall image quality. For head-neck case under a full-fan mode, 13 out of 80 slices are contaminated. It is even more severe in pelvis case under half-fan mode, where 36 out of 80 slices are affected, leading to inferior soft-tissue delineation. By applying the proposed method, the cone artifacts are effectively corrected, with a mean intensity difference decreased from ∼497 HU to ∼39HU for those contaminated slices. Conclusion: A practical and effective solution for cone artifacts correction is proposed and validated in CBCT IR algorithm. This study is supported in part by NIH (1R01CA154747-01)

  16. Accelerated barrier optimization compressed sensing (ABOCS) reconstruction for cone-beam CT: Phantom studies.

    PubMed

    Niu, Tianye; Zhu, Lei

    2012-07-01

    Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks. The data fidelity tolerance of CS reconstruction can be well estimated based on the measured data, as most of the projection errors are from Poisson noise after effective data correction for scatter and beam-hardening effects. We therefore adopt the TV optimization framework with a data fidelity constraint. To accelerate the convergence, we first convert such a constrained optimization using a logarithmic barrier method into a form similar to that of the conventional TV regularization based reconstruction but with an automatically adjusted penalty weight. The problem is then solved efficiently by gradient projection with an adaptive Barzilai-Borwein step-size selection scheme. The proposed algorithm is referred to as accelerated barrier optimization for CS (ABOCS), and evaluated using both digital and physical phantom studies. ABOCS directly estimates the data fidelity tolerance from the raw projection data. Therefore, as demonstrated in both digital Shepp

  17. Accelerated barrier optimization compressed sensing (ABOCS) reconstruction for cone-beam CT: phantom studies.

    PubMed

    Niu, Tianye; Zhu, Lei

    2012-07-01

    Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks. The data fidelity tolerance of CS reconstruction can be well estimated based on the measured data, as most of the projection errors are from Poisson noise after effective data correction for scatter and beam-hardening effects. We therefore adopt the TV optimization framework with a data fidelity constraint. To accelerate the convergence, we first convert such a constrained optimization using a logarithmic barrier method into a form similar to that of the conventional TV regularization based reconstruction but with an automatically adjusted penalty weight. The problem is then solved efficiently by gradient projection with an adaptive Barzilai-Borwein step-size selection scheme. The proposed algorithm is referred to as accelerated barrier optimization for CS (ABOCS), and evaluated using both digital and physical phantom studies. ABOCS directly estimates the data fidelity tolerance from the raw projection data. Therefore, as demonstrated in both digital Shepp

  18. Accelerated barrier optimization compressed sensing (ABOCS) reconstruction for cone-beam CT: Phantom studies

    PubMed Central

    Niu, Tianye; Zhu, Lei

    2012-01-01

    Purpose: Recent advances in compressed sensing (CS) enable accurate CT image reconstruction from highly undersampled and noisy projection measurements, due to the sparsifiable feature of most CT images using total variation (TV). These novel reconstruction methods have demonstrated advantages in clinical applications where radiation dose reduction is critical, such as onboard cone-beam CT (CBCT) imaging in radiation therapy. The image reconstruction using CS is formulated as either a constrained problem to minimize the TV objective within a small and fixed data fidelity error, or an unconstrained problem to minimize the data fidelity error with TV regularization. However, the conventional solutions to the above two formulations are either computationally inefficient or involved with inconsistent regularization parameter tuning, which significantly limit the clinical use of CS-based iterative reconstruction. In this paper, we propose an optimization algorithm for CS reconstruction which overcomes the above two drawbacks. Methods: The data fidelity tolerance of CS reconstruction can be well estimated based on the measured data, as most of the projection errors are from Poisson noise after effective data correction for scatter and beam-hardening effects. We therefore adopt the TV optimization framework with a data fidelity constraint. To accelerate the convergence, we first convert such a constrained optimization using a logarithmic barrier method into a form similar to that of the conventional TV regularization based reconstruction but with an automatically adjusted penalty weight. The problem is then solved efficiently by gradient projection with an adaptive Barzilai–Borwein step-size selection scheme. The proposed algorithm is referred to as accelerated barrier optimization for CS (ABOCS), and evaluated using both digital and physical phantom studies. Results: ABOCS directly estimates the data fidelity tolerance from the raw projection data. Therefore, as

  19. Spectral X-Ray CT Image Reconstruction with a Combination of Energy-Integrating and Photon-Counting Detectors.

    PubMed

    Yang, Qingsong; Cong, Wenxiang; Xi, Yan; Wang, Ge

    2016-01-01

    The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT) which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV). The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved.

  20. Spectral X-Ray CT Image Reconstruction with a Combination of Energy-Integrating and Photon-Counting Detectors

    PubMed Central

    Yang, Qingsong; Cong, Wenxiang; Xi, Yan; Wang, Ge

    2016-01-01

    The purpose of this paper is to develop an algorithm for hybrid spectral computed tomography (CT) which combines energy-integrating and photon-counting detectors. While the energy-integrating scan is global, the photon-counting scan can have a local field of view (FOV). The algorithm synthesizes both spectral data and energy-integrating data. Low rank and sparsity prior is used for spectral CT reconstruction. An initial estimation is obtained from the projection data based on physical principles of x-ray interaction with the matter, which provides a more accurate Taylor expansion than previous work and can guarantee the convergence of the algorithm. Numerical simulation with clinical CT images are performed. The proposed algorithm produces very good spectral features outside the FOV when no K-edge material exists. Exterior reconstruction of K-edge material can be partially achieved. PMID:27171153

  1. SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography

    SciTech Connect

    Zhang, J; Ge, G; Winkler, M; Cong, W; Wang, G

    2014-06-01

    Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose.

  2. 4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

    PubMed Central

    Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

    2016-01-01

    A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp–Davis–Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations. PMID:26758496

  3. 4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling

    NASA Astrophysics Data System (ADS)

    Zhong, Zichun; Gu, Xuejun; Mao, Weihua; Wang, Jing

    2016-02-01

    A simultaneous motion estimation and image reconstruction (SMEIR) strategy was proposed for 4D cone-beam CT (4D-CBCT) reconstruction and showed excellent results in both phantom and lung cancer patient studies. In the original SMEIR algorithm, the deformation vector field (DVF) was defined on voxel grid and estimated by enforcing a global smoothness regularization term on the motion fields. The objective of this work is to improve the computation efficiency and motion estimation accuracy of SMEIR for 4D-CBCT through developing a multi-organ meshing model. Feature-based adaptive meshes were generated to reduce the number of unknowns in the DVF estimation and accurately capture the organ shapes and motion. Additionally, the discontinuity in the motion fields between different organs during respiration was explicitly considered in the multi-organ mesh model. This will help with the accurate visualization and motion estimation of the tumor on the organ boundaries in 4D-CBCT. To further improve the computational efficiency, a GPU-based parallel implementation was designed. The performance of the proposed algorithm was evaluated on a synthetic sliding motion phantom, a 4D NCAT phantom, and four lung cancer patients. The proposed multi-organ mesh based strategy outperformed the conventional Feldkamp-Davis-Kress, iterative total variation minimization, original SMEIR and single meshing method based on both qualitative and quantitative evaluations.

  4. Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

    SciTech Connect

    Solomon, Justin; Samei, Ehsan

    2014-09-15

    Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

  5. Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT

    PubMed Central

    Dillman, Jonathan R.; Goodsitt, Mitchell M.; Christodoulou, Emmanuel G.; Keshavarzi, Nahid; Strouse, Peter J.

    2014-01-01

    Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P < .002), lungs (P < .001), and bones (P < .001). By using the same reduced-dose acquisition, lesion detectability was better (38% [32 of 84 rated lesions]) or the same (62% [52 of 84 rated lesions]) with MBIR as compared with 100% ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental

  6. Iterative ct reconstruction from few projections for the nondestructive post irradiation examination of nuclear fuel assemblies

    NASA Astrophysics Data System (ADS)

    Abir, Muhammad Imran Khan

    The core components (e.g. fuel assemblies, spacer grids, control rods) of the nuclear reactors encounter harsh environment due to high temperature, physical stress, and a tremendous level of radiation. The integrity of these elements is crucial for safe operation of the nuclear power plants. The Post Irradiation Examination (PIE) can reveal information about the integrity of the elements during normal operations and off?normal events. Computed tomography (CT) is a tool for evaluating the structural integrity of elements non-destructively. CT requires many projections to be acquired from different view angles after which a mathematical algorithm is adopted for reconstruction. Obtaining many projections is laborious and expensive in nuclear industries. Reconstructions from a small number of projections are explored to achieve faster and cost-efficient PIE. Classical reconstruction algorithms (e.g. filtered back projection) cannot offer stable reconstructions from few projections and create severe streaking artifacts. In this thesis, conventional algorithms are reviewed, and new algorithms are developed for reconstructions of the nuclear fuel assemblies using few projections. CT reconstruction from few projections falls into two categories: the sparse-view CT and the limited-angle CT or tomosynthesis. Iterative reconstruction algorithms are developed for both cases in the field of compressed sensing (CS). The performance of the algorithms is assessed using simulated projections and validated through real projections. The thesis also describes the systematic strategy towards establishing the conditions of reconstructions and finds the optimal imaging parameters for reconstructions of the fuel assemblies from few projections.

  7. [The study of associated reconstruction using MV linear accelerator and cone-beam CT].

    PubMed

    Liu, Zun-gang; Zhao, Jun; Zhuang, Tian-ge

    2006-07-01

    In this paper, we proposed a new scan mode and image reconstruction method, which combines the data from both the linear accelerator and the cone-beam CT to reconstruct the volume with a limited rotation angle and low sampling rate. The classical filtered backprojection method and the iterative method are utilized to reconstruct the volume. The reconstruction results of the two methods are compared with each other with a relavant anlysis given here.

  8. Texture-preserving Bayesian image reconstruction for low-dose CT

    NASA Astrophysics Data System (ADS)

    Zhang, Hao; Han, Hao; Hu, Yifan; Liu, Yan; Ma, Jianhua; Li, Lihong; Moore, William; Liang, Zhengrong

    2016-03-01

    Markov random field (MRF) model has been widely used in Bayesian image reconstruction to reconstruct piecewise smooth images in the presence of noise, such as in low-dose X-ray computed tomography (LdCT). While it can preserve edge sharpness via edge-preserving potential function, its regional smoothing may sacrifice tissue image textures, which have been recognized as useful imaging biomarkers, and thus it compromises clinical tasks such as differentiating malignant vs. benign lesions, e.g., lung nodule or colon polyp. This study aims to shift the edge preserving regional noise smoothing paradigm to texture-preserving framework for LdCT image reconstruction while retaining the advantage of MRF's neighborhood system on edge preservation. Specifically, we adapted the MRF model to incorporate the image textures of lung, bone, fat, muscle, etc. from previous full-dose CT scan as a priori knowledge for texture-preserving Bayesian reconstruction of current LdCT images. To show the feasibility of proposed reconstruction framework, experiments using clinical patient scans (with lung nodule or colon polyp) were conducted. The experimental outcomes showed noticeable gain by the a priori knowledge for LdCT image reconstruction with the well-known Haralick texture measures. Thus, it is conjectured that texture-preserving LdCT reconstruction has advantages over edge-preserving regional smoothing paradigm for texture-specific clinical applications.

  9. Postoperative Evaluation after Anterior Cruciate Ligament Reconstruction: Measurements and Abnormalities on Radiographic and CT Imaging.

    PubMed

    Kim, Minchul; Choi, Yun Sun; Kim, Hyoungseop; Choi, Nam-Hong

    2016-01-01

    Reconstruction of a ruptured anterior cruciate ligament (ACL) is a well-established procedure for repair of ACL injury. Despite improvement of surgical and rehabilitation techniques over the past decades, up to 25% of patients still fail to regain satisfactory function after an ACL reconstruction. With development of CT imaging techniques for reducing metal artifacts, multi-planar reconstruction, and three-dimensional reconstruction, early post-operative imaging is increasingly being used to provide immediate feedback to surgeons regarding tunnel positioning, fixation, and device placement. Early post-operative radiography and CT imaging are easy to perform and serve as the baseline examinations for future reference.

  10. Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

    SciTech Connect

    Brady, Samuel L.; Shulkin, Barry L.

    2015-02-15

    Purpose: To develop ultralow dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUV{sub bw}) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV{sub bw}, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.

  11. WE-G-18A-05: Cone-Beam CT Reconstruction with Deformed Prior Image

    SciTech Connect

    Zhang, H; Huang, J; Ma, J; Chen, W; Ouyang, L; Wang, J

    2014-06-15

    Purpose: Prior image can be incorporated into image reconstruction process to improve the quality of on-treatment cone-beam CT (CBCT) from sparseview or low-dose projections. However, the deformation between the prior image and on-treatment CBCT are not considered in current prior image based reconstructions (e.g., prior image constrained compressed sensing (PICCS)). The purpose of this work is to develop a deformed-prior-imagebased- reconstruction strategy (DPIR) to address the mismatch problem between the prior image and target image. Methods: The deformed prior image is obtained by a projection based registration approach. Specifically, the deformation vector fields (DVF) used to deform the prior image is estimated through matching the forward projection of the prior image and the measured on-treatment projection. The deformed prior image is then used as the prior image in the standard PICCS algorithm. Simulation studies on the XCAT phantom was conducted to evaluate the performance of the projection based registration procedure and the proposed DPIR strategy. Results: The deformed prior image matches the geometry of on-treatment CBCT closer as compared to the original prior image. Using the deformed prior image, the quality of the image reconstructed by DPIR from few-view projection data is greatly improved as compared to the standard PICCS algorithm. The relative image reconstruction error is reduced to 11.13% in the proposed DPIR from 17.57% in the original PICCS. Conclusion: The proposed DPIR approach can solve the mismatch problem between the prior image and target image, which overcomes the limitation of the original PICCS algorithm for CBCT reconstruction from sparse-view or low-dose projections.

  12. Estimation of radiation cancer risk in CT-KUB

    NASA Astrophysics Data System (ADS)

    Karim, M. K. A.; Hashim, S.; Bakar, K. A.; Bradley, D. A.; Ang, W. C.; Bahrudin, N. A.; Mhareb, M. H. A.

    2017-08-01

    The increased demand for computed tomography (CT) in radiological scanning examinations raises the question of a potential health impact from the associated radiation exposures. Focusing on CT kidney-ureter-bladder (CT-KUB) procedures, this work was aimed at determining organ equivalent dose using a commercial CT dose calculator and providing an estimate of cancer risks. The study, which included 64 patients (32 males and 32 females, mean age 55.5 years and age range 30-80 years), involved use of a calibrated CT scanner (Siemens-Somatom Emotion 16-slice). The CT exposures parameter including tube potential, pitch factor, tube current, volume CT dose index (CTDIvol) and dose-length product (DLP) were recorded and analyzed using CT-EXPO (Version 2.3.1, Germany). Patient organ doses, including for stomach, liver, colon, bladder, red bone marrow, prostate and ovaries were calculated and converted into cancer risks using age- and sex-specific data published in the Biological Effects of Ionizing Radiation (BEIR) VII report. With a median value scan range of 36.1 cm, the CTDIvol, DLP, and effective dose were found to be 10.7 mGy, 390.3 mGy cm and 6.2 mSv, respectively. The mean cancer risks for males and females were estimated to be respectively 25 and 46 out of 100,000 procedures with effective doses between 4.2 mSv and 10.1 mSv. Given the increased cancer risks from current CT-KUB procedures compared to conventional examinations, we propose that the low dose protocols for unenhanced CT procedures be taken into consideration before establishing imaging protocols for CT-KUB.

  13. A robust geometry estimation method for spiral, sequential and circular cone-beam micro-CT

    SciTech Connect

    Sawall, Stefan; Knaup, Michael; Kachelriess, Marc

    2012-09-15

    Purpose: The authors propose a novel method for misalignment estimation of micro-CT scanners using an adaptive genetic algorithm. Methods: The proposed algorithm is able to estimate the rotational geometry, the direction vector of table movement and the displacement between different imaging threads of a dual source or even multisource scanner. The calibration procedure does not rely on dedicated calibration phantoms and a sequence scan of a single metal bead is sufficient to geometrically calibrate the whole imaging system for spiral, sequential, and circular scan protocols. Dual source spiral and sequential scan protocols in micro-computed tomography result in projection data that-besides the source and detector positions and orientations-also require a precise knowledge of the table direction vector to be reconstructed properly. If those geometric parameters are not known accurately severe artifacts and a loss in spatial resolution appear in the reconstructed images as long as no geometry calibration is performed. The table direction vector is further required to ensure that consecutive volumes of a sequence scan can be stitched together and to allow the reconstruction of spiral data at all. Results: The algorithm's performance is evaluated using simulations of a micro-CT system with known geometry and misalignment. To assess the quality of the algorithm in a real world scenario the calibration of a micro-CT scanner is performed and several reconstructions with and without geometry estimation are presented. Conclusions: The results indicate that the algorithm successfully estimates all geometry parameters, misalignment artifacts in the reconstructed volumes vanish, and the spatial resolution is increased as can be shown by the evaluation of modulation transfer function measurements.

  14. Directional sinogram interpolation for motion weighted 4D cone-beam CT reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Hua; Kruis, Matthijs; Sonke, Jan-Jakob

    2017-03-01

    The image quality of respiratory sorted four-dimensional (4D) cone-beam (CB) computed tomography (CT) is often limited by streak artifacts due to insufficient projections. A motion weighted reconstruction (MWR) method is proposed to decrease streak artifacts and improve image quality. Firstly, respiratory correlated CBCT projections were interpolated by directional sinogram interpolation (DSI) to generate additional CB projections for each phase and subsequently reconstructed. Secondly, local motion was estimated by deformable image registration of the interpolated 4D CBCT. Thirdly, a regular 3D FDK CBCT was reconstructed from the non-interpolated projections. Finally, weights were assigned to each voxel, based on the local motion, and then were used to combine the 3D FDK CBCT and interpolated 4D CBCT to generate the final 4D image. MWR method was compared with regular 4D CBCT scans as well as McKinnon and Bates (MKB) based reconstructions. Comparisons were made in terms of (1) comparing the steepness of an extracted profile from the boundary of the region-of-interest (ROI), (2) contrast-to-noise ratio (CNR) inside certain ROIs, and (3) the root-mean-square-error (RMSE) between the planning CT and CBCT inside a homogeneous moving region. Comparisons were made for both a phantom and four patient scans. In a 4D phantom, RMSE were reduced by 24.7% and 38.7% for MKB and MWR respectively, compared to conventional 4D CBCT. Meanwhile, interpolation induced blur was minimal in static regions for MWR based reconstructions. In regions with considerable respiratory motion, image blur using MWR is less than the MKB and 3D Feldkamp (FDK) methods. In the lung cancer patients, average CNRs of MKB, DSI and MWR improved by a factor 1.7, 2.8 and 3.5 respectively relative to 4D FDK. MWR effectively reduces RMSE in 4D cone-beam CT and improves the image quality in both the static and respiratory moving regions compared to 4D FDK and MKB methods.

  15. Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

    SciTech Connect

    Gu, Renliang; Dogandžić, Aleksandar

    2014-02-18

    We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer’s law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ{sub 1}-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

  16. Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

    NASA Astrophysics Data System (ADS)

    Gu, Renliang; Dogandžić, Aleksandar

    2014-02-01

    We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer's law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ1-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

  17. Left ventricle surface reconstruction from volumetric CT images by the fusion of clustering and active contours

    NASA Astrophysics Data System (ADS)

    Fan, Li; Chen, Chang W.

    1998-07-01

    This paper presents an integrated scheme to extract and reconstruct left ventricle chambers from CT volumetric image sequences. An accurate extraction of left ventricle chambers is a crucial step towards cardiac dynamics analysis based on image sequences, a very much desired non-invasive technique for heart disease diagnosis and monitoring. The integrated approach aims at solving two major problems in cardiac image segmentation: imaging related ambiguity and anatomy related ambiguity. The K-means clustering with Gibb's random field constraints is able to resolve the imaging related ambiguity to obtain robust segmentation even when the intensity of the left ventricle exhibits spatially varying distribution. The active contour models incorporating a priori shape knowledge is able to resolve the anatomy related ambiguity to estimate the valve that separates the left ventricle from left atrium and aorta but is indistinguishable in the given images due to motion and partial volume effects. The fusion of the clustering and active contour models enables an integrated reconstruction of left ventricle chambers from the CT image sequences. Preliminary results show that the proposed scheme can produce extracted left ventricle chambers that compare favorably with the manually delineated chambers by a skilled operator. However, this proposed scheme is fast and reproducible.

  18. Proximal ADMM for multi-channel image reconstruction in spectral X-ray CT.

    PubMed

    Sawatzky, Alex; Xu, Qiaofeng; Schirra, Carsten O; Anastasio, Mark A

    2014-08-01

    The development of spectral X-ray computed tomography (CT) using binned photon-counting detectors has received great attention in recent years and has enabled selective imaging of contrast agents loaded with K-edge materials. A practical issue in implementing this technique is the mitigation of the high-noise levels often present in material-decomposed sinogram data. In this work, the spectral X-ray CT reconstruction problem is formulated within a multi-channel (MC) framework in which statistical correlations between the decomposed material sinograms can be exploited to improve image quality. Specifically, a MC penalized weighted least squares (PWLS) estimator is formulated in which the data fidelity term is weighted by the MC covariance matrix and sparsity-promoting penalties are employed. This allows the use of any number of basis materials and is therefore applicable to photon-counting systems and K-edge imaging. To overcome numerical challenges associated with use of the full covariance matrix as a data fidelity weight, a proximal variant of the alternating direction method of multipliers is employed to minimize the MC PWLS objective function. Computer-simulation and experimental phantom studies are conducted to quantitatively evaluate the proposed reconstruction method.

  19. Cardiovascular CT angiography in neonates and children: image quality and potential for radiation dose reduction with iterative image reconstruction techniques.

    PubMed

    Tricarico, Francesco; Hlavacek, Anthony M; Schoepf, U Joseph; Ebersberger, Ullrich; Nance, John W; Vliegenthart, Rozemarijn; Cho, Young Jun; Spears, J Reid; Secchi, Francesco; Savino, Giancarlo; Marano, Riccardo; Schoenberg, Stefan O; Bonomo, Lorenzo; Apfaltrer, Paul

    2013-05-01

    To evaluate image quality (IQ) of low-radiation-dose paediatric cardiovascular CT angiography (CTA), comparing iterative reconstruction in image space (IRIS) and sinogram-affirmed iterative reconstruction (SAFIRE) with filtered back-projection (FBP) and estimate the potential for further dose reductions. Forty neonates and children underwent low radiation CTA with or without ECG synchronisation. Data were reconstructed with FBP, IRIS and SAFIRE. For ECG-synchronised studies, half-dose image acquisitions were simulated. Signal noise was measured and IQ graded. Effective dose (ED) was estimated. Mean absolute and relative image noise with IRIS and full-dose SAFIRE was lower than with FBP (P < 0.001), while SNR and CNR were higher (P < 0.001). Image noise was also lower and SNR and CNR higher in half-dose SAFIRE studies compared with full-and half-dose FBP studies (P < 0.001). IQ scores were higher for IRIS, full-dose SAFIRE and half-dose SAFIRE than for full-dose FBP and higher for half-dose SAFIRE than for half-dose FBP (P < 0.05). Median weight-specific ED was 0.3 mSv without and 1.36 mSv with ECG synchronisation. The estimated ED of half-dose SAFIRE studies was 0.68 mSv. IR improves image noise, SNR, CNR and subjective IQ compared with FBP in low-radiation-dose paediatric CTA and allows further dose reductions without compromising diagnostic IQ. • Iterative reconstruction techniques significantly improve non-invasive cardiovascular CT in children. • Using half traditional radiation dose image quality is higher with iterative reconstruction. • Iterative reconstruction techniques may allow further radiation reductions in paediatric cardiovascular CT.

  20. Impact of radiation dose and iterative reconstruction on pulmonary nodule measurements at chest CT: a phantom study.

    PubMed

    Kim, Hyungjin; Park, Chang Min; Chae, Hee Dong; Lee, Sang Min; Goo, Jin Mo

    2015-01-01

    We aimed to identify the impact of radiation dose and iterative reconstruction (IR) on measurement of pulmonary nodules by chest computed tomography (CT). CT scans were performed on a chest phantom containing various nodules (diameters of 3, 5, 8, 10, and 12 mm; +100, -630 and -800 HU for each diameter) at 80, 100, 120 kVp and 10, 20, 50, 100 mAs (a total of 12 radiation dose settings). Each CT was reconstructed using filtered back projection, iDose4, and iterative model reconstruction (IMR). Thereafter, two radiologists measured the diameter and attenuation of the nodules. Noise, contrast-to-noise ratio and signal-to-noise ratio of CT images were also obtained. Influence of radiation dose and reconstruction algorithm on measurement error and objective image quality metrics was analyzed using generalized estimating equations. The 80 kVp, 10 mAs CT scan was not feasible for the measurement of 3 mm sized simulated ground-glass nodule (GGN); otherwise, diameter measurement error was not significantly influenced by radiation dose (P > 0.05). IR did not have a significant impact on diameter measurement error for simulated solid nodules (P > 0.05). However, for simulated GGNs, IMR was associated with significantly decreased relative diameter measurement error (P < 0.001). Attenuation measurement error was not significantly influenced by either radiation dose or reconstruction algorithm (P > 0.05). Objective image quality was significantly better with IMR (P < 0.05). Nodule measurements were not affected by radiation dose except for 3 mm simulated GGN on 80 kVp, 10 mAs dose setting. However, for GGNs, IMR may help reduce diameter measurement error while improving image quality.

  1. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

    PubMed

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Kim, Jin Sung; Park, Justin C

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

  2. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy

    PubMed Central

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Park, Justin C.

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy. PMID:27243822

  3. Helical mode lung 4D-CT reconstruction using Bayesian model.

    PubMed

    He, Tiancheng; Xue, Zhong; Nitsch, Paige L; Teh, Bin S; Wong, Stephen T

    2013-01-01

    4D computed tomography (CT) has been widely used for treatment planning of thoracic and abdominal cancer radiotherapy. Current 4D-CT lung image reconstruction methods rely on respiratory gating to rearrange the large number of axial images into different phases, which may be subject to external surrogate errors due to poor reproducibility of breathing cycles. New image-matching-based reconstruction works better for the cine mode of 4D-CT acquisition than the helical mode because the table position of each axial image is different in helical mode and image matching might suffer from bigger errors. In helical mode, not only the phases but also the un-uniform table positions of images need to be considered. We propose a Bayesian method for automated 4D-CT lung image reconstruction in helical mode 4D scans. Each axial image is assigned to a respiratory phase based on the Bayesian framework that ensures spatial and temporal smoothness of surfaces of anatomical structures. Iterative optimization is used to reconstruct a series of 3D-CT images for subjects undergoing 4D scans. In experiments, we compared visually and quantitatively the results of the proposed Bayesian 4D-CT reconstruction algorithm with the respiratory surrogate and the image matching-based method. The results showed that the proposed algorithm yielded better 4D-CT for helical scans.

  4. Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

    SciTech Connect

    Dong, Xue; Niu, Tianye; Zhu, Lei

    2014-05-15

    order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.

  5. Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization.

    PubMed

    Dong, Xue; Niu, Tianye; Zhu, Lei

    2014-05-01

    improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.

  6. Estimation of skull table thickness with clinical CT and validation with microCT.

    PubMed

    Lillie, Elizabeth M; Urban, Jillian E; Weaver, Ashley A; Powers, Alexander K; Stitzel, Joel D

    2015-01-01

    Brain injuries resulting from motor vehicle crashes (MVC) are extremely common yet the details of the mechanism of injury remain to be well characterized. Skull deformation is believed to be a contributing factor to some types of traumatic brain injury (TBI). Understanding biomechanical contributors to skull deformation would provide further insight into the mechanism of head injury resulting from blunt trauma. In particular, skull thickness is thought be a very important factor governing deformation of the skull and its propensity for fracture. Current computed tomography (CT) technology is limited in its ability to accurately measure cortical thickness using standard techniques. A method to evaluate cortical thickness using cortical density measured from CT data has been developed previously. This effort validates this technique for measurement of skull table thickness in clinical head CT scans using two postmortem human specimens. Bone samples were harvested from the skulls of two cadavers and scanned with microCT to evaluate the accuracy of the estimated cortical thickness measured from clinical CT. Clinical scans were collected at 0.488 and 0.625 mm in plane resolution with 0.625 mm thickness. The overall cortical thickness error was determined to be 0.078 ± 0.58 mm for cortical samples thinner than 4 mm. It was determined that 91.3% of these differences fell within the scanner resolution. Color maps of clinical CT thickness estimations are comparable to color maps of microCT thickness measurements, indicating good quantitative agreement. These data confirm that the cortical density algorithm successfully estimates skull table thickness from clinical CT scans. The application of this technique to clinical CT scans enables evaluation of cortical thickness in population-based studies.

  7. Estimation of skull table thickness with clinical CT and validation with microCT

    PubMed Central

    Lillie, Elizabeth M; Urban, Jillian E; Weaver, Ashley A; Powers, Alexander K; Stitzel, Joel D

    2015-01-01

    Brain injuries resulting from motor vehicle crashes (MVC) are extremely common yet the details of the mechanism of injury remain to be well characterized. Skull deformation is believed to be a contributing factor to some types of traumatic brain injury (TBI). Understanding biomechanical contributors to skull deformation would provide further insight into the mechanism of head injury resulting from blunt trauma. In particular, skull thickness is thought be a very important factor governing deformation of the skull and its propensity for fracture. Current computed tomography (CT) technology is limited in its ability to accurately measure cortical thickness using standard techniques. A method to evaluate cortical thickness using cortical density measured from CT data has been developed previously. This effort validates this technique for measurement of skull table thickness in clinical head CT scans using two postmortem human specimens. Bone samples were harvested from the skulls of two cadavers and scanned with microCT to evaluate the accuracy of the estimated cortical thickness measured from clinical CT. Clinical scans were collected at 0.488 and 0.625 mm in plane resolution with 0.625 mm thickness. The overall cortical thickness error was determined to be 0.078 ± 0.58 mm for cortical samples thinner than 4 mm. It was determined that 91.3% of these differences fell within the scanner resolution. Color maps of clinical CT thickness estimations are comparable to color maps of microCT thickness measurements, indicating good quantitative agreement. These data confirm that the cortical density algorithm successfully estimates skull table thickness from clinical CT scans. The application of this technique to clinical CT scans enables evaluation of cortical thickness in population-based studies. PMID:25441171

  8. Comparison of computational to human observer detection for evaluation of CT low dose iterative reconstruction

    NASA Astrophysics Data System (ADS)

    Eck, Brendan; Fahmi, Rachid; Brown, Kevin M.; Raihani, Nilgoun; Wilson, David L.

    2014-03-01

    Model observers were created and compared to human observers for the detection of low contrast targets in computed tomography (CT) images reconstructed with an advanced, knowledge-based, iterative image reconstruction method for low x-ray dose imaging. A 5-channel Laguerre-Gauss Hotelling Observer (CHO) was used with internal noise added to the decision variable (DV) and/or channel outputs (CO). Models were defined by parameters: (k1) DV-noise with standard deviation (std) proportional to DV std; (k2) DV-noise with constant std; (k3) CO-noise with constant std across channels; and (k4) CO-noise in each channel with std proportional to CO variance. Four-alternative forced choice (4AFC) human observer studies were performed on sub-images extracted from phantom images with and without a "pin" target. Model parameters were estimated using maximum likelihood comparison to human probability correct (PC) data. PC in human and all model observers increased with dose, contrast, and size, and was much higher for advanced iterative reconstruction (IMR) as compared to filtered back projection (FBP). Detection in IMR was better than FPB at 1/3 dose, suggesting significant dose savings. Model(k1,k2,k3,k4) gave the best overall fit to humans across independent variables (dose, size, contrast, and reconstruction) at fixed display window. However Model(k1) performed better when considering model complexity using the Akaike information criterion. Model(k1) fit the extraordinary detectability difference between IMR and FBP, despite the different noise quality. It is anticipated that the model observer will predict results from iterative reconstruction methods having similar noise characteristics, enabling rapid comparison of methods.

  9. MicroCT: Semi-Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

    SciTech Connect

    Seetho, I M; Brown, W D; Kallman, J S; Martz, H E; White, W T

    2011-09-22

    This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition [1] and MicroCT image reconstruction [2], per the IDD Quality Assurance Plan for MicroCT Scanning [3]. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to R and D work - for production applications, use [4].

  10. MicroCT: Automated Analysis of CT Reconstructed Data of Home Made Explosive Materials Using the Matlab MicroCT Analysis GUI

    SciTech Connect

    Seetho, I M; Brown, W D; Kallman, J S; Martz, H E; White, W T

    2011-09-22

    This Standard Operating Procedure (SOP) provides the specific procedural steps for analyzing reconstructed CT images obtained under the IDD Standard Operating Procedures for data acquisition [1] and MicroCT image reconstruction [2], per the IDD Quality Assurance Plan for MicroCT Scanning [3]. Although intended to apply primarily to MicroCT data acquired in the HEAFCAT Facility at LLNL, these procedures may also be applied to data acquired at Tyndall from the YXLON cabinet and at TSL from the HEXCAT system. This SOP also provides the procedural steps for preparing the tables and graphs to be used in the reporting of analytical results. This SOP applies to production work - for R and D there are two other semi-automated methods as given in [4, 5].

  11. Iterative Image Reconstruction for Limited-Angle CT Using Optimized Initial Image

    PubMed Central

    Guo, Jingyu; Qi, Hongliang; Xu, Yuan; Chen, Zijia; Li, Shulong; Zhou, Linghong

    2016-01-01

    Limited-angle computed tomography (CT) has great impact in some clinical applications. Existing iterative reconstruction algorithms could not reconstruct high-quality images, leading to severe artifacts nearby edges. Optimal selection of initial image would influence the iterative reconstruction performance but has not been studied deeply yet. In this work, we proposed to generate optimized initial image followed by total variation (TV) based iterative reconstruction considering the feature of image symmetry. The simulated data and real data reconstruction results indicate that the proposed method effectively removes the artifacts nearby edges. PMID:27066107

  12. Cardiac motion correction based on partial angle reconstructed images in x-ray CT

    SciTech Connect

    Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

    2015-05-15

    Purpose: Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. Methods: A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of

  13. Cardiac motion correction based on partial angle reconstructed images in x-ray CT.

    PubMed

    Kim, Seungeon; Chang, Yongjin; Ra, Jong Beom

    2015-05-01

    Cardiac x-ray CT imaging is still challenging due to heart motion, which cannot be ignored even with the current rotation speed of the equipment. In response, many algorithms have been developed to compensate remaining motion artifacts by estimating the motion using projection data or reconstructed images. In these algorithms, accurate motion estimation is critical to the compensated image quality. In addition, since the scan range is directly related to the radiation dose, it is preferable to minimize the scan range in motion estimation. In this paper, the authors propose a novel motion estimation and compensation algorithm using a sinogram with a rotation angle of less than 360°. The algorithm estimates the motion of the whole heart area using two opposite 3D partial angle reconstructed (PAR) images and compensates the motion in the reconstruction process. A CT system scans the thoracic area including the heart over an angular range of 180° + α + β, where α and β denote the detector fan angle and an additional partial angle, respectively. The obtained cone-beam projection data are converted into cone-parallel geometry via row-wise fan-to-parallel rebinning. Two conjugate 3D PAR images, whose center projection angles are separated by 180°, are then reconstructed with an angular range of β, which is considerably smaller than a short scan range of 180° + α. Although these images include limited view angle artifacts that disturb accurate motion estimation, they have considerably better temporal resolution than a short scan image. Hence, after preprocessing these artifacts, the authors estimate a motion model during a half rotation for a whole field of view via nonrigid registration between the images. Finally, motion-compensated image reconstruction is performed at a target phase by incorporating the estimated motion model. The target phase is selected as that corresponding to a view angle that is orthogonal to the center view angles of two conjugate PAR

  14. Estimating cancer risks to adults undergoing body CT examinations.

    PubMed

    Huda, Walter; He, Wenjun

    2012-06-01

    The purpose of the study is to estimate cancer risks from the amount of radiation used to perform body computed tomography (CT) examination. The ImPACT CT Patient Dosimetry Calculator was used to compute values of organ doses for adult body CT examinations. The radiation used to perform each examination was quantified by the dose-length product (DLP). Patient organ doses were converted into corresponding age and sex dependent cancer risks using data from BEIR VII. Results are presented for cancer risks per unit DLP and unit effective dose for 11 sensitive organs, as well as estimates of the contribution from 'other organs'. For patients who differ from a standard sized adult, correction factors based on the patient weight and antero-posterior dimension are provided to adjust organ doses and the corresponding risks. At constant incident radiation intensity, for CT examinations that include the chest, risks for females are markedly higher than those for males, whereas for examinations that include the pelvis, risks in males were slightly higher than those in females. In abdominal CT scans, risks for males and female patients are very similar. For abdominal CT scans, increasing the patient age from 20 to 80 resulted in a reduction in patient risks of nearly a factor of 5. The average cancer risk for chest/abdomen/pelvis CT examinations was ∼26 % higher than the cancer risk caused by 'sensitive organs'. Doses and radiation risks in 80 kg adults were ∼10 % lower than those in 70 kg patients. Cancer risks in body CT can be estimated from the examination DLP by accounting for sex, age, as well as patient physical characteristics.

  15. An Approximate Cone Beam Reconstruction Algorithm for Gantry-Tilted CT Using Tangential Filtering

    PubMed Central

    Zhang, Cishen; Liang, Hongzhu

    2006-01-01

    FDK algorithm is a well-known 3D (three-dimensional) approximate algorithm for CT (computed tomography) image reconstruction and is also known to suffer from considerable artifacts when the scanning cone angle is large. Recently, it has been improved by performing the ramp filtering along the tangential direction of the X-ray source helix for dealing with the large cone angle problem. In this paper, we present an FDK-type approximate reconstruction algorithm for gantry-tilted CT imaging. The proposed method improves the image reconstruction by filtering the projection data along a proper direction which is determined by CT parameters and gantry-tilted angle. As a result, the proposed algorithm for gantry-tilted CT reconstruction can provide more scanning flexibilities in clinical CT scanning and is efficient in computation. The performance of the proposed algorithm is evaluated with turbell clock phantom and thorax phantom and compared with FDK algorithm and a popular 2D (two-dimensional) approximate algorithm. The results show that the proposed algorithm can achieve better image quality for gantry-tilted CT image reconstruction. PMID:23165022

  16. Can low-dose CT with iterative reconstruction reduce both the radiation dose and the amount of iodine contrast medium in a dynamic CT study of the liver?

    PubMed

    Takahashi, Hiroto; Okada, Masahiro; Hyodo, Tomoko; Hidaka, Syojiro; Kagawa, Yuki; Matsuki, Mitsuru; Tsurusaki, Masakatsu; Murakami, Takamichi

    2014-04-01

    To investigate whether low-dose dynamic CT of the liver with iterative reconstruction can reduce both the radiation dose and the amount of contrast medium. This study was approved by our institutional review board. 113 patients were randomly assigned to one of two groups. Group A/group B (fifty-eight/fifty-five patients) underwent liver dynamic CT at 120/100 kV, with 0/40% adaptive statistical iterative reconstruction (ASIR), with a contrast dose of 600/480 mg I/kg, respectively. Radiation exposure was estimated based on the manufacturer's phantom data. The enhancement value of the hepatic parenchyma, vessels and the tumor-to-liver contrast of hepatocellular carcinomas (HCCs) were compared between two groups. Two readers independently assessed the CT images of the hepatic parenchyma and HCCs. The mean CT dose indices: 6.38/4.04 mGy, the dose-length products: 194.54/124.57 mGy cm, for group A/group B. The mean enhancement value of the hepatic parenchyma and the tumor-to-liver contrast of HCCs with diameters greater than 1cm in the post-contrast all phases did not differ significantly between two groups (P>0.05). The enhancement values of vessels in group B were significantly higher than that in group A in the delayed phases (P<0.05). Two reader's confidence levels for the hepatic parenchyma in the delayed phases and HCCs did not differ significantly between the groups (P>0.05). Low-dose dynamic CT with ASIR can reduce both the radiation dose and the amount of contrast medium without image quality degradation, compared to conventional dynamic CT without ASIR. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  17. CT of the chest with model-based, fully iterative reconstruction: comparison with adaptive statistical iterative reconstruction.

    PubMed

    Ichikawa, Yasutaka; Kitagawa, Kakuya; Nagasawa, Naoki; Murashima, Shuichi; Sakuma, Hajime

    2013-08-09

    The recently developed model-based iterative reconstruction (MBIR) enables significant reduction of image noise and artifacts, compared with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP). The purpose of this study was to evaluate lesion detectability of low-dose chest computed tomography (CT) with MBIR in comparison with ASIR and FBP. Chest CT was acquired with 64-slice CT (Discovery CT750HD) with standard-dose (5.7 ± 2.3 mSv) and low-dose (1.6 ± 0.8 mSv) conditions in 55 patients (aged 72 ± 7 years) who were suspected of lung disease on chest radiograms. Low-dose CT images were reconstructed with MBIR, ASIR 50% and FBP, and standard-dose CT images were reconstructed with FBP, using a reconstructed slice thickness of 0.625 mm. Two observers evaluated the image quality of abnormal lung and mediastinal structures on a 5-point scale (Score 5 = excellent and score 1 = non-diagnostic). The objective image noise was also measured as the standard deviation of CT intensity in the descending aorta. The image quality score of enlarged mediastinal lymph nodes on low-dose MBIR CT (4.7 ± 0.5) was significantly improved in comparison with low-dose FBP and ASIR CT (3.0 ± 0.5, p = 0.004; 4.0 ± 0.5, p = 0.02, respectively), and was nearly identical to the score of standard-dose FBP image (4.8 ± 0.4, p = 0.66). Concerning decreased lung attenuation (bulla, emphysema, or cyst), the image quality score on low-dose MBIR CT (4.9 ± 0.2) was slightly better compared to low-dose FBP and ASIR CT (4.5 ± 0.6, p = 0.01; 4.6 ± 0.5, p = 0.01, respectively). There were no significant differences in image quality scores of visualization of consolidation or mass, ground-glass attenuation, or reticular opacity among low- and standard-dose CT series. Image noise with low-dose MBIR CT (11.6 ± 1.0 Hounsfield units (HU)) were significantly lower than with low-dose ASIR (21.1 ± 2.6 HU, p < 0.0005), low-dose FBP CT (30.9 ± 3.9 HU, p < 0.0005), and

  18. Estimating radiation risk induced by CT screening for Korean population

    NASA Astrophysics Data System (ADS)

    Yang, Won Seok; Yang, Hye Jeong; Min, Byung In

    2017-02-01

    The purposes of this study are to estimate the radiation risks induced by chest/abdomen computed tomography (CT) screening for healthcare and to determine the cancer risk level of the Korean population compared to other populations. We used an ImPACT CT Patient Dosimetry Calculator to compute the organ effective dose induced by CT screening (chest, low-dose chest, abdomen/pelvis, and chest/abdomen/pelvis CT). A risk model was applied using principles based on the BEIR VII Report in order to estimate the lifetime attributable risk (LAR) using the Korean Life Table 2010. In addition, several countries including Hong Kong, the United States (U.S.), and the United Kingdom, were selected for comparison. Herein, each population exposed radiation dose of 100 mSv was classified according to country, gender and age. For each CT screening the total organ effective dose calculated by ImPACT was 6.2, 1.5, 5.2 and 11.4 mSv, respectively. In the case of Korean female LAR, it was similar to Hong Kong female but lower than those of U.S. and U.K. females, except for those in their twenties. The LAR of Korean males was the highest for all types of CT screening. However, the difference of the risk level was negligible because of the quite low value.

  19. Screening and comparison of polychromatic and monochromatic image reconstruction of abdominal arterial energy spectrum CT.

    PubMed

    Wang, X P; Wang, B; Hou, P; Li, R; Gao, J B

    2017-01-01

    We screened the suitable image reconstruction to observe the abdominal artery and compare the quality between the polychromatic and the monochromatic reconstruction images of the abdominal artery spectrum CT. Eighty patients underwent Gemstone CT energy spectrum imaging to obtain an abdominal artery polychromatic image (140 kVp) and a monochromatic image from 40 ~ 140 keV. The CT value of region of interest (ROI) was measured on the polychromatic image and the single energy image. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the abdominal aorta and hepatic artery were determined. The images in each group underwent image quality subjective scoring by three experienced radiologists using a blinded method. Finally, comprehensive comparisons and image quality subjective scorings were performed on the CT, SNR, and CNR values of the abdominal aorta. The obtained data were statistically analyzed by SPSS 19.0 software. When the keV value was reduced, the CT value of the abdominal artery gradually increased, and the image noise also changed. The comprehensive comparisons and subjective scorings were finalized for each single energy image based on the abdominal artery image quality objective indicators (CT value, SNR, and CNR). Results revealed that the abdominal artery image quality in the 50 ~ 60 keV monochromatic group was better compared to the polychromatic group. Furthermore, onochromatic imaging had different impacts on the abdominal aorta and hepatic artery image qualities. In different types of abdominal arterial reconstruction images obtained using abdominal energy spectrum CT conventional enhanced scanning, the image quality of the 50 ~ 60keV monochromatic reconstruction was higher when compared with the polychromatic reconstruction. Thus, it is recommended to apply the conventional reconstruction for abdominal artery energy spectrum CT scanning.

  20. In-line phase contrast micro-CT reconstruction for biomedical specimens.

    PubMed

    Fu, Jian; Tan, Renbo

    2014-01-01

    X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

  1. Reconstruction algorithm for polychromatic CT imaging: application to beam hardening correction

    NASA Technical Reports Server (NTRS)

    Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

    2000-01-01

    This paper presents a new reconstruction algorithm for both single- and dual-energy computed tomography (CT) imaging. By incorporating the polychromatic characteristics of the X-ray beam into the reconstruction process, the algorithm is capable of eliminating beam hardening artifacts. The single energy version of the algorithm assumes that each voxel in the scan field can be expressed as a mixture of two known substances, for example, a mixture of trabecular bone and marrow, or a mixture of fat and flesh. These assumptions are easily satisfied in a quantitative computed tomography (QCT) setting. We have compared our algorithm to three commonly used single-energy correction techniques. Experimental results show that our algorithm is much more robust and accurate. We have also shown that QCT measurements obtained using our algorithm are five times more accurate than that from current QCT systems (using calibration). The dual-energy mode does not require any prior knowledge of the object in the scan field, and can be used to estimate the attenuation coefficient function of unknown materials. We have tested the dual-energy setup to obtain an accurate estimate for the attenuation coefficient function of K2 HPO4 solution.

  2. Accurate low-dose iterative CT reconstruction from few projections by Generalized Anisotropic Total Variation minimization for industrial CT.

    PubMed

    Debatin, Maurice; Hesser, Jürgen

    2015-01-01

    Reducing the amount of time for data acquisition and reconstruction in industrial CT decreases the operation time of the X-ray machine and therefore increases the sales. This can be achieved by reducing both, the dose and the pulse length of the CT system and the number of projections for the reconstruction, respectively. In this paper, a novel generalized Anisotropic Total Variation regularization for under-sampled, low-dose iterative CT reconstruction is discussed and compared to the standard methods, Total Variation, Adaptive weighted Total Variation and Filtered Backprojection. The novel regularization function uses a priori information about the Gradient Magnitude Distribution of the scanned object for the reconstruction. We provide a general parameterization scheme and evaluate the efficiency of our new algorithm for different noise levels and different number of projection views. When noise is not present, error-free reconstructions are achievable for AwTV and GATV from 40 projections. In cases where noise is simulated, our strategy achieves a Relative Root Mean Square Error that is up to 11 times lower than Total Variation-based and up to 4 times lower than AwTV-based iterative statistical reconstruction (e.g. for a SNR of 223 and 40 projections). To obtain the same reconstruction quality as achieved by Total Variation, the projection number and the pulse length, and the acquisition time and the dose respectively can be reduced by a factor of approximately 3.5, when AwTV is used and a factor of approximately 6.7, when our proposed algorithm is used.

  3. Fetal dose estimates for CT pelvimetry

    SciTech Connect

    Moore, M.M.; Shearer, D.R.

    1989-04-01

    Fetal and maternal dose estimates for computed tomographic pelvimetry have been obtained from phantom measurements. Use of routine abdomen imaging techniques may result in localized fetal doses in excess of 13 mGy (1.3 rad). With the use of a low-exposure (40-mAs) technique, it is possible to obtain images of acceptable quality for the necessary measurements. The resulting dose to the fetus is approximately 2.3 mGy (0.23 rad).

  4. [Analysis and discussion on the facet of the spinal column, spiral CT lock multiplanar reconstruction and 
3D reconstruction].

    PubMed

    Zheng, Zhifeng; Wang, Shuhang; Si, Donglei

    2015-10-01

    To investigate the imaging appearances and diagnostic value of axial CT scanning, spiral CT multiplanar reconstruction (MPR) and three-dimensional (3D) reconstruction in vertebral facet joints locking.
 A total of 31 cases of vertebral facet joints locking, with injuries in different parts, were recruited to explore their CT features, and to evaluate their advantages in diagnosis against each other.
 Among the CT images of 31 cases with "Hamburger" sign in axial view, there were 21 cases of cervical spine and 10 cases of thoracolumbar segment; in vertical plane of MPR, "top to top" form was formed below the inferior and the superior articular process, accompanied by I° spondylolisthesis and inferior articular process tip fracture; 5 cases were unilateral locked cervical spine; none case for thoracolumbar segment. The inferior articular process was crossed with the superior articular process below and moved forward, formed "back to back" form, accompanied by II°-III° spondylolisthesis. 9 or 6 cases were bilateral or unilateral locking cervical spine, 10 cases were thoracolumbar segment, accompanied by teardrop fracture in the vertebral body below cervical spine. In coronal plane of MPR, inferior articular process showed ingression in different extent, and relied on the superior articular process below or locked in the articular fossa (21 cases for cervical spine); inferior articular process displayed upward displacement or appeared with the superior articular process at the same time, which meant joint structure disappearing thoracolumbar segment (10 cases). In 3D reconstruction, 31 cases displayed clearly in the spatial form of vertebral facet joints locking and the degree of spondylolisthesis of vertebral body.
 MPR and 3D image were more clear and intuitive in vertebral facet joints locking comparing to axial CT scan image. Spiral CT MPR and 3D reconstruction contributed to the diagnosis of vertebral facet joints locking and the reduction of misdiagnoses

  5. Automated cardiac motion compensation in PET/CT for accurate reconstruction of PET myocardial perfusion images

    NASA Astrophysics Data System (ADS)

    Khurshid, Khawar; McGough, Robert J.; Berger, Kevin

    2008-10-01

    Error-free reconstruction of PET data with a registered CT attenuation map is essential for accurate quantification and interpretation of cardiac perfusion. Misalignment of the CT and PET data can produce an erroneous attenuation map that projects lung attenuation parameters onto the heart wall, thereby underestimating the attenuation and creating artifactual areas of hypoperfusion that can be misinterpreted as myocardial ischemia or infarction. The major causes of misregistration between CT and PET images are the respiratory motion, cardiac motion and gross physical motion of the patient. The misalignment artifact problem is overcome with automated cardiac registration software that minimizes the alignment error between the two modalities. Results show that the automated registration process works equally well for any respiratory phase in which the CT scan is acquired. Further evaluation of this procedure on 50 patients demonstrates that the automated registration software consistently aligns the two modalities, eliminating artifactual hypoperfusion in reconstructed PET images due to PET/CT misregistration. With this registration software, only one CT scan is required for PET/CT imaging, which reduces the radiation dose required for CT-based attenuation correction and improves the clinical workflow for PET/CT.

  6. Model-based PSF and MTF estimation and validation from skeletal clinical CT images

    SciTech Connect

    Pakdel, Amirreza; Mainprize, James G.; Robert, Normand; Fialkov, Jeffery; Whyne, Cari M.

    2014-01-15

    Purpose: A method was developed to correct for systematic errors in estimating the thickness of thin bones due to image blurring in CT images using bone interfaces to estimate the point-spread-function (PSF). This study validates the accuracy of the PSFs estimated using said method from various clinical CT images featuring cortical bones. Methods: Gaussian PSFs, characterized by a different extent in the z (scan) direction than in the x and y directions were obtained using our method from 11 clinical CT scans of a cadaveric craniofacial skeleton. These PSFs were estimated for multiple combinations of scanning parameters and reconstruction methods. The actual PSF for each scan setting was measured using the slanted-slit technique within the image slice plane and the longitudinal axis. The Gaussian PSF and the corresponding modulation transfer function (MTF) are compared against the actual PSF and MTF for validation. Results: The differences (errors) between the actual and estimated full-width half-max (FWHM) of the PSFs were 0.09 ± 0.05 and 0.14 ± 0.11 mm for the xy and z axes, respectively. The overall errors in the predicted frequencies measured at 75%, 50%, 25%, 10%, and 5% MTF levels were 0.06 ± 0.07 and 0.06 ± 0.04 cycles/mm for the xy and z axes, respectively. The accuracy of the estimates was dependent on whether they were reconstructed with a standard kernel (Toshiba's FC68, mean error of 0.06 ± 0.05 mm, MTF mean error 0.02 ± 0.02 cycles/mm) or a high resolution bone kernel (Toshiba's FC81, PSF FWHM error 0.12 ± 0.03 mm, MTF mean error 0.09 ± 0.08 cycles/mm). Conclusions: The method is accurate in 3D for an image reconstructed using a standard reconstruction kernel, which conforms to the Gaussian PSF assumption but less accurate when using a high resolution bone kernel. The method is a practical and self-contained means of estimating the PSF in clinical CT images featuring cortical bones, without the need phantoms or any prior knowledge about the

  7. Image reconstruction for PET/CT scanners: past achievements and future challenges

    PubMed Central

    Tong, Shan; Alessio, Adam M; Kinahan, Paul E

    2011-01-01

    PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831

  8. Investigation of iterative image reconstruction in low-dose breast CT

    NASA Astrophysics Data System (ADS)

    Bian, Junguo; Yang, Kai; Boone, John M.; Han, Xiao; Sidky, Emil Y.; Pan, Xiaochuan

    2014-06-01

    There is interest in developing computed tomography (CT) dedicated to breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence has been found that suggests that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image total-variation minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with a focus on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics.

  9. Evaluation of accelerated iterative x-ray CT image reconstruction using floating point graphics hardware.

    PubMed

    Kole, J S; Beekman, F J

    2006-02-21

    Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.

  10. Investigation of iterative image reconstruction in low-dose breast CT.

    PubMed

    Bian, Junguo; Yang, Kai; Boone, John M; Han, Xiao; Sidky, Emil Y; Pan, Xiaochuan

    2014-06-07

    There is interest in developing computed tomography (CT) dedicated to breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence has been found that suggests that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image total-variation minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with a focus on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics.

  11. Evaluation of accelerated iterative x-ray CT image reconstruction using floating point graphics hardware

    NASA Astrophysics Data System (ADS)

    Kole, J. S.; Beekman, F. J.

    2006-02-01

    Statistical reconstruction methods offer possibilities to improve image quality as compared with analytical methods, but current reconstruction times prohibit routine application in clinical and micro-CT. In particular, for cone-beam x-ray CT, the use of graphics hardware has been proposed to accelerate the forward and back-projection operations, in order to reduce reconstruction times. In the past, wide application of this texture hardware mapping approach was hampered owing to limited intrinsic accuracy. Recently, however, floating point precision has become available in the latest generation commodity graphics cards. In this paper, we utilize this feature to construct a graphics hardware accelerated version of the ordered subset convex reconstruction algorithm. The aims of this paper are (i) to study the impact of using graphics hardware acceleration for statistical reconstruction on the reconstructed image accuracy and (ii) to measure the speed increase one can obtain by using graphics hardware acceleration. We compare the unaccelerated algorithm with the graphics hardware accelerated version, and for the latter we consider two different interpolation techniques. A simulation study of a micro-CT scanner with a mathematical phantom shows that at almost preserved reconstructed image accuracy, speed-ups of a factor 40 to 222 can be achieved, compared with the unaccelerated algorithm, and depending on the phantom and detector sizes. Reconstruction from physical phantom data reconfirms the usability of the accelerated algorithm for practical cases.

  12. Adaptive sampling of CT data for myocardial blood flow estimation from dose-reduced dynamic CT

    NASA Astrophysics Data System (ADS)

    Modgil, Dimple; Bindschadler, Michael D.; Alessio, Adam M.; La Rivière, Patrick J.

    2015-03-01

    Quantification of myocardial blood flow (MBF) can aid in the diagnosis and treatment of coronary artery disease (CAD). However, there are no widely accepted clinical methods for estimating MBF. Dynamic CT holds the promise of providing a quick and easy method to measure MBF quantitatively, however the need for repeated scans has raised concerns about the potential for high radiation dose. In our previous work, we explored techniques to reduce the patient dose by either uniformly reducing the tube current or by uniformly reducing the number of temporal frames in the dynamic CT sequence. These dose reduction techniques result in very noisy data, which can give rise to large errors in MBF estimation. In this work, we seek to investigate whether nonuniformly varying the tube current or sampling intervals can yield more accurate MBF estimates. Specifically, we try to minimize the dose and obtain the most accurate MBF estimate through addressing the following questions: when in the time attenuation curve (TAC) should the CT data be collected and at what tube current(s). We hypothesize that increasing the sampling rate and/or tube current during the time frames when the myocardial CT number is most sensitive to the flow rate, while reducing them elsewhere, can achieve better estimation accuracy for the same dose. We perform simulations of contrast agent kinetics and CT acquisitions to evaluate the relative MBF estimation performance of several clinically viable adaptive acquisition methods. We found that adaptive temporal and tube current sequences can be performed that impart an effective dose of about 5 mSv and allow for reductions in MBF estimation RMSE on the order of 11% compared to uniform acquisition sequences with comparable or higher radiation doses.

  13. Impact of iterative reconstruction on image quality of low-dose CT of the lumbar spine.

    PubMed

    Alshamari, Muhammed; Geijer, Mats; Norrman, Eva; Lidén, Mats; Krauss, Wolfgang; Jendeberg, Johan; Magnuson, Anders; Geijer, Håkan

    2017-06-01

    Background Iterative reconstruction (IR) is a recent reconstruction algorithm for computed tomography (CT) that can be used instead of the standard algorithm, filtered back projection (FBP), to reduce radiation dose and/or improve image quality. Purpose To evaluate and compare the image quality of low-dose CT of the lumbar spine reconstructed with IR to conventional FBP, without further reduction of radiation dose. Material and Methods Low-dose CT on 55 patients was performed on a Siemens scanner using 120 kV tube voltage, 30 reference mAs, and automatic dose modulation. From raw CT data, lumbar spine CT images were reconstructed with a medium filter (B41f) using FBP and four levels of IR (levels 2-5). Five reviewers scored all images on seven image quality criteria according to the European guidelines on quality criteria for CT, using a five-grade scale. A side-by-side comparison was also performed. Results There was significant improvement in image quality for IR (levels 2-4) compared to FBP. According to visual grading regression, odds ratios of all criteria with 95% confidence intervals for IR2, IR3, IR4, and IR5 were: 1.59 (1.39-1.83), 1.74 (1.51-1.99), 1.68 (1.46-1.93), and 1.08 (0.94-1.23), respectively. In the side-by-side comparison of all reconstructions, images with IR (levels 2-4) received the highest scores. The mean overall CTDIvol was 1.70 mGy (SD 0.46; range, 1.01-3.83 mGy). Image noise decreased in a linear fashion with increased strength of IR. Conclusion Iterative reconstruction at levels 2, 3, and 4 improves image quality of low-dose CT of the lumbar spine compared to FPB.

  14. Region-of-interest image reconstruction in circular cone-beam microCT

    SciTech Connect

    Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.; Chen, C.-T.; He, T.-C.; Pan Xiaochuan

    2007-12-15

    Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolution entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.

  15. Quantitative CT: technique dependence of volume estimation on pulmonary nodules.

    PubMed

    Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Colsher, James; Amurao, Maxwell; Samei, Ehsan

    2012-03-07

    Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

  16. Quantitative CT: technique dependence of volume estimation on pulmonary nodules

    NASA Astrophysics Data System (ADS)

    Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Colsher, James; Amurao, Maxwell; Samei, Ehsan

    2012-03-01

    Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.

  17. GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation

    SciTech Connect

    Jia Xun; Lou Yifei; Li Ruijiang; Song, William Y.; Jiang, Steve B.

    2010-04-15

    Purpose: Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. Methods: The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. The authors developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multigrid technique is also employed. Results: It is found that 20-40 x-ray projections are sufficient to reconstruct images with satisfactory quality for IGRT. The reconstruction time ranges from 77 to 130 s on an NVIDIA Tesla C1060 (NVIDIA, Santa Clara, CA) GPU card, depending on the number of projections used, which is estimated about 100 times faster than similar iterative reconstruction approaches. Moreover, phantom studies indicate that the algorithm enables the CBCT to be reconstructed under a scanning protocol with as low as 0.1 mA s/projection. Comparing with currently widely used full-fan head and neck scanning protocol of {approx}360 projections with 0.4 mA s/projection, it is estimated that an overall 36-72 times dose reduction has been achieved in our fast CBCT reconstruction algorithm. Conclusions: This work indicates that the developed GPU-based CBCT reconstruction algorithm is capable of lowering imaging dose considerably. The high computation efficiency in this algorithm makes the iterative CBCT reconstruction approach applicable in real clinical environments.

  18. A new CT reconstruction technique using adaptive deformation recovery and intensity correction (ADRIC).

    PubMed

    Zhang, You; Ma, Jianhua; Iyengar, Puneeth; Zhong, Yuncheng; Wang, Jing

    2017-06-01

    Sequential same-patient CT images may involve deformation-induced and non-deformation-induced voxel intensity changes. An adaptive deformation recovery and intensity correction (ADRIC) technique was developed to improve the CT reconstruction accuracy, and to separate deformation from non-deformation-induced voxel intensity changes between sequential CT images. ADRIC views the new CT volume as a deformation of a prior high-quality CT volume, but with additional non-deformation-induced voxel intensity changes. ADRIC first applies the 2D-3D deformation technique to recover the deformation field between the prior CT volume and the new, to-be-reconstructed CT volume. Using the deformation-recovered new CT volume, ADRIC further corrects the non-deformation-induced voxel intensity changes with an updated algebraic reconstruction technique ("ART-dTV"). The resulting intensity-corrected new CT volume is subsequently fed back into the 2D-3D deformation process to further correct the residual deformation errors, which forms an iterative loop. By ADRIC, the deformation field and the non-deformation voxel intensity corrections are optimized separately and alternately to reconstruct the final CT. CT myocardial perfusion imaging scenarios were employed to evaluate the efficacy of ADRIC, using both simulated data of the extended-cardiac-torso (XCAT) digital phantom and experimentally acquired porcine data. The reconstruction accuracy of the ADRIC technique was compared to the technique using ART-dTV alone, and to the technique using 2D-3D deformation alone. The relative error metric and the universal quality index metric are calculated between the images for quantitative analysis. The relative error is defined as the square root of the sum of squared voxel intensity differences between the reconstructed volume and the "ground-truth" volume, normalized by the square root of the sum of squared "ground-truth" voxel intensities. In addition to the XCAT and porcine studies, a physical

  19. Low Dose CT Reconstruction via Edge-preserving Total Variation Regularization

    PubMed Central

    Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

    2014-01-01

    High radiation dose in CT scans increases a lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with Total Variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing an energy consisting of an edge-preserving TV norm and a data fidelity term posed by the x-ray projections. The edge-preserving TV term is proposed to preferentially perform smoothing only on non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original total variation norm. During the reconstruction process, the pixels at edges would be gradually identified and given small penalty weight. Our iterative algorithm is implemented on GPU to improve its speed. We test our reconstruction algorithm on a digital NCAT phantom, a physical chest phantom, and a Catphan phantom. Reconstruction results from a conventional FBP algorithm and a TV regularization method without edge preserving penalty are also presented for comparison purpose. The experimental results illustrate that both TV-based algorithm and our edge-preserving TV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under the low dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low contrast structures and therefore maintain acceptable spatial resolution. PMID:21860076

  20. Low-dose CT reconstruction via edge-preserving total variation regularization

    NASA Astrophysics Data System (ADS)

    Tian, Zhen; Jia, Xun; Yuan, Kehong; Pan, Tinsu; Jiang, Steve B.

    2011-09-01

    High radiation dose in computed tomography (CT) scans increases the lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with total variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low-contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV (EPTV) regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing energy consisting of an EPTV norm and a data fidelity term posed by the x-ray projections. The EPTV term is proposed to preferentially perform smoothing only on the non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original TV norm. During the reconstruction process, the pixels at the edges would be gradually identified and given low penalty weight. Our iterative algorithm is implemented on graphics processing unit to improve its speed. We test our reconstruction algorithm on a digital NURBS-based cardiac-troso phantom, a physical chest phantom and a Catphan phantom. Reconstruction results from a conventional filtered backprojection (FBP) algorithm and a TV regularization method without edge-preserving penalty are also presented for comparison purposes. The experimental results illustrate that both the TV-based algorithm and our EPTV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under a low-dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low-contrast structures and therefore maintain acceptable spatial resolution.

  1. WE-EF-207-07: Dual Energy CT with One Full Scan and a Second Sparse-View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

    SciTech Connect

    Wang, T; Zhu, L

    2015-06-15

    Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CT scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan can

  2. Improving image-guided radiation therapy of lung cancer by reconstructing 4D-CT from a single free-breathing 3D-CT on the treatment day.

    PubMed

    Wu, Guorong; Lian, Jun; Shen, Dinggang

    2012-12-01

    registering the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built on the planning day. We first evaluated the accuracy of our 4D-CT model on a set of lung 4D-CT images with manually labeled landmarks, where the maximum error in respiratory motion estimation can be reduced from 6.08 mm by diffeomorphic Demons to 3.67 mm by our method. Next, we evaluated our proposed 4D-CT reconstruction algorithm on both simulated and real free-breathing images. The reconstructed 4D-CT using our algorithm shows clinically acceptable accuracy and could be used to guide a more accurate patient setup than the conventional method. We have proposed a novel two-step method to reconstruct a new 4D-CT from a single free-breathing 3D-CT on the treatment day. Promising reconstruction results imply the possible application of this new algorithm in the image guided radiation therapy of lung cancer.

  3. Sparse angular CT reconstruction using non-local means based iterative-correction POCS.

    PubMed

    Huang, Jing; Ma, Jianhua; Liu, Nan; Zhang, Hua; Bian, Zhaoying; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan

    2011-04-01

    In divergent-beam computed tomography (CT), sparse angular sampling frequently leads to conspicuous streak artifacts. In this paper, we propose a novel non-local means (NL-means) based iterative-correction projection onto convex sets (POCS) algorithm, named as NLMIC-POCS, for effective and robust sparse angular CT reconstruction. The motivation for using NLMIC-POCS is that NL-means filtered image can produce an acceptable priori solution for sequential POCS iterative reconstruction. The NLMIC-POCS algorithm has been tested on simulated and real phantom data. The experimental results show that the presented NLMIC-POCS algorithm can significantly improve the image quality of the sparse angular CT reconstruction in suppressing streak artifacts and preserving the edges of the image.

  4. Combining ordered subsets and momentum for accelerated X-ray CT image reconstruction.

    PubMed

    Kim, Donghwan; Ramani, Sathish; Fessler, Jeffrey A

    2015-01-01

    Statistical X-ray computed tomography (CT) reconstruction can improve image quality from reduced dose scans, but requires very long computation time. Ordered subsets (OS) methods have been widely used for research in X-ray CT statistical image reconstruction (and are used in clinical PET and SPECT reconstruction). In particular, OS methods based on separable quadratic surrogates (OS-SQS) are massively parallelizable and are well suited to modern computing architectures, but the number of iterations required for convergence should be reduced for better practical use. This paper introduces OS-SQS-momentum algorithms that combine Nesterov's momentum techniques with OS-SQS methods, greatly improving convergence speed in early iterations. If the number of subsets is too large, the OS-SQS-momentum methods can be unstable, so we propose diminishing step sizes that stabilize the method while preserving the very fast convergence behavior. Experiments with simulated and real 3D CT scan data illustrate the performance of the proposed algorithms.

  5. Acetabular Cartilage Thickness: Accuracy of Three-Dimensional Reconstructions from Multidetector CT Arthrograms in a Cadaver Study1

    PubMed Central

    Allen, Bryce C; Peters, Christopher L.; Brown, Nicholas A. T.; Anderson, Andrew E.

    2010-01-01

    Purpose: To prospectively quantify the accuracy of hip cartilage thickness estimated from three-dimensional (3D) surfaces, generated by segmenting multidetector computed tomographic (CT) arthrograms by using direct physical measurements of cartilage thickness as the reference standard. Materials and Methods: Four fresh-frozen cadaver hip joints from two male donors, ages 43 and 46 years, were obtained; institutional review board approval for cadaver research was also obtained. Sixteen holes were drilled perpendicular to the cartilage of four cadaveric acetabula (two specimens). Hip capsules were surgically closed, injected with contrast material, and scanned by using multidetector CT. After scanning, 5.3-mmcores were harvested concentrically at each drill hole and cartilage thickness was measured with a microscope. Cartilage was reconstructed in 3D by using commercial software. Segmentations were repeated by two authors. Reconstructed cartilage thickness was determined by using a published algorithm. Bland-Altman plots and linear regression were used to assess accuracy. Repeatability was quantified by using the coefficient of variation, intraclass correlation coefficient (ICC), repeatability coefficient, and percentage variability. Results: Cartilage was reconstructed to a bias of −0.13 mm and a repeatability coefficient of ±0.46 mm. Regression of the scatterplots indicated a tendency for multidetector CT to overestimate thickness. Intra- and interobserver repeatability were very good. For intraobserver correlation, the coefficient of variation was 14.80%, the ICC was 0.88, the repeatability coefficient was 0.55 mm, and the percentage variability was 11.77%. For interobserver correlation, the coefficient of variation was 13.47%, the ICC was 0.90, the repeatability coefficient was 0.52 mm, and the percentage variability was 11.63%. Conclusion: Assuming that an accuracy of approximately ±0.5 mm is sufficient, reconstructions of cartilage geometry from

  6. Sparse-view X-ray CT Reconstruction via Total Generalized Variation Regularization

    PubMed Central

    Niu, Shanzhou; Gao, Yang; Bian, Zhaoying; Huang, Jing; Chen, Wufan; Yu, Gaohang; Liang, Zhengrong; Ma, Jianhua

    2014-01-01

    Sparse-view CT reconstruction algorithms via total variation (TV) optimize the data iteratively on the basis of a noise- and artifact-reducing model, resulting in significant radiation dose reduction while maintaining image quality. However, the piecewise constant assumption of TV minimization often leads to the appearance of noticeable patchy artifacts in reconstructed images. To obviate this drawback, we present a penalized weighted least-squares (PWLS) scheme to retain the image quality by incorporating the new concept of total generalized variation (TGV) regularization. We refer to the proposed scheme as “PWLS-TGV” for simplicity. Specifically, TGV regularization utilizes higher order derivatives of the objective image, and the weighted least-squares term considers data-dependent variance estimation, which fully contribute to improving the image quality with sparse-view projection measurement. Subsequently, an alternating optimization algorithm was adopted to minimize the associative objective function. To evaluate the PWLS-TGV method, both qualitative and quantitative studies were conducted by using digital and physical phantoms. Experimental results show that the present PWLS-TGV method can achieve images with several noticeable gains over the original TV-based method in terms of accuracy and resolution properties. PMID:24842150

  7. An iterative reconstruction method for high-pitch helical luggage CT

    NASA Astrophysics Data System (ADS)

    Xue, Hui; Zhang, Li; Chen, Zhiqiang; Jin, Xin

    2012-10-01

    X-ray luggage CT is widely used in airports and railway stations for the purpose of detecting contrabands and dangerous goods that may be potential threaten to public safety, playing an important role in homeland security. An X-ray luggage CT is usually in a helical trajectory with a high pitch for achieving a high passing speed of the luggage. The disadvantage of high pitch is that conventional filtered back-projection (FBP) requires a very large slice thickness, leading to bad axial resolution and helical artifacts. Especially when severe data inconsistencies are present in the z-direction, like the ends of a scanning object, the partial volume effect leads to inaccuracy value and may cause a wrong identification. In this paper, an iterative reconstruction method is developed to improve the image quality and accuracy for a large-spacing multi-detector high-pitch helical luggage CT system. In this method, the slice thickness is set to be much smaller than the pitch. Each slice involves projection data collected in a rather small angular range, being an ill-conditioned limited-angle problem. Firstly a low-resolution reconstruction is employed to obtain images, which are used as prior images in the following process. Then iterative reconstruction is performed to obtain high-resolution images. This method enables a high volume coverage speed and a thin reconstruction slice for the helical luggage CT. We validate this method with data collected in a commercial X-ray luggage CT.

  8. [Spiral computerized tomography with tridimensional reconstruction (spiral 3D CT) in the study of maxillofacial pathology].

    PubMed

    Mevio, E; Calabrò, P; Preda, L; Di Maggio, E M; Caprotti, A

    1995-12-01

    Three dimensional computer reconstruction of CT scans provide head and neck surgeons with an exciting interactive display of clinical anatomy. The 3D CT reconstruction of complex maxillo facial anatomic parts permits a more specific preoperative analysis and surgical planning. Its delineation of disease extension aids the surgeon in developing his own mental three-dimensional image of the regional morphology. Three-dimensional CT permits a clearer perception of the extent of fracture comminution and resulting displacement of fragments. In the case of maxillo-facial tumors, 3D images provide a very clear picture of the extent of erosion involving the adjacent critical organs. Three-dimensional imaging in first generation 3D scanners did have some limitations such as long reconstruction times and inadequate resolution. Subsequent generations, in particular the spiral 3D CT, have eliminated these drawbacks. Furthermore, costs are comparable with those of other computer reconstruction technology that might provide similar images. Representative cases demonstrating the use of 3D CT in maxillofacial surgery and its benefits in planning surgery are discussed.

  9. Pitfalls in image reconstruction of helical CT angiography: an experimental study.

    PubMed

    Ogata, I; Yamashita, Y; Sumi, S; Nishiharu, T; Mitsuzaki, K; Takahashi, M

    1999-01-01

    This study was undertaken to evaluate the effects of the object related factors: background tissue and the direction of vessels on the morphological reproducibility of helical CT angiography. Cylindrical tubes filled with a diluted contrast medium were prepared to obtain vascular phantoms. The scan was performed within various background tissues. For the evaluation of the direction of the vessels, two types of vascular phantoms were prepared. The phantoms were scanned by varying beam collimations and scan pitches. Reconstructed CT images were markedly affected by the background tissue. The reconstructed images were also affected by the direction of vessels.

  10. Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction

    SciTech Connect

    Min, Jonghwan; Pua, Rizza; Cho, Seungryong; Kim, Insoo; Han, Bumsoo

    2015-11-15

    Purpose: A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. Methods: The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. Results: The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. Conclusions: The authors have successfully demonstrated that the

  11. Analytic image reconstruction from partial data for a single-scan cone-beam CT with scatter correction.

    PubMed

    Min, Jonghwan; Pua, Rizza; Kim, Insoo; Han, Bumsoo; Cho, Seungryong

    2015-11-01

    A beam-blocker composed of multiple strips is a useful gadget for scatter correction and/or for dose reduction in cone-beam CT (CBCT). However, the use of such a beam-blocker would yield cone-beam data that can be challenging for accurate image reconstruction from a single scan in the filtered-backprojection framework. The focus of the work was to develop an analytic image reconstruction method for CBCT that can be directly applied to partially blocked cone-beam data in conjunction with the scatter correction. The authors developed a rebinned backprojection-filteration (BPF) algorithm for reconstructing images from the partially blocked cone-beam data in a circular scan. The authors also proposed a beam-blocking geometry considering data redundancy such that an efficient scatter estimate can be acquired and sufficient data for BPF image reconstruction can be secured at the same time from a single scan without using any blocker motion. Additionally, scatter correction method and noise reduction scheme have been developed. The authors have performed both simulation and experimental studies to validate the rebinned BPF algorithm for image reconstruction from partially blocked cone-beam data. Quantitative evaluations of the reconstructed image quality were performed in the experimental studies. The simulation study revealed that the developed reconstruction algorithm successfully reconstructs the images from the partial cone-beam data. In the experimental study, the proposed method effectively corrected for the scatter in each projection and reconstructed scatter-corrected images from a single scan. Reduction of cupping artifacts and an enhancement of the image contrast have been demonstrated. The image contrast has increased by a factor of about 2, and the image accuracy in terms of root-mean-square-error with respect to the fan-beam CT image has increased by more than 30%. The authors have successfully demonstrated that the proposed scanning method and image

  12. Single-slice reconstruction method for helical cone-beam differential phase-contrast CT.

    PubMed

    Fu, Jian; Chen, Liyuan

    2014-01-01

    X-ray phase-contrast computed tomography (PC-CT) can provide the internal structure information of biomedical specimens with high-quality cross-section images and has become an invaluable analysis tool. Here a simple and fast reconstruction algorithm is reported for helical cone-beam differential PC-CT (DPC-CT), which is called the DPC-CB-SSRB algorithm. It combines the existing CB-SSRB method of helical cone-beam absorption-contrast CT with the differential nature of DPC imaging. The reconstruction can be performed using 2D fan-beam filtered back projection algorithm with the Hilbert imaginary filter. The quality of the results for large helical pitches is surprisingly good. In particular, with this algorithm comparable quality is obtained using helical cone-beam DPC-CT data with a normalized pitch of 10 to that obtained using the traditional inter-row interpolation reconstruction with a normalized pitch of 2. This method will push the future medical helical cone-beam DPC-CT imaging applications.

  13. A framelet-based iterative maximum-likelihood reconstruction algorithm for spectral CT

    NASA Astrophysics Data System (ADS)

    Wang, Yingmei; Wang, Ge; Mao, Shuwei; Cong, Wenxiang; Ji, Zhilong; Cai, Jian-Feng; Ye, Yangbo

    2016-11-01

    Standard computed tomography (CT) cannot reproduce spectral information of an object. Hardware solutions include dual-energy CT which scans the object twice in different x-ray energy levels, and energy-discriminative detectors which can separate lower and higher energy levels from a single x-ray scan. In this paper, we propose a software solution and give an iterative algorithm that reconstructs an image with spectral information from just one scan with a standard energy-integrating detector. The spectral information obtained can be used to produce color CT images, spectral curves of the attenuation coefficient μ (r,E) at points inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. Our software solution requires no change on hardware of a CT machine. With the Shepp-Logan phantom, we have found that although the photoelectric and Compton components were not perfectly reconstructed, their composite effect was very accurately reconstructed as compared to the ground truth and the dual-energy CT counterpart. This means that our proposed method has an intrinsic benefit in beam hardening correction and metal artifact reduction. The algorithm is based on a nonlinear polychromatic acquisition model for x-ray CT. The key technique is a sparse representation of iterations in a framelet system. Convergence of the algorithm is studied. This is believed to be the first application of framelet imaging tools to a nonlinear inverse problem.

  14. Precision of iodine quantification in hepatic CT: effects of reconstruction (FBP and MBIR) and imaging parameters

    NASA Astrophysics Data System (ADS)

    Chen, Baiyu; Samei, Ehsan; Colsher, James; Barnhart, Huiman; Marin, Daniele; Nelson, Rendon

    2011-03-01

    In hepatic CT imaging, the lesion enhancement after the injection of contrast media is of quantitative interest. However, the precision of this quantitative measurement may be dependent on the imaging techniques such as dose and reconstruction algorithm. To determine the impact of different techniques, we scanned an iodinated liver phantom with acquisition protocols of different dose levels, and reconstructed images with different algorithms (FBP and MBIR) and slice thicknesses. The contrast of lesions was quantified from the images, and its precision was calculated for each protocol separately. Results showed that precision was improved by increasing dose, increasing slice thickness, and using MBIR reconstruction. When using MBIR instead of FBP, the same precision can be achieved at 50% less dose. To our knowledge, this is the first investigation of the quantification precision in hepatic CT imaging using iterative reconstructions.

  15. Improved Compressed Sensing-Based Algorithm for Sparse-View CT Image Reconstruction

    PubMed Central

    Babyn, Paul; Cooper, David; Pratt, Isaac

    2013-01-01

    In computed tomography (CT), there are many situations where reconstruction has to be performed with sparse-view data. In sparse-view CT imaging, strong streak artifacts may appear in conventionally reconstructed images due to limited sampling rate that compromises image quality. Compressed sensing (CS) algorithm has shown potential to accurately recover images from highly undersampled data. In the past few years, total-variation-(TV-) based compressed sensing algorithms have been proposed to suppress the streak artifact in CT image reconstruction. In this paper, we propose an efficient compressed sensing-based algorithm for CT image reconstruction from few-view data where we simultaneously minimize three parameters: the ℓ 1 norm, total variation, and a least squares measure. The main feature of our algorithm is the use of two sparsity transforms—discrete wavelet transform and discrete gradient transform. Experiments have been conducted using simulated phantoms and clinical data to evaluate the performance of the proposed algorithm. The results using the proposed scheme show much smaller streaking artifacts and reconstruction errors than other conventional methods. PMID:23606898

  16. Investigation on viewing direction dependent detectability in a reconstructed 3D volume for a cone beam CT system

    NASA Astrophysics Data System (ADS)

    Park, Junhan; Lee, Changwoo; Baek, Jongduk

    2015-03-01

    In medical imaging systems, several factors (e.g., reconstruction algorithm, noise structures, target size, contrast, etc) affect the detection performance and need to be considered for object detection. In a cone beam CT system, FDK reconstruction produces different noise structures in axial and coronal slices, and thus we analyzed directional dependent detectability of objects using detection SNR of Channelized Hotelling observer. To calculate the detection SNR, difference-of-Gaussian channel model with 10 channels was implemented, and 20 sphere objects with different radius (i.e., 0.25 (mm) to 5 (mm) equally spaced by 0.25 (mm)), reconstructed by FDK algorithm, were used as object templates. Covariance matrix in axial and coronal direction was estimated from 3000 reconstructed noise volumes, and then the SNR ratio between axial and coronal direction was calculated. Corresponding 2D noise power spectrum was also calculated. The results show that as the object size increases, the SNR ratio decreases, especially lower than 1 when the object size is larger than 2.5 mm radius. The reason is because the axial (coronal) noise power is higher in high (low) frequency band, and therefore the detectability of a small (large) object is higher in coronal (axial) images. Our results indicate that it is more beneficial to use coronal slices in order to improve the detectability of a small object in a cone beam CT system.

  17. The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK)

    NASA Astrophysics Data System (ADS)

    Rit, S.; Vila Oliva, M.; Brousmiche, S.; Labarbe, R.; Sarrut, D.; Sharp, G. C.

    2014-03-01

    We propose the Reconstruction Toolkit (RTK, http://www.openrtk.org), an open-source toolkit for fast cone-beam CT reconstruction, based on the Insight Toolkit (ITK) and using GPU code extracted from Plastimatch. RTK is developed by an open consortium (see affiliations) under the non-contaminating Apache 2.0 license. The quality of the platform is daily checked with regression tests in partnership with Kitware, the company supporting ITK. Several features are already available: Elekta, Varian and IBA inputs, multi-threaded Feldkamp-David-Kress reconstruction on CPU and GPU, Parker short scan weighting, multi-threaded CPU and GPU forward projectors, etc. Each feature is either accessible through command line tools or C++ classes that can be included in independent software. A MIDAS community has been opened to share CatPhan datasets of several vendors (Elekta, Varian and IBA). RTK will be used in the upcoming cone-beam CT scanner developed by IBA for proton therapy rooms. Many features are under development: new input format support, iterative reconstruction, hybrid Monte Carlo / deterministic CBCT simulation, etc. RTK has been built to freely share tomographic reconstruction developments between researchers and is open for new contributions.

  18. FFT and cone-beam CT reconstruction on graphics hardware

    NASA Astrophysics Data System (ADS)

    Després, Philippe; Sun, Mingshan; Hasegawa, Bruce H.; Prevrhal, Sven

    2007-03-01

    Graphics processing units (GPUs) are increasingly used for general purpose calculations. Their pipelined architecture can be exploited to accelerate various parallelizable algorithms. Medical imaging applications are inherently well suited to benefit from the development of GPU-based computational platforms. We evaluate in this work the potential of GPUs to improve the execution speed of two common medical imaging tasks, namely Fourier transforms and tomographic reconstructions. A two-dimensional fast Fourier transform (FFT) algorithm was GPU-implemented and compared, in terms of execution speed, to two popular CPU-based FFT routines. Similarly, the Feldkamp, David and Kress (FDK) algorithm for cone-beam tomographic reconstruction was implemented on the GPU and its performance compared to a CPU version. Different reconstruction strategies were employed to assess the performance of various GPU memory layouts. For the specific hardware used, GPU implementations of the FFT were up to 20 times faster than their CPU counterparts, but slower than highly optimized CPU versions of the algorithm. Tomographic reconstructions were faster on the GPU by a factor up to 30, allowing 256 3 voxel reconstructions of 256 projections in about 20 seconds. Overall, GPUs are an attractive alternative to other imaging-dedicated computing hardware like application-specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs) in terms of cost, simplicity and versatility. With the development of simpler language extensions and programming interfaces, GPUs are likely to become essential tools in medical imaging.

  19. Estimating mineral changes in enamel formation by ashing/BSE and microCT.

    PubMed

    Schmitz, J E; Teepe, J D; Hu, Y; Smith, C E; Fajardo, R J; Chun, Y-H P

    2014-03-01

    Enamel formation produces the most highly mineralized tissue in the human body. The growth of enamel crystallites is assisted by enamel proteins and proteinases. As enamel formation progresses from secretory to maturation stages, the composition of the matrix with its mineral and non-mineral components dynamically changes in an inverse fashion. We hypothesized that appropriately calibrated micro-computed tomography (µCT) technology is suitable to estimate the mineral content (weight and/or density) and volume comparable in accuracy with that for directly weighed and sectioned enamel. Different sets of mouse mandibular incisors of C57BL/6 mice were used for dissections and µCT reconstructions. Calibration phantoms corresponding to the range of enamel mineral densities were used. Secretory-stage enamel contained little mineral and was consequently too poor in contrast for enamel volumes to be accurately estimated by µCT. Maturation-stage enamel, however, showed remarkable correspondence for total mineral content per volume where comparisons were possible between and among the different analytical techniques used. The main advantages of the µCT approach are that it is non-destructive, time-efficient, and can monitor changes in mineral content of the most mature enamel, which is too physically hard to dissect away from the tooth.

  20. Estimating Mineral Changes in Enamel Formation by Ashing/BSE and MicroCT

    PubMed Central

    Schmitz, J.E.; Teepe, J.D.; Hu, Y.; Smith, C.E.; Fajardo, R.J.; Chun, Y.-H.P.

    2014-01-01

    Enamel formation produces the most highly mineralized tissue in the human body. The growth of enamel crystallites is assisted by enamel proteins and proteinases. As enamel formation progresses from secretory to maturation stages, the composition of the matrix with its mineral and non-mineral components dynamically changes in an inverse fashion. We hypothesized that appropriately calibrated micro-computed tomography (µCT) technology is suitable to estimate the mineral content (weight and/or density) and volume comparable in accuracy with that for directly weighed and sectioned enamel. Different sets of mouse mandibular incisors of C57BL/6 mice were used for dissections and µCT reconstructions. Calibration phantoms corresponding to the range of enamel mineral densities were used. Secretory-stage enamel contained little mineral and was consequently too poor in contrast for enamel volumes to be accurately estimated by µCT. Maturation-stage enamel, however, showed remarkable correspondence for total mineral content per volume where comparisons were possible between and among the different analytical techniques used. The main advantages of the µCT approach are that it is non-destructive, time-efficient, and can monitor changes in mineral content of the most mature enamel, which is too physically hard to dissect away from the tooth. PMID:24470541

  1. Few-view cone-beam CT reconstruction with deformed prior image

    SciTech Connect

    Zhang, Hua; Ouyang, Luo; Wang, Jing E-mail: jing.wang@utsouthwestern.edu; Huang, Jing; Ma, Jianhua E-mail: jing.wang@utsouthwestern.edu; Chen, Wufan

    2014-12-15

    Purpose: Prior images can be incorporated into the image reconstruction process to improve the quality of subsequent cone-beam CT (CBCT) images from sparse-view or low-dose projections. The purpose of this work is to develop a deformed prior image-based reconstruction (DPIR) strategy to mitigate the deformation between the prior image and the target image. Methods: The deformed prior image is obtained by a projection-based registration approach. Specifically, the deformation vector fields used to deform the prior image are estimated through iteratively matching the forward projection of the deformed prior image and the measured on-treatment projections. The deformed prior image is then used as the prior image in the standard prior image constrained compressed sensing (PICCS) algorithm. A simulation study on an XCAT phantom and a clinical study on a head-and-neck cancer patient were conducted to evaluate the performance of the proposed DPIR strategy. Results: The deformed prior image matches the geometry of the on-treatment CBCT more closely as compared to the original prior image. Consequently, the performance of the DPIR strategy from few-view projections is improved in comparison to the standard PICCS algorithm, based on both visual inspection and quantitative measures. In the XCAT phantom study using 20 projections, the average root mean squared error is reduced from 14% in PICCS to 10% in DPIR, and the average universal quality index increases from 0.88 in PICCS to 0.92 in DPIR. Conclusions: The present DPIR approach provides a practical solution to the mismatch problem between the prior image and target image, which improves the performance of the original PICCS algorithm for CBCT reconstruction from few-view or low-dose projections.

  2. Effects of voxel size and iterative reconstruction parameters on the spatial resolution of 99mTc SPECT/CT.

    PubMed

    Kappadath, S Cheenu

    2011-11-15

    The purpose of this study was to evaluate the effects of voxel size and iterative reconstruction parameters on the radial and tangential resolution for 99mTc SPECT as a function of radial distance from isocenter. SPECT/CT scans of eight coplanar point sources of size smaller than 1 mm3 containing high concentration 99mTc solution were acquired on a SPECT/CT system with 5/8 inch NaI(Tl) detector and low-energy, high-resolution collimator. The tomographic projection images were acquired in step-and-shoot mode for 360 views over 360° with 250,000 counts per view, a zoom of 2.67, and an image matrix of 256 × 256 pixels that resulted in a 0.9 × 0.9 × 0.9 mm3 SPECT voxel size over 230 mm field-of-view. The projection images were also rebinned to image matrices of 128 × 128 and 64 × 64 to yield SPECT voxel sizes of 1.8 × 1.8 × 1.8 and 3.6 × 3.6 × 3.6 mm3, respectively. The SPECT/CT datasets were reconstructed using the vendor-supplied iterative reconstruction software that incorporated collimator-specific resolution recovery, CT-based attenuation correction, and dual-energy window-based scatter correction using different combinations of iterations and subsets. SPECT spatial resolution was estimated as the full width at half maximum of the radial and tangential profiles through the center of each point source in reconstructed SPECT images. Both radial and tangential resolution improved with higher iterations and subsets, and with smaller voxel sizes. Both radial and tangential resolution also improved with radial distance further away from isocenter. The magnitude of variation decreased for smaller voxel sizes and for higher number of iterations and subsets. Tangential resolution was found not to be equal to the radial resolution, and the nature of the anisotropy depended on the distribution of the radionuclide and on the reconstruction parameters used. The tangential resolution converged faster than the radial resolution, with higher iterations and subsets

  3. Edge guided image reconstruction in linear scan CT by weighted alternating direction TV minimization.

    PubMed

    Cai, Ailong; Wang, Linyuan; Zhang, Hanming; Yan, Bin; Li, Lei; Xi, Xiaoqi; Li, Jianxin

    2014-01-01

    Linear scan computed tomography (CT) is a promising imaging configuration with high scanning efficiency while the data set is under-sampled and angularly limited for which high quality image reconstruction is challenging. In this work, an edge guided total variation minimization reconstruction (EGTVM) algorithm is developed in dealing with this problem. The proposed method is modeled on the combination of total variation (TV) regularization and iterative edge detection strategy. In the proposed method, the edge weights of intermediate reconstructions are incorporated into the TV objective function. The optimization is efficiently solved by applying alternating direction method of multipliers. A prudential and conservative edge detection strategy proposed in this paper can obtain the true edges while restricting the errors within an acceptable degree. Based on the comparison on both simulation studies and real CT data set reconstructions, EGTVM provides comparable or even better quality compared to the non-edge guided reconstruction and adaptive steepest descent-projection onto convex sets method. With the utilization of weighted alternating direction TV minimization and edge detection, EGTVM achieves fast and robust convergence and reconstructs high quality image when applied in linear scan CT with under-sampled data set.

  4. Multienergy CT acquisition and reconstruction with a stepped tube potential scan

    SciTech Connect

    Shen, Le; Xing, Yuxiang

    2015-01-15

    Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed Seg

  5. A fast method based on NESTA to accurately reconstruct CT image from highly undersampled projection measurements.

    PubMed

    He, Zhijie; Qiao, Quanbang; Li, Jun; Huang, Meiping; Zhu, Shouping; Huang, Liyu

    2016-11-22

    The CT image reconstruction algorithm based compressed sensing (CS) can be formulated as an optimization problem that minimizes the total-variation (TV) term constrained by the data fidelity and image nonnegativity. There are a lot of solutions to this problem, but the computational efficiency and reconstructed image quality of these methods still need to be improved. To investigate a faster and more accurate mathematical algorithm to settle TV term minimization problem of CT image reconstruction. A Nesterov's algorithm (NESTA) is a fast and accurate algorithm for solving TV minimization problem, which can be ascribed to the use of most notably Nesterov's smoothing technique and a subtle averaging of sequences of iterates, which has been shown to improve the convergence properties of standard gradient-descent algorithms. In order to demonstrate the superior performance of NESTA on computational efficiency and image quality, a comparison with Simultaneous Algebraic Reconstruction Technique-TV (SART-TV) and Split-Bregman (SpBr) algorithm is made using a digital phantom study and two physical phantom studies from highly undersampled projection measurements. With only 25% of conventional full-scan dose and, NESTA method reduces the average CT number error from 51.76HU to 9.98HU on Shepp-Logan phantom and reduces the average CT number error from 50.13HU to 0.32HU on Catphan 600 phantom. On an anthropomorphic head phantom, the average CT number error is reduced from 84.21HU to 1.01HU in the central uniform area. To the best of our knowledge this is the first work that apply the NESTA method into CT reconstruction based CS. Research shows that this method is of great potential, further studies and optimization are necessary.

  6. Three-dimensional cone-beam region-of-interest (ROI) CT reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Ruijie Rachel

    2001-06-01

    ROI cone-beam (CB) CT is proposed in this thesis as a new technique in which a set of partially filtered ROI images is used for CT reconstruction. It can be used in neural surgery as fluoroscopy 3D CT images with reduced dose outside the ROL Depending on the contrast resolution requirement of the CT images and therefore the thickness of the ROI filter, the dose can be reduced by 50%-70%. In this study, the shape of the ROI is rectangular in the middle of the image. In order to do CB reconstruction, the image distortion has to be corrected, because all the images were acquired by the image intensifier (II) where distortion occurs. We proposed a new method, named as super-global (SG) model with a set of parameters, to do distortion correction for all the images in a rotational run. The SG model is carefully tested and compared with the conventional global correction method Study shows that it is an accurate efficient method for the distortion correction of images acquired by rotational C-arms. The intensity of ROI images has to be equalized within and without ROI after distortion correction. First, the edge is detected; then equalization factors are applied to the filtered areas. Now the distortion-free and intensity-equalized images are used for CB backprojection to reconstruct the 3D CT images by Feldkamp algorithm. This algorithm is tested by a mathematical phantom reconstruction. Iso-center correction and uniform scattering subtraction is discussed and applied in the experimental phantom reconstruction. We took images of a phantom and a rabbit with and without contrast medium injection, and with and without ROI filtration. Their 3D CT images were obtained. For the rabbit, vascular CT images were obtained by subtracting CT images with contrast medium from those without contrast. The CT images of the ROI edges are in good shape, and no obvious artifact is observed. Though the filtered area has higher noise, its intensify is equalized pretty well with that of the

  7. Micro-CT images reconstruction and 3D visualization for small animal studying

    NASA Astrophysics Data System (ADS)

    Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng

    2005-01-01

    A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.

  8. Sparse CT reconstruction based on multi-direction anisotropic total variation (MDATV)

    PubMed Central

    2014-01-01

    Background The sparse CT (Computed Tomography), inspired by compressed sensing, means to introduce a prior information of image sparsity into CT reconstruction to reduce the input projections so as to reduce the potential threat of incremental X-ray dose to patients’ health. Recently, many remarkable works were concentrated on the sparse CT reconstruction from sparse (limited-angle or few-view style) projections. In this paper we would like to incorporate more prior information into the sparse CT reconstruction for improvement of performance. It is known decades ago that the given projection directions can provide information about the directions of edges in the restored CT image. ATV (Anisotropic Total Variation), a TV (Total Variation) norm based regularization, could use the prior information of image sparsity and edge direction simultaneously. But ATV can only represent the edge information in few directions and lose much prior information of image edges in other directions. Methods To sufficiently use the prior information of edge directions, a novel MDATV (Multi-Direction Anisotropic Total Variation) is proposed. In this paper we introduce the 2D-IGS (Two Dimensional Image Gradient Space), and combined the coordinate rotation transform with 2D-IGS to represent edge information in multiple directions. Then by incorporating this multi-direction representation into ATV norm we get the MDATV regularization. To solve the optimization problem based on the MDATV regularization, a novel ART (algebraic reconstruction technique) + MDATV scheme is outlined. And NESTA (NESTerov’s Algorithm) is proposed to replace GD (Gradient Descent) for minimizing the TV-based regularization. Results The numerical and real data experiments demonstrate that MDATV based iterative reconstruction improved the quality of restored image. NESTA is more suitable than GD for minimization of TV-based regularization. Conclusions MDATV regularization can sufficiently use the prior

  9. Sparse CT reconstruction based on multi-direction anisotropic total variation (MDATV).

    PubMed

    Li, Hongxiao; Chen, Xiaodong; Wang, Yi; Zhou, Zhongxing; Zhu, Qingzhen; Yu, Daoyin

    2014-07-04

    The sparse CT (Computed Tomography), inspired by compressed sensing, means to introduce a prior information of image sparsity into CT reconstruction to reduce the input projections so as to reduce the potential threat of incremental X-ray dose to patients' health. Recently, many remarkable works were concentrated on the sparse CT reconstruction from sparse (limited-angle or few-view style) projections. In this paper we would like to incorporate more prior information into the sparse CT reconstruction for improvement of performance. It is known decades ago that the given projection directions can provide information about the directions of edges in the restored CT image. ATV (Anisotropic Total Variation), a TV (Total Variation) norm based regularization, could use the prior information of image sparsity and edge direction simultaneously. But ATV can only represent the edge information in few directions and lose much prior information of image edges in other directions. To sufficiently use the prior information of edge directions, a novel MDATV (Multi-Direction Anisotropic Total Variation) is proposed. In this paper we introduce the 2D-IGS (Two Dimensional Image Gradient Space), and combined the coordinate rotation transform with 2D-IGS to represent edge information in multiple directions. Then by incorporating this multi-direction representation into ATV norm we get the MDATV regularization. To solve the optimization problem based on the MDATV regularization, a novel ART (algebraic reconstruction technique) + MDATV scheme is outlined. And NESTA (NESTerov's Algorithm) is proposed to replace GD (Gradient Descent) for minimizing the TV-based regularization. The numerical and real data experiments demonstrate that MDATV based iterative reconstruction improved the quality of restored image. NESTA is more suitable than GD for minimization of TV-based regularization. MDATV regularization can sufficiently use the prior information of image sparsity and edge information

  10. Diagnosis of small posterior fossa stroke on brain CT: effect of iterative reconstruction designed for brain CT on detection performance.

    PubMed

    Inoue, Taihei; Nakaura, Takeshi; Yoshida, Morikatsu; Yokoyama, Koichi; Hirata, Kenichiro; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Harada, Kazunori; Yamashita, Yasuyuki

    2017-09-01

    In this study, we aimed to determine whether iterative model reconstruction designed for brain CT (IMR-neuro) would improve the accuracy of posterior fossa stroke diagnosis on brain CT. We enrolled 37 patients with ischaemic stroke in the posterior fossa and 37 patients without stroke (controls). Using axial images reconstructed using filtered back-projection (FBP) and IMR-neuro, we compared the CT numbers in infarcted areas, image noise in the pons, and contrast-to-noise ratios (CNRs) of infarcted and non-infarcted areas on scans subjected to IMR-neuro and FBP. To analyse the performance of hypo-attenuation detection, we used receiver-operating characteristic (ROC) curve techniques. The image noise was significantly lower (2.2 ± 0.5 vs. 5.1 ± 0.9 Hounsfield units, p < 0.01) and the difference in CNR between the infarcted and non-infarcted areas was significantly higher with IMR-neuro than with FBP (2.2 ± 1.7 vs. 4.0 ± 3.6, p < 0.01). Furthermore, the average area under the ROC curve was significantly higher with IMR-neuro (0.90 vs. 0.86 for FBP, p = 0.04). IMR-neuro yielded better image quality and improved hypo-attenuation detection in patients with ischaemic stroke. • Iterative model reconstruction of brain CT data can facilitate the diagnosis of ischaemic stroke. • IMR improved the detectability of low-contrast lesions in the posterior fossa. • IMR-neuro yielded better image quality and improved observer performance.

  11. Alpha image reconstruction (AIR): A new iterative CT image reconstruction approach using voxel-wise alpha blending

    SciTech Connect

    Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

    2014-06-15

    factor for contrast-resolution plots. Furthermore, the authors calculate the contrast-to-noise ratio with the low contrast disks and the authors compare the agreement of the reconstructions with the ground truth by calculating the normalized cross-correlation and the root-mean-square deviation. To evaluate the clinical performance of the proposed method, the authors reconstruct patient data acquired with a Somatom Definition Flash dual source CT scanner (Siemens Healthcare, Forchheim, Germany). Results: The results of the simulation study show that among the compared algorithms AIR achieves the highest resolution and the highest agreement with the ground truth. Compared to the reference FBP reconstruction AIR is able to reduce the relative pixel noise by up to 50% and at the same time achieve a higher resolution by maintaining the edge information from the basis images. These results can be confirmed with the patient data. Conclusions: To evaluate the AIR algorithm simulated and measured patient data of a state-of-the-art clinical CT system were processed. It is shown, that generating CT images through the reconstruction of weighting coefficients has the potential to improve the resolution noise trade-off and thus to improve the dose usage in clinical CT.

  12. Full dose reduction potential of statistical iterative reconstruction for head CT protocols in a predominantly pediatric population

    PubMed Central

    Mirro, Amy E.; Brady, Samuel L.; Kaufman, Robert. A.

    2016-01-01

    Purpose To implement the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population. Methods Select head examinations (brain, orbits, sinus, maxilla and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction (ASiR) were compared for image quality with the original filtered back projection (FBP) reconstructed protocols in phantom using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio (CNR), and spatial resolution. Dose reduction estimates were based on computed tomography dose index (CTDIvol) values. Patient CTDIvol and image noise magnitude were assessed in 737 pre and post dose reduced examinations. Results Image noise texture was acceptable up to 60% ASiR for Soft reconstruction kernel (at both 100 and 120 kVp), and up to 40% ASiR for Standard reconstruction kernel. Implementation of 40% and 60% ASiR led to an average reduction in CTDIvol of 43% for brain, 41% for orbits, 30% maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years, while maintaining an average noise magnitude difference of 0.1% (range: −3% to 5%), improving CNR of low contrast soft tissue targets, and improving spatial resolution of high contrast bony anatomy, as compared to FBP. Conclusion The methodology in this study demonstrates a methodology for maximizing patient dose reduction and maintaining image quality using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examination. PMID:27056425

  13. Estimation of cartilaginous region in noncontrast CT of the chest

    NASA Astrophysics Data System (ADS)

    Zhao, Qian; Safdar, Nabile; Yu, Glenna; Myers, Emmarie; Sandler, Anthony; Linguraru, Marius George

    2014-03-01

    Pectus excavatum is a posterior depression of the sternum and adjacent costal cartilages and is the most common congenital deformity of the anterior chest wall. Its surgical repair can be performed via minimally invasive procedures that involve sternum and cartilage relocation and benefit from adequate surgical planning. In this study, we propose a method to estimate the cartilage regions in thoracic CT scans, which is the first step of statistical modeling of the osseous and cartilaginous structures for the rib cage. The ribs and sternum are first segmented by using interactive region growing and removing the vertebral column with morphological operations. The entire chest wall is also segmented to estimate the skin surface. After the segmentation, surface meshes are generated from the volumetric data and the skeleton of the ribs is extracted using surface contraction method. Then the cartilage surface is approximated via contracting the skin surface to the osseous structure. The ribs' skeleton is projected to the cartilage surface and the cartilages are estimated using cubic interpolation given the joints with the sternum. The final cartilage regions are formed by the cartilage surface inside the convex hull of the estimated cartilages. The method was validated with the CT scans of two pectus excavatum patients and three healthy subjects. The average distance between the estimated cartilage surface and the ground truth is 2.89 mm. The promising results indicate the effectiveness of cartilage surface estimation using the skin surface.

  14. Image reconstruction for view-limited x-ray CT in baggage scanning

    NASA Astrophysics Data System (ADS)

    Mandava, Sagar; Coccarelli, David; Greenberg, Joel A.; Gehm, Michael E.; Ashok, Amit; Bilgin, Ali

    2017-05-01

    X-ray CT based baggage scanners are widely used in security applications. Recently, there has been increased interest in view-limited systems which can improve the scanning throughput while maintaining the threat detection performance. However as very few view angles are acquired in these systems, the image reconstruction problem is challenging. Standard reconstruction algorithms such as the filtered backprojection create strong artifacts when working with view-limited data. In this work, we study the performance of a variety of reconstruction algorithms for both single and multi-energy view-limited systems.

  15. Direct Reconstruction of CT-Based Attenuation Correction Images for PET With Cluster-Based Penalties

    NASA Astrophysics Data System (ADS)

    Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Kinahan, Paul E.

    2017-03-01

    Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

  16. Automated selection of the optimal cardiac phase for single-beat coronary CT angiography reconstruction

    SciTech Connect

    Stassi, D.; Ma, H.; Schmidt, T. G.; Dutta, S.; Soderman, A.; Pazzani, D.; Gros, E.; Okerlund, D.

    2016-01-15

    Purpose: Reconstructing a low-motion cardiac phase is expected to improve coronary artery visualization in coronary computed tomography angiography (CCTA) exams. This study developed an automated algorithm for selecting the optimal cardiac phase for CCTA reconstruction. The algorithm uses prospectively gated, single-beat, multiphase data made possible by wide cone-beam imaging. The proposed algorithm differs from previous approaches because the optimal phase is identified based on vessel image quality (IQ) directly, compared to previous approaches that included motion estimation and interphase processing. Because there is no processing of interphase information, the algorithm can be applied to any sampling of image phases, making it suited for prospectively gated studies where only a subset of phases are available. Methods: An automated algorithm was developed to select the optimal phase based on quantitative IQ metrics. For each reconstructed slice at each reconstructed phase, an image quality metric was calculated based on measures of circularity and edge strength of through-plane vessels. The image quality metric was aggregated across slices, while a metric of vessel-location consistency was used to ignore slices that did not contain through-plane vessels. The algorithm performance was evaluated using two observer studies. Fourteen single-beat cardiac CT exams (Revolution CT, GE Healthcare, Chalfont St. Giles, UK) reconstructed at 2% intervals were evaluated for best systolic (1), diastolic (6), or systolic and diastolic phases (7) by three readers and the algorithm. Pairwise inter-reader and reader-algorithm agreement was evaluated using the mean absolute difference (MAD) and concordance correlation coefficient (CCC) between the reader and algorithm-selected phases. A reader-consensus best phase was determined and compared to the algorithm selected phase. In cases where the algorithm and consensus best phases differed by more than 2%, IQ was scored by three

  17. TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.

    PubMed

    Liu, Jiulong; Ding, Huanjun; Molloi, Sabee; Zhang, Xiaoqun; Gao, Hao

    2016-12-01

    This work develops a material reconstruction method for spectral CT, namely Total Image Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in terms of both spectral information and high signal-to-noise ratio (SNR). This is motivated by the following fact: when viewed as a spectrally-integrated measurement, the projection data can be used to reconstruct a total image without spectral information, which however has a relatively high SNR; when viewed as a spectrally-resolved measurement, the projection data can be utilized to reconstruct the material composition, which however has a relatively low SNR. The material reconstruction synergizes material decomposition and image reconstruction, i.e., the direct reconstruction of material compositions instead of a two-step procedure that first reconstructs images and then decomposes images. For material reconstruction with high SNR, we propose TICMR with nonlocal total variation (NLTV) regularization. That is, first we reconstruct a total image using spectrally-integrated measurement without spectral binning, and build the NLTV weights from this image that characterize nonlocal image features; then the NLTV weights are incorporated into a NLTV-based iterative material reconstruction scheme using spectrally-binned projection data, so that these weights serve as a high-SNR reference to regularize material reconstruction. Note that the nonlocal property of NLTV is essential for material reconstruction, since material compositions may have significant local intensity variations although their structural information is often similar. In terms of solution algorithm, TICMR is formulated as an iterative reconstruction method with the NLTV regularization, in which the nonlocal divergence is utilized based on the adjoint relationship. The alternating direction method of multipliers is developed to solve this sparsity optimization problem. The proposed TICMR method was validated using both simulated

  18. Role of CT Imaging with Volume Reconstruction in Hemi Facial Hypertrophy: A Pediatric Case Report.

    PubMed

    I, Gurubharath; Karanam, Lakshmi Sudha Prasanna; P, Ramesh

    2014-06-01

    Hemifacial hypertrophy is a rare congenital disorder more common in males.It involves the soft tissue, hard bones and teeth of the face.Its etiology is unknown and multiple theories have been postulated. We present a 6-year-old male with hemifacial hypertrophy and describes the importance of CT volume reconstruction in this condition.

  19. Statistical image reconstruction for low-dose CT using nonlocal means-based regularization.

    PubMed

    Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Lu, Hongbing; Liang, Zhengrong

    2014-09-01

    Low-dose computed tomography (CT) imaging without sacrifice of clinical tasks is desirable due to the growing concerns about excessive radiation exposure to the patients. One common strategy to achieve low-dose CT imaging is to lower the milliampere-second (mAs) setting in data scanning protocol. However, the reconstructed CT images by the conventional filtered back-projection (FBP) method from the low-mAs acquisitions may be severely degraded due to the excessive noise. Statistical image reconstruction (SIR) methods have shown potentials to significantly improve the reconstructed image quality from the low-mAs acquisitions, wherein the regularization plays a critical role and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) in image processing applications, in this work, we propose to explore the NLM-based regularization for SIR to reconstruct low-dose CT images from low-mAs acquisitions. Experimental results with both digital and physical phantoms consistently demonstrated that SIR with the NLM-based regularization can achieve more gains than SIR with the well-known Gaussian MRF regularization or the generalized Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation.

  20. Statistical image reconstruction for low-dose CT using nonlocal means-based regularization

    PubMed Central

    Zhang, Hao; Ma, Jianhua; Wang, Jing; Liu, Yan; Lu, Hongbing

    2014-01-01

    Low-dose computed tomography (CT) imaging without sacrifice of clinical tasks is desirable due to the growing concerns about excessive radiation exposure to the patients. One common strategy to achieve low-dose CT imaging is to lower the milliampere-second (mAs) setting in data scanning protocol. However, the reconstructed CT images by the conventional filtered back-projection (FBP) method from the low-mAs acquisitions may be severely degraded due to the excessive noise. Statistical image reconstruction (SIR) methods have shown potentials to significantly improve the reconstructed image quality from the low-mAs acquisitions, wherein the regularization plays a critical role and an established family of regularizations is based on the Markov random field (MRF) model. Inspired by the success of nonlocal means (NLM) in image processing applications, in this work, we propose to explore the NLM-based regularization for SIR to reconstruct low-dose CT images from low-mAs acquisitions. Experimental results with both digital and physical phantoms consistently demonstrated that SIR with the NLM-based regularization can achieve more gains than SIR with the well-known Gaussian MRF regularization or the generalized Gaussian MRF regularization and the conventional FBP method, in terms of image noise reduction and resolution preservation. PMID:24881498

  1. 3D iterative full and half scan reconstruction in CT architectures with distributed sources

    NASA Astrophysics Data System (ADS)

    Iatrou, M.; De Man, B.; Beque, D.; Yin, Z.; Khare, K.; Benson, T. M.

    2008-03-01

    In 3 rd generation CT systems projection data, generated by X-rays emitted from a single source and passing through the imaged object, are acquired by a single detector covering the entire field of view (FOV). Novel CT system architectures employing distributed sources [1,2] could extend the axial coverage, while removing cone-beam artifacts and improving spatial resolution and dose. The sources can be distributed in plane and/or in the longitudinal direction. We investigate statistical iterative reconstruction of multi-axial data, acquired with simulated CT systems with multiple sources distributed along the in-plane and longitudinal directions. The current study explores the feasibility of 3D iterative Full and Half Scan reconstruction methods for CT systems with two different architectures. In the first architecture the sources are distributed in the longitudinal direction, and in the second architecture the sources are distributed both longitudinally and trans-axially. We used Penalized Weighted Least Squares Transmission Reconstruction (PWLSTR) and incorporated a projector-backprojector model matching the simulated architectures. The proposed approaches minimize artifacts related to the proposed geometries. The reconstructed images show that the investigated architectures can achieve good image quality for very large coverage without severe cone-beam artifacts.

  2. Minimizing image noise in on-board CT reconstruction using both kilovoltage and megavoltage beam projections.

    PubMed

    Zhang, Junan; Yin, Fang-Fang

    2007-09-01

    We studied a recently proposed aggregated CT reconstruction technique which combines the complementary advantages of kilovoltage (kV) and megavoltage (MV) x-ray imaging. Various phantoms were imaged to study the effects of beam orientations and geometry of the imaging object on image quality of reconstructed CT. It was shown that the quality of aggregated CT was correlated with both kV and MV beam orientations and the degree of this correlation depended upon the geometry of the imaging object. The results indicated that the optimal orientations were those when kV beams pass through the thinner portion and MV beams pass through the thicker portion of the imaging object. A special preprocessing procedure was also developed to perform contrast conversions between kV and MV information prior to image reconstruction. The performance of two reconstruction methods, one filtered backprojection method and one iterative method, were compared. The effects of projection number, beam truncation, and contrast conversion on the CT image quality were investigated.

  3. Relaxed Linearized Algorithms for Faster X-Ray CT Image Reconstruction.

    PubMed

    Nien, Hung; Fessler, Jeffrey

    2015-12-17

    Statistical image reconstruction (SIR) methods are studied extensively for X-ray computed tomography (CT) due to the potential of acquiring CT scans with reduced X-ray dose while maintaining image quality. However, the longer reconstruction time of SIR methods hinders their use in X-ray CT in practice. To accelerate statistical methods, many optimization techniques have been investigated. Over-relaxation is a common technique to speed up convergence of iterative algorithms. For instance, using a relaxation parameter that is close to two in alternating direction method of multipliers (ADMM) has been shown to speed up convergence significantly. This paper proposes a relaxed linearized augmented Lagrangian (AL) method that shows theoretical faster convergence rate with over-relaxation and applies the proposed relaxed linearized AL method to X-ray CT image reconstruction problems. Experimental results with both simulated and real CT scan data show that the proposed relaxed algorithm (with ordered-subsets [OS] acceleration) is about twice as fast as the existing unrelaxed fast algorithms, with negligible computation and memory overhead.

  4. Relaxed Linearized Algorithms for Faster X-Ray CT Image Reconstruction.

    PubMed

    Nien, Hung; Fessler, Jeffrey A

    2016-04-01

    Statistical image reconstruction (SIR) methods are studied extensively for X-ray computed tomography (CT) due to the potential of acquiring CT scans with reduced X-ray dose while maintaining image quality. However, the longer reconstruction time of SIR methods hinders their use in X-ray CT in practice. To accelerate statistical methods, many optimization techniques have been investigated. Over-relaxation is a common technique to speed up convergence of iterative algorithms. For instance, using a relaxation parameter that is close to two in alternating direction method of multipliers (ADMM) has been shown to speed up convergence significantly. This paper proposes a relaxed linearized augmented Lagrangian (AL) method that shows theoretical faster convergence rate with over-relaxation and applies the proposed relaxed linearized AL method to X-ray CT image reconstruction problems. Experimental results with both simulated and real CT scan data show that the proposed relaxed algorithm (with ordered-subsets [OS] acceleration) is about twice as fast as the existing unrelaxed fast algorithms, with negligible computation and memory overhead.

  5. Extracting information from previous full-dose CT scan for knowledge-based Bayesian reconstruction of current low-dose CT images

    PubMed Central

    Zhang, Hao; Han, Hao; Liang, Zhengrong; Hu, Yifan; Liu, Yan; Moore, William; Ma, Jianhua; Lu, Hongbing

    2015-01-01

    Markov random field (MRF) model has been widely employed in edge-preserving regional noise smoothing penalty to reconstruct piece-wise smooth images in the presence of noise, such as in low-dose computed tomography (LdCT). While it preserves edge sharpness, its regional smoothing may sacrifice tissue image textures, which have been recognized as useful imaging biomarkers, and thus it may compromise clinical tasks such as differentiating malignant vs. benign lesions, e.g., lung nodules or colon polyps. This study aims to shift the edge-preserving regional noise smoothing paradigm to texture-preserving framework for LdCT image reconstruction while retaining the advantage of MRF’s neighborhood system on edge preservation. Specifically, we adapted the MRF model to incorporate the image textures of muscle, fat, bone, lung, etc. from previous full-dose CT (FdCT) scan as a priori knowledge for texture-preserving Bayesian reconstruction of current LdCT images. To show the feasibility of the proposed reconstruction framework, experiments using clinical patient scans were conducted. The experimental outcomes showed a dramatic gain by the a priori knowledge for LdCT image reconstruction using the commonly-used Haralick texture measures. Thus, it is conjectured that the texture-preserving LdCT reconstruction has advantages over the edge-preserving regional smoothing paradigm for texture-specific clinical applications. PMID:26561284

  6. Estimation of adipose compartment volumes in CT images of a mastectomy specimen

    NASA Astrophysics Data System (ADS)

    Imran, Abdullah-Al-Zubaer; Pokrajac, David D.; Maidment, Andrew D. A.; Bakic, Predrag R.

    2016-03-01

    Anthropomorphic software breast phantoms have been utilized for preclinical quantitative validation of breast imaging systems. Efficacy of the simulation-based validation depends on the realism of phantom images. Anatomical measurements of the breast tissue, such as the size and distribution of adipose compartments or the thickness of Cooper's ligaments, are essential for the realistic simulation of breast anatomy. Such measurements are, however, not readily available in the literature. In this study, we assessed the statistics of adipose compartments as visualized in CT images of a total mastectomy specimen. The specimen was preserved in formalin, and imaged using a standard body CT protocol and high X-ray dose. A human operator manually segmented adipose compartments in reconstructed CT images using ITK-SNAP software, and calculated the volume of each compartment. In addition, the time needed for the manual segmentation and the operator's confidence were recorded. The average volume, standard deviation, and the probability distribution of compartment volumes were estimated from 205 segmented adipose compartments. We also estimated the potential correlation between the segmentation time, operator's confidence, and compartment volume. The statistical tests indicated that the estimated compartment volumes do not follow the normal distribution. The compartment volumes are found to be correlated with the segmentation time; no significant correlation between the volume and the operator confidence. The performed study is limited by the mastectomy specimen position. The analysis of compartment volumes will better inform development of more realistic breast anatomy simulation.

  7. SYRMEP Tomo Project: a graphical user interface for customizing CT reconstruction workflows.

    PubMed

    Brun, Francesco; Massimi, Lorenzo; Fratini, Michela; Dreossi, Diego; Billé, Fulvio; Accardo, Agostino; Pugliese, Roberto; Cedola, Alessia

    2017-01-01

    When considering the acquisition of experimental synchrotron radiation (SR) X-ray CT data, the reconstruction workflow cannot be limited to the essential computational steps of flat fielding and filtered back projection (FBP). More refined image processing is often required, usually to compensate artifacts and enhance the quality of the reconstructed images. In principle, it would be desirable to optimize the reconstruction workflow at the facility during the experiment (beamtime). However, several practical factors affect the image reconstruction part of the experiment and users are likely to conclude the beamtime with sub-optimal reconstructed images. Through an example of application, this article presents SYRMEP Tomo Project (STP), an open-source software tool conceived to let users design custom CT reconstruction workflows. STP has been designed for post-beamtime (off-line use) and for a new reconstruction of past archived data at user's home institution where simple computing resources are available. Releases of the software can be downloaded at the Elettra Scientific Computing group GitHub repository https://github.com/ElettraSciComp/STP-Gui.

  8. A method for investigating system matrix properties in optimization-based CT reconstruction

    NASA Astrophysics Data System (ADS)

    Rose, Sean D.; Sidky, Emil Y.; Pan, Xiaochuan

    2016-04-01

    Optimization-based iterative reconstruction methods have shown much promise for a variety of applications in X-ray computed tomography (CT). In these reconstruction methods, the X-ray measurement is modeled as a linear mapping from a finite-dimensional image space to a finite dimensional data-space. This mapping is dependent on a number of factors including the basis functions used for image representation1 and the method by which the matrix representing this mapping is generated.2 Understanding the properties of this linear mapping and how it depends on our choice of parameters is fundamental to optimization-based reconstruction. In this work, we confine our attention to a pixel basis and propose a method to investigate the effect of pixel size in optimization-based reconstruction. The proposed method provides insight into the tradeoff between higher resolution image representation and matrix conditioning. We demonstrate this method for a particular breast CT system geometry. We find that the images obtained from accurate solution of a least squares reconstruction optimization problem have high sensitivity to pixel size within certain regimes. We propose two methods by which this sensitivity can be reduced and demonstrate their efficacy. Our results indicate that the choice of pixel size in optimization-based reconstruction can have great impact on the quality of the reconstructed image, and that understanding the properties of the linear mapping modeling the X-ray measurement can help guide us with this choice.

  9. Evaluation of dose reduction and image quality in CT colonography: comparison of low-dose CT with iterative reconstruction and routine-dose CT with filtered back projection.

    PubMed

    Nagata, Koichi; Fujiwara, Masanori; Kanazawa, Hidenori; Mogi, Tomohiro; Iida, Nao; Mitsushima, Toru; Lefor, Alan T; Sugimoto, Hideharu

    2015-01-01

    To prospectively evaluate the radiation dose and image quality comparing low-dose CT colonography (CTC) reconstructed using different levels of iterative reconstruction techniques with routine-dose CTC reconstructed with filtered back projection. Following institutional ethics clearance and informed consent procedures, 210 patients underwent screening CTC using automatic tube current modulation for dual positions. Examinations were performed in the supine position with a routine-dose protocol and in the prone position, randomly applying four different low-dose protocols. Supine images were reconstructed with filtered back projection and prone images with iterative reconstruction. Two blinded observers assessed the image quality of endoluminal images. Image noise was quantitatively assessed by region-of-interest measurements. The mean effective dose in the supine series was 1.88 mSv using routine-dose CTC, compared to 0.92, 0.69, 0.57, and 0.46 mSv at four different low doses in the prone series (p < 0.01). Overall image quality and noise of low-dose CTC with iterative reconstruction were significantly improved compared to routine-dose CTC using filtered back projection. The lowest dose group had image quality comparable to routine-dose images. Low-dose CTC with iterative reconstruction reduces the radiation dose by 48.5 to 75.1% without image quality degradation compared to routine-dose CTC with filtered back projection. • Low-dose CTC reduces radiation dose ≥ 48.5% compared to routine-dose CTC. • Iterative reconstruction improves overall CTC image quality compared with FBP. • Iterative reconstruction reduces overall CTC image noise compared with FBP. • Automated exposure control with iterative reconstruction is useful for low-dose CTC.

  10. Noise properties of CT images reconstructed by use of constrained total-variation, data-discrepancy minimization

    PubMed Central

    Rose, Sean; Andersen, Martin S.; Sidky, Emil Y.; Pan, Xiaochuan

    2015-01-01

    Purpose: The authors develop and investigate iterative image reconstruction algorithms based on data-discrepancy minimization with a total-variation (TV) constraint. The various algorithms are derived with different data-discrepancy measures reflecting the maximum likelihood (ML) principle. Simulations demonstrate the iterative algorithms and the resulting image statistical properties for low-dose CT data acquired with sparse projection view angle sampling. Of particular interest is to quantify improvement of image statistical properties by use of the ML data fidelity term. Methods: An incremental algorithm framework is developed for this purpose. The instances of the incremental algorithms are derived for solving optimization problems including a data fidelity objective function combined with a constraint on the image TV. For the data fidelity term the authors, compare application of the maximum likelihood principle, in the form of weighted least-squares (WLSQ) and Poisson-likelihood (PL), with the use of unweighted least-squares (LSQ). Results: The incremental algorithms are applied to projection data generated by a simulation modeling the breast computed tomography (bCT) imaging application. The only source of data inconsistency in the bCT projections is due to noise, and a Poisson distribution is assumed for the transmitted x-ray photon intensity. In the simulations involving the incremental algorithms an ensemble of images, reconstructed from 1000 noise realizations of the x-ray transmission data, is used to estimate the image statistical properties. The WLSQ and PL incremental algorithms are seen to reduce image variance as compared to that of LSQ without sacrificing image bias. The difference is also seen at few iterations—short of numerical convergence of the corresponding optimization problems. Conclusions: The proposed incremental algorithms prove effective and efficient for iterative image reconstruction in low-dose CT applications particularly with

  11. Model-based x-ray energy spectrum estimation algorithm from CT scanning data with spectrum filter

    NASA Astrophysics Data System (ADS)

    Li, Lei; Wang, Lin-Yuan; Yan, Bin

    2016-10-01

    With the development of technology, the traditional X-ray CT can't meet the modern medical and industry needs for component distinguish and identification. This is due to the inconsistency of X-ray imaging system and reconstruction algorithm. In the current CT systems, X-ray spectrum produced by X-ray source is continuous in energy range determined by tube voltage and energy filter, and the attenuation coefficient of object is varied with the X-ray energy. So the distribution of X-ray energy spectrum plays an important role for beam-hardening correction, dual energy CT image reconstruction or dose calculation. However, due to high ill-condition and ill-posed feature of system equations of transmission measurement data, statistical fluctuations of X ray quantum and noise pollution, it is very hard to get stable and accurate spectrum estimation using existing methods. In this paper, a model-based X-ray energy spectrum estimation method from CT scanning data with energy spectrum filter is proposed. First, transmission measurement data were accurately acquired by CT scan and measurement using phantoms with different energy spectrum filter. Second, a physical meaningful X-ray tube spectrum model was established with weighted gaussian functions and priori information such as continuity of bremsstrahlung and specificity of characteristic emission and estimation information of average attenuation coefficient. The parameter in model was optimized to get the best estimation result for filtered spectrum. Finally, the original energy spectrum was reconstructed from filtered spectrum estimation with filter priori information. Experimental results demonstrate that the stability and accuracy of X ray energy spectrum estimation using the proposed method are improved significantly.

  12. Performance benchmarking of liver CT image segmentation and volume estimation

    NASA Astrophysics Data System (ADS)

    Xiong, Wei; Zhou, Jiayin; Tian, Qi; Liu, Jimmy J.; Qi, Yingyi; Leow, Wee Kheng; Han, Thazin; Wang, Shih-chang

    2008-03-01

    In recent years more and more computer aided diagnosis (CAD) systems are being used routinely in hospitals. Image-based knowledge discovery plays important roles in many CAD applications, which have great potential to be integrated into the next-generation picture archiving and communication systems (PACS). Robust medical image segmentation tools are essentials for such discovery in many CAD applications. In this paper we present a platform with necessary tools for performance benchmarking for algorithms of liver segmentation and volume estimation used for liver transplantation planning. It includes an abdominal computer tomography (CT) image database (DB), annotation tools, a ground truth DB, and performance measure protocols. The proposed architecture is generic and can be used for other organs and imaging modalities. In the current study, approximately 70 sets of abdominal CT images with normal livers have been collected and a user-friendly annotation tool is developed to generate ground truth data for a variety of organs, including 2D contours of liver, two kidneys, spleen, aorta and spinal canal. Abdominal organ segmentation algorithms using 2D atlases and 3D probabilistic atlases can be evaluated on the platform. Preliminary benchmark results from the liver segmentation algorithms which make use of statistical knowledge extracted from the abdominal CT image DB are also reported. We target to increase the CT scans to about 300 sets in the near future and plan to make the DBs built available to medical imaging research community for performance benchmarking of liver segmentation algorithms.

  13. Reconstruction Algorithm with Improved Efficiency and Flexibility in Multi-Slice Spiral CT.

    PubMed

    Sun, Wenwu; Chen, Siping; Zhuang, Tiange

    2005-01-01

    There is a requirement for the development of CT to scan rapidly large longitudinal volume with high z-axis resolution. The combination of spiral scanning with multi-slice CT is a promising approach. The algorithm of image reconstruction for multi-slice spiral CT becomes, therefore, the main challenge. All algorithms known to the authors either need to derive the complementary data or work only for certain range of pitch values. This paper presents a novel reconstruction algorithm that can omit the derivations of the complementary data and work for arbitrary pitch values. The filter interpolation based on the proposed method is also easy to be implemented. The method is, thus, versatile. The results of computer simulations show that we can choose a combination of scan and filter parameters to meet the purpose of the examination.

  14. Spatial-temporal total variation regularization (STTVR) for 4D-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Wu, Haibo; Maier, Andreas; Fahrig, Rebecca; Hornegger, Joachim

    2012-03-01

    Four dimensional computed tomography (4D-CT) is very important for treatment planning in thorax or abdomen area, e.g. for guiding radiation therapy planning. The respiratory motion makes the reconstruction problem illposed. Recently, compressed sensing theory was introduced. It uses sparsity as a prior to solve the problem and improves image quality considerably. However, the images at each phase are reconstructed individually. The correlations between neighboring phases are not considered in the reconstruction process. In this paper, we propose the spatial-temporal total variation regularization (STTVR) method which not only employs the sparsity in the spatial domain but also in the temporal domain. The algorithm is validated with XCAT thorax phantom. The Euclidean norm of the reconstructed image and ground truth is calculated for evaluation. The results indicate that our method improves the reconstruction quality by more than 50% compared to standard ART.

  15. CT multiplanar reconstructions (MPR) for shrapnel injury trajectory.

    PubMed

    Brook, Olga R; Eran, Ayelet; Engel, Ahuva

    2012-01-01

    We report our experience in implementing CT multiplanar reformats (MPRs) to demonstrate the trajectory of penetrating trauma. It is an easily learned tool that can be conveniently and speedily applied in the fragments injury. We describe the detailed technique of performing MPRs, depicted by various examples. Furthermore, benefits and limitations of the technique (such as numerous fragments, change in position and respiratory phase, and embolization of fragments) are presented. We conclude that MPRs in the fragments trajectory can be helpful for accurate and fast diagnosis of injury. In addition, MPRs serve as a vivid presentation of injured and spared organs.

  16. SU-E-I-86: Ultra-Low Dose Computed Tomography Attenuation Correction for Pediatric PET CT Using Adaptive Statistical Iterative Reconstruction (ASiR™)

    SciTech Connect

    Brady, S; Shulkin, B

    2015-06-15

    Purpose: To develop ultra-low dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultra-low doses (10–35 mAs). CT quantitation: noise, low-contrast resolution, and CT numbers for eleven tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% CTDIvol (0.39/3.64; mGy) radiation dose from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUVbw) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation organ dose, as derived from patient exam size specific dose estimate (SSDE), was converted to effective dose using the standard ICRP report 103 method. Effective dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative patient population dose reduction and noise control. Results: CT numbers were constant to within 10% from the non-dose reduced CTAC image down to 90% dose reduction. No change in SUVbw, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols reconstructed with ASiR and down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62%–86% (3.2/8.3−0.9/6.2; mSv). Noise magnitude in dose-reduced patient images increased but was not statistically different from pre dose-reduced patient images. Conclusion: Using ASiR allowed for aggressive reduction in CTAC dose with no change in PET reconstructed images while maintaining sufficient image quality for co

  17. An adaptive reconstruction algorithm for spectral CT regularized by a reference image

    NASA Astrophysics Data System (ADS)

    Wang, Miaoshi; Zhang, Yanbo; Liu, Rui; Guo, Shuxu; Yu, Hengyong

    2016-12-01

    The photon counting detector based spectral CT system is attracting increasing attention in the CT field. However, the spectral CT is still premature in terms of both hardware and software. To reconstruct high quality spectral images from low-dose projections, an adaptive image reconstruction algorithm is proposed that assumes a known reference image (RI). The idea is motivated by the fact that the reconstructed images from different spectral channels are highly correlated. If a high quality image of the same object is known, it can be used to improve the low-dose reconstruction of each individual channel. This is implemented by maximizing the patch-wise correlation between the object image and the RI. Extensive numerical simulations and preclinical mouse study demonstrate the feasibility and merits of the proposed algorithm. It also performs well for truncated local projections, and the surrounding area of the region- of-interest (ROI) can be more accurately reconstructed. Furthermore, a method is introduced to adaptively choose the step length, making the algorithm more feasible and easier for applications.

  18. Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners.

    PubMed

    Abella, M; Vaquero, J J; Sisniega, A; Pascau, J; Udías, A; García, V; Vidal, I; Desco, M

    2012-08-01

    Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flat-panel detector orbiting in a circular trajectory. Image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp et al. (FDK). Besides the implementation of the reconstruction algorithm itself, in order to design a real system it is necessary to take into account numerous issues so as to obtain the best quality images from the acquired data. This work presents a comprehensive, novel software architecture for small-animal CT scanners based on cone-beam geometry with circular scanning trajectory. The proposed architecture covers all the steps from the system calibration to the volume reconstruction and conversion into Hounsfield units. It includes an efficient implementation of an FDK-based reconstruction algorithm that takes advantage of system symmetries and allows for parallel reconstruction using a multiprocessor computer. Strategies for calibration and artifact correction are discussed to justify the strategies adopted. New procedures for multi-bed misalignment, beam-hardening, and Housfield units calibration are proposed. Experiments with phantoms and real data showed the suitability of the proposed software architecture for an X-ray small animal CT based on cone-beam geometry. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  19. Deep learning methods to guide CT image reconstruction and reduce metal artifacts

    NASA Astrophysics Data System (ADS)

    Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

    2017-03-01

    The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

  20. Low-Dose X-ray CT Reconstruction via Dictionary Learning

    PubMed Central

    Xu, Qiong; Zhang, Lei; Hsieh, Jiang; Wang, Ge

    2013-01-01

    Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures. PMID:22542666

  1. Low-dose X-ray CT reconstruction via dictionary learning.

    PubMed

    Xu, Qiong; Yu, Hengyong; Mou, Xuanqin; Zhang, Lei; Hsieh, Jiang; Wang, Ge

    2012-09-01

    Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.

  2. Quantifying Admissible Undersampling for Sparsity-Exploiting Iterative Image Reconstruction in X-Ray CT

    PubMed Central

    Sidky, Emil Y.; Pan, Xiaochuan

    2014-01-01

    Iterative image reconstruction with sparsity-exploiting methods, such as total variation (TV) minimization, investigated in compressive sensing claim potentially large reductions in sampling requirements. Quantifying this claim for computed tomography (CT) is nontrivial, because both full sampling in the discrete-to-discrete imaging model and the reduction in sampling admitted by sparsity-exploiting methods are ill-defined. The present article proposes definitions of full sampling by introducing four sufficient-sampling conditions (SSCs). The SSCs are based on the condition number of the system matrix of a linear imaging model and address invertibility and stability. In the example application of breast CT, the SSCs are used as reference points of full sampling for quantifying the undersampling admitted by reconstruction through TV-minimization. In numerical simulations, factors affecting admissible undersampling are studied. Differences between few-view and few-detector bin reconstruction as well as a relation between object sparsity and admitted undersampling are quantified. PMID:23204282

  3. Smoothed l0 Norm Regularization for Sparse-View X-Ray CT Reconstruction

    PubMed Central

    Li, Ming; Peng, Chengtao; Guan, Yihui; Xu, Pin

    2016-01-01

    Low-dose computed tomography (CT) reconstruction is a challenging problem in medical imaging. To complement the standard filtered back-projection (FBP) reconstruction, sparse regularization reconstruction gains more and more research attention, as it promises to reduce radiation dose, suppress artifacts, and improve noise properties. In this work, we present an iterative reconstruction approach using improved smoothed l0 (SL0) norm regularization which is used to approximate l0 norm by a family of continuous functions to fully exploit the sparseness of the image gradient. Due to the excellent sparse representation of the reconstruction signal, the desired tissue details are preserved in the resulting images. To evaluate the performance of the proposed SL0 regularization method, we reconstruct the simulated dataset acquired from the Shepp-Logan phantom and clinical head slice image. Additional experimental verification is also performed with two real datasets from scanned animal experiment. Compared to the referenced FBP reconstruction and the total variation (TV) regularization reconstruction, the results clearly reveal that the presented method has characteristic strengths. In particular, it improves reconstruction quality via reducing noise while preserving anatomical features. PMID:27725935

  4. CT scan range estimation using multiple body parts detection: let PACS learn the CT image content.

    PubMed

    Wang, Chunliang; Lundström, Claes

    2016-02-01

    The aim of this study was to develop an efficient CT scan range estimation method that is based on the analysis of image data itself instead of metadata analysis. This makes it possible to quantitatively compare the scan range of two studies. In our study, 3D stacks are first projected to 2D coronal images via a ray casting-like process. Trained 2D body part classifiers are then used to recognize different body parts in the projected image. The detected candidate regions go into a structure grouping process to eliminate false-positive detections. Finally, the scale and position of the patient relative to the projected figure are estimated based on the detected body parts via a structural voting. The start and end lines of the CT scan are projected to a standard human figure. The position readout is normalized so that the bottom of the feet represents 0.0, and the top of the head is 1.0. Classifiers for 18 body parts were trained using 184 CT scans. The final application was tested on 136 randomly selected heterogeneous CT scans. Ground truth was generated by asking two human observers to mark the start and end positions of each scan on the standard human figure. When compared with the human observers, the mean absolute error of the proposed method is 1.2% (max: 3.5%) and 1.6% (max: 5.4%) for the start and end positions, respectively. We proposed a scan range estimation method using multiple body parts detection and relative structure position analysis. In our preliminary tests, the proposed method delivered promising results.

  5. Rank-sparsity constrained, spectro-temporal reconstruction for retrospectively gated, dynamic CT

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Lee, C. L.; Kirsch, D. G.; Badea, C. T.

    2015-03-01

    Relative to prospective projection gating, retrospective projection gating for dynamic CT applications allows fast imaging times, minimizing the potential for physiological and anatomic variability. Preclinically, fast imaging is attractive due to the rapid clearance of low molecular weight contrast agents and the rapid heart rate of rodents. Clinically, retrospective gating is relevant for intraoperative C-arm CT. More generally, retrospective sampling provides an opportunity for significant reduction in x-ray dose within the framework of compressive sensing theory and sparsity-constrained iterative reconstruction. Even so, CT reconstruction from projections with random temporal sampling is a very poorly conditioned inverse problem, requiring high fidelity regularization to minimize variability in the reconstructed results. Here, we introduce a highly novel data acquisition and regularization strategy for spectro-temporal (5D) CT reconstruction from retrospectively gated projections. We show that by taking advantage of the rank-sparse structure and separability of the temporal and spectral reconstruction sub-problems, being able to solve each sub-problem independently effectively guarantees that we can solve both problems together. In this paper, we show 4D simulation results (2D + 2 energies + time) using the proposed technique and compare them with two competing techniques— spatio-temporal total variation minimization and prior image constrained compressed sensing. We also show in vivo, 5D (3D + 2 energies + time) myocardial injury data acquired in a mouse, reconstructing 20 data sets (10 phases, 2 energies) and performing material decomposition from data acquired over a single rotation (360°, dose: ~60 mGy).

  6. Ultra-Low-Dose Fetal CT With Model-Based Iterative Reconstruction: A Prospective Pilot Study.

    PubMed

    Imai, Rumi; Miyazaki, Osamu; Horiuchi, Tetsuya; Asano, Keisuke; Nishimura, Gen; Sago, Haruhiko; Nosaka, Shunsuke

    2017-06-01

    Prenatal diagnosis of skeletal dysplasia by means of 3D skeletal CT examination is highly accurate. However, it carries a risk of fetal exposure to radiation. Model-based iterative reconstruction (MBIR) technology can reduce radiation exposure; however, to our knowledge, the lower limit of an optimal dose is currently unknown. The objectives of this study are to establish ultra-low-dose fetal CT as a method for prenatal diagnosis of skeletal dysplasia and to evaluate the appropriate radiation dose for ultra-low-dose fetal CT. Relationships between tube current and image noise in adaptive statistical iterative reconstruction and MBIR were examined using a 32-cm CT dose index (CTDI) phantom. On the basis of the results of this examination and the recommended methods for the MBIR option and the known relationship between noise and tube current for filtered back projection, as represented by the expression SD = (milliamperes)(-0.5), the lower limit of the optimal dose in ultra-low-dose fetal CT with MBIR was set. The diagnostic power of the CT images obtained using the aforementioned scanning conditions was evaluated, and the radiation exposure associated with ultra-low-dose fetal CT was compared with that noted in previous reports. Noise increased in nearly inverse proportion to the square root of the dose in adaptive statistical iterative reconstruction and in inverse proportion to the fourth root of the dose in MBIR. Ultra-low-dose fetal CT was found to have a volume CTDI of 0.5 mGy. Prenatal diagnosis was accurately performed on the basis of ultra-low-dose fetal CT images that were obtained using this protocol. The level of fetal exposure to radiation was 0.7 mSv. The use of ultra-low-dose fetal CT with MBIR led to a substantial reduction in radiation exposure, compared with the CT imaging method currently used at our institution, but it still enabled diagnosis of skeletal dysplasia without reducing diagnostic power.

  7. Reconstruction of 4D-CT from a Single Free-Breathing 3D-CT by Spatial-Temporal Image Registration

    PubMed Central

    Wu, Guorong; Wang, Qian; Lian, Jun; Shen, Dinggang

    2011-01-01

    In the radiation therapy of lung cancer, a free-breathing 3D-CT image is usually acquired in the treatment day for image-guided patient setup, by registering with the free-breathing 3D-CT image acquired in the planning day. In this way, the optimal dose plan computed in the planning day can be transferred onto the treatment day for cancer radiotherapy. However, patient setup based on the simple registration of the free-breathing 3D-CT images of the planning and the treatment days may mislead the radiotherapy, since the free-breathing 3D-CT is actually the mixed-phase image, with different slices often acquired from different respiratory phases. Moreover, a 4D-CT that is generally acquired in the planning day for improvement of dose planning is often ignored for guiding patient setup in the treatment day. To overcome these limitations, we present a novel two-step method to reconstruct the 4D-CT from a single free-breathing 3D-CT of the treatment day, by utilizing the 4D-CT model built in the planning day. Specifically, in the first step, we proposed a new spatial-temporal registration algorithm to align all phase images of the 4D-CT acquired in the planning day, for building a 4D-CT model with temporal correspondences established among all respiratory phases. In the second step, we first determine the optimal phase for each slice of the free-breathing (mixed-phase) 3D-CT of the treatment day by comparing with the 4D-CT of the planning day and thus obtain a sequence of partial 3D-CT images for the treatment day, each with only the incomplete image information in certain slices; and then we reconstruct a complete 4D-CT for the treatment day by warping the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built in the planning day. We have comprehensively evaluated our 4D-CT model building algorithm on a public lung image database, achieving the best registration

  8. Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR)

    SciTech Connect

    Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

    2013-11-15

    Purpose: Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables.Methods: Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision.Results: Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A.Conclusions: The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of

  9. Development of a method to estimate organ doses for pediatric CT examinations

    SciTech Connect

    Papadakis, Antonios E. Perisinakis, Kostas; Damilakis, John

    2016-05-15

    Purpose: To develop a method for estimating doses to primarily exposed organs in pediatric CT by taking into account patient size and automatic tube current modulation (ATCM). Methods: A Monte Carlo CT dosimetry software package, which creates patient-specific voxelized phantoms, accurately simulates CT exposures, and generates dose images depicting the energy imparted on the exposed volume, was used. Routine head, thorax, and abdomen/pelvis CT examinations in 92 pediatric patients, ranging from 1-month to 14-yr-old (49 boys and 43 girls), were simulated on a 64-slice CT scanner. Two sets of simulations were performed in each patient using (i) a fixed tube current (FTC) value over the entire examination length and (ii) the ATCM profile extracted from the DICOM header of the reconstructed images. Normalized to CTDI{sub vol} organ dose was derived for all primary irradiated radiosensitive organs. Normalized dose data were correlated to patient’s water equivalent diameter using log-transformed linear regression analysis. Results: The maximum percent difference in normalized organ dose between FTC and ATCM acquisitions was 10% for eyes in head, 26% for thymus in thorax, and 76% for kidneys in abdomen/pelvis. In most of the organs, the correlation between dose and water equivalent diameter was significantly improved in ATCM compared to FTC acquisitions (P < 0.001). Conclusions: The proposed method employs size specific CTDI{sub vol}-normalized organ dose coefficients for ATCM-activated and FTC acquisitions in pediatric CT. These coefficients are substantially different between ATCM and FTC modes of operation and enable a more accurate assessment of patient-specific organ dose in the clinical setting.

  10. Development of a method to estimate organ doses for pediatric CT examinations.

    PubMed

    Papadakis, Antonios E; Perisinakis, Kostas; Damilakis, John

    2016-05-01

    To develop a method for estimating doses to primarily exposed organs in pediatric CT by taking into account patient size and automatic tube current modulation (ATCM). A Monte Carlo CT dosimetry software package, which creates patient-specific voxelized phantoms, accurately simulates CT exposures, and generates dose images depicting the energy imparted on the exposed volume, was used. Routine head, thorax, and abdomen/pelvis CT examinations in 92 pediatric patients, ranging from 1-month to 14-yr-old (49 boys and 43 girls), were simulated on a 64-slice CT scanner. Two sets of simulations were performed in each patient using (i) a fixed tube current (FTC) value over the entire examination length and (ii) the ATCM profile extracted from the DICOM header of the reconstructed images. Normalized to CTDIvol organ dose was derived for all primary irradiated radiosensitive organs. Normalized dose data were correlated to patient's water equivalent diameter using log-transformed linear regression analysis. The maximum percent difference in normalized organ dose between FTC and ATCM acquisitions was 10% for eyes in head, 26% for thymus in thorax, and 76% for kidneys in abdomen/pelvis. In most of the organs, the correlation between dose and water equivalent diameter was significantly improved in ATCM compared to FTC acquisitions (P < 0.001). The proposed method employs size specific CTDIvol-normalized organ dose coefficients for ATCM-activated and FTC acquisitions in pediatric CT. These coefficients are substantially different between ATCM and FTC modes of operation and enable a more accurate assessment of patient-specific organ dose in the clinical setting.

  11. Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

    SciTech Connect

    Yin, Zhye De Man, Bruno; Yao, Yangyang; Wu, Mingye; Montillo, Albert; Edic, Peter M.; Kalra, Mannudeep

    2015-05-15

    Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.

  12. Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning.

    PubMed

    Yin, Zhye; Yao, Yangyang; Montillo, Albert; Wu, Mingye; Edic, Peter M; Kalra, Mannudeep; De Man, Bruno

    2015-05-01

    Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors' pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.

  13. An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

    SciTech Connect

    Lin, Yuan Samei, Ehsan

    2014-02-15

    Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

  14. An efficient polyenergetic SART (pSART) reconstruction algorithm for quantitative myocardial CT perfusion

    SciTech Connect

    Lin, Yuan Samei, Ehsan

    2014-02-15

    Purpose: In quantitative myocardial CT perfusion imaging, beam hardening effect due to dense bone and high concentration iodinated contrast agent can result in visible artifacts and inaccurate CT numbers. In this paper, an efficient polyenergetic Simultaneous Algebraic Reconstruction Technique (pSART) was presented to eliminate the beam hardening artifacts and to improve the CT quantitative imaging ability. Methods: Our algorithm made threea priori assumptions: (1) the human body is composed of several base materials (e.g., fat, breast, soft tissue, bone, and iodine); (2) images can be coarsely segmented to two types of regions, i.e., nonbone regions and noniodine regions; and (3) each voxel can be decomposed into a mixture of two most suitable base materials according to its attenuation value and its corresponding region type information. Based on the above assumptions, energy-independent accumulated effective lengths of all base materials can be fast computed in the forward ray-tracing process and be used repeatedly to obtain accurate polyenergetic projections, with which a SART-based equation can correctly update each voxel in the backward projecting process to iteratively reconstruct artifact-free images. This approach effectively reduces the influence of polyenergetic x-ray sources and it further enables monoenergetic images to be reconstructed at any arbitrarily preselected target energies. A series of simulation tests were performed on a size-variable cylindrical phantom and a realistic anthropomorphic thorax phantom. In addition, a phantom experiment was also performed on a clinical CT scanner to further quantitatively validate the proposed algorithm. Results: The simulations with the cylindrical phantom and the anthropomorphic thorax phantom showed that the proposed algorithm completely eliminated beam hardening artifacts and enabled quantitative imaging across different materials, phantom sizes, and spectra, as the absolute relative errors were reduced

  15. Pixel-based reconstruction (PBR) promising simultaneous techniques for CT reconstructions.

    PubMed

    Fager, R S; Peddanarappagari, K V; Kumar, G N

    1993-01-01

    Algorithms belonging to the class of pixel-based reconstruction (PBR) algorithms, which are similar to simultaneous iterative reconstruction techniques (SIRTs) for reconstruction of objects from their fan beam projections in X-ray transmission tomography, are discussed. The general logic of these algorithms is discussed. Simulation studies indicate that, contrary to previous results with parallel beam projections, the iterative algebraic algorithms do not diverge when a more logical technique of obtaining the pseudoprojections is used. These simulations were carried out under conditions in which the number of object pixels exceeded (double) the number of detector pixel readings, i.e., the equations were highly underdetermined. The effect of the number of projections on the reconstruction and the convergence (empirical) to the exact solution is shown. For comparison, the reconstructions obtained by convolution backprojection are also given.

  16. Normalization of CT scans reconstructed with different kernels to reduce variability in emphysema measurements

    NASA Astrophysics Data System (ADS)

    Gallardo Estrella, L.; van Ginneken, B.; van Rikxoort, E. M.

    2013-03-01

    Chronic Obstructive Pulmonary Disease (COPD) is a lung disease characterized by progressive air flow limitation caused by emphysema and chronic bronchitis. Emphysema is quantified from chest computed tomography (CT) scans as the percentage of attentuation values below a fixed threshold. The emphysema quantification varies substantially between scans reconstructed with different kernels, limiting the possibilities to compare emphysema quantifications obtained from scans with different reconstruction parameters. In this paper we propose a method to normalize scans reconstructed with different kernels to have the same characteristics as scans reconstructed with a reference kernel and investigate if this normalization reduces the variability in emphysema quantification. The proposed normalization splits a CT scan into different frequency bands based on hierarchical unsharp masking. Normalization is performed by changing the energy in each frequency band to the average energy in each band in the reference kernel. A database of 15 subjects with COPD was constructed for this study. All subjects were scanned at total lung capacity and the scans were reconstructed with four different reconstruction kernels. The normalization was applied to all scans. Emphysema quantification was performed before and after normalization. It is shown that the emphysema score varies substantially before normalization but the variation diminishes after normalization.

  17. A motion-compensated scheme for helical cone-beam reconstruction in cardiac CT angiography

    SciTech Connect

    Stevendaal, U. van; Berg, J. von; Lorenz, C.; Grass, M.

    2008-07-15

    Since coronary heart disease is one of the main causes of death all over the world, cardiac computed tomography (CT) imaging is an application of very high interest in order to verify indications timely. Due to the cardiac motion, electrocardiogram (ECG) gating has to be implemented into the reconstruction of the measured projection data. However, the temporal and spatial resolution is limited due to the mechanical movement of the gantry and due to the fact that a finite angular span of projections has to be acquired for the reconstruction of each voxel. In this article, a motion-compensated reconstruction method for cardiac CT is described, which can be used to increase the signal-to-noise ratio or to suppress motion blurring. Alternatively, it can be translated into an improvement of the temporal and spatial resolution. It can be applied to the entire heart in common and to high contrast objects moving with the heart in particular, such as calcified plaques or devices like stents. The method is based on three subsequent steps: As a first step, the projection data acquired in low pitch helical acquisition mode together with the ECG are reconstructed at multiple phase points. As a second step, the motion-vector field is calculated from the reconstructed images in relation to the image in a reference phase. Finally, a motion-compensated reconstruction is carried out for the reference phase using those projections, which cover the cardiac phases for which the motion-vector field has been determined.

  18. Phase-selective image reconstruction of the lungs in small animals using micro-CT

    NASA Astrophysics Data System (ADS)

    Johnston, S. M.; Perez, B. A.; Kirsch, D. G.; Badea, C. T.

    2010-04-01

    Gating in small animal imaging can compensate for artifacts due to physiological motion. This paper presents a strategy for sampling and image reconstruction in the rodent lung using micro-CT. The approach involves rapid sampling of freebreathing mice without any additional hardware to detect respiratory motion. The projection images are analyzed postacquisition to derive a respiratory signal, which is used to provide weighting factors for each projection that favor a selected phase of the respiration (e.g. end-inspiration or end-expiration) for the reconstruction. Since the sampling cycle and the respiratory cycle are uncorrelated, the sets of projections corresponding to any of the selected respiratory phases do not have a regular angular distribution. This drastically affects the image quality of reconstructions based on simple filtered backprojection. To address this problem, we use an iterative reconstruction algorithm that combines the Simultaneous Algebraic Reconstruction Technique with Total Variation minimization (SART-TV). At each SART-TV iteration, backprojection is performed with a set of weighting factors that favor the desired respiratory phase. To reduce reconstruction time, the algorithm is implemented on a graphics processing unit. The performance of the proposed approach was investigated in simulations and in vivo scans of mice with primary lung cancers imaged with our in-house developed dual tube/detector micro-CT system. We note that if the ECG signal is acquired during sampling, the same approach could be used for phase-selective cardiac imaging.

  19. PET/CT (and CT) instrumentation, image reconstruction and data transfer for radiotherapy planning.

    PubMed

    Sattler, Bernhard; Lee, John A; Lonsdale, Markus; Coche, Emmanuel

    2010-09-01

    The positron emission tomography in combination with CT in hybrid, cross-modality imaging systems (PET/CT) gains more and more importance as a part of the treatment-planning procedure in radiotherapy. Positron emission tomography (PET), as a integral part of nuclear medicine imaging and non-invasive imaging technique, offers the visualization and quantification of pre-selected tracer metabolism. In combination with the structural information from CT, this molecular imaging technique has great potential to support and improve the outcome of the treatment-planning procedure prior to radiotherapy. By the choice of the PET-Tracer, a variety of different metabolic processes can be visualized. First and foremost, this is the glucose metabolism of a tissue as well as for instance hypoxia or cell proliferation. This paper comprises the system characteristics of hybrid PET/CT systems. Acquisition and processing protocols are described in general and modifications to cope with the special needs in radiooncology. This starts with the different position of the patient on a special table top, continues with the use of the same fixation material as used for positioning of the patient in radiooncology while simulation and irradiation and leads to special processing protocols that include the delineation of the volumes that are subject to treatment planning and irradiation (PTV, GTV, CTV, etc.). General CT acquisition and processing parameters as well as the use of contrast enhancement of the CT are described. The possible risks and pitfalls the investigator could face during the hybrid-imaging procedure are explained and listed. The interdisciplinary use of different imaging modalities implies a increase of the volume of data created. These data need to be stored and communicated fast, safe and correct. Therefore, the DICOM-Standard provides objects and classes for this purpose (DICOM RT). Furthermore, the standard DICOM objects and classes for nuclear medicine (NM, PT) and

  20. List-mode reconstruction for the Biograph mCT with physics modeling and event-by-event motion correction

    NASA Astrophysics Data System (ADS)

    Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E.; Liu, Chi; Carson, Richard E.

    2013-08-01

    Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion

  1. List-mode reconstruction for the Biograph mCT with physics modeling and event-by-event motion correction.

    PubMed

    Jin, Xiao; Chan, Chung; Mulnix, Tim; Panin, Vladimir; Casey, Michael E; Liu, Chi; Carson, Richard E

    2013-08-21

    Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion

  2. A novel scheme to design the filter for CT reconstruction using FBP algorithm.

    PubMed

    Shi, Hongli; Luo, Shuqian

    2013-06-01

    The Filtered Back-Projection (FBP) algorithm is the most important technique for computerized tomographic (CT) imaging, in which the ramp filter plays a key role. FBP algorithm had been derived using the continuous system model. However, it has to be discretized in practical applications, which necessarily produces distortion in the reconstructed images. A novel scheme is proposed to design the filters to substitute the standard ramp filter to improve the reconstruction performance for parallel beam tomography. The design scheme is presented under the discrete image model and discrete projection environment. The designs are achieved by constrained optimization procedures. The designed filter can be regarded as the optimal filter for the corresponding parameters in some ways. Some filters under given parameters (such as image size and scanning angles) have been designed. The performance evaluation of CT reconstruction shows that the designed filters are better than the ramp filter in term of some general criteria. The 2-D or 3-D FBP algorithms for fan beam tomography used in most CT systems, are obtained by modifying the FBP algorithm for parallel beam tomography. Therefore, the designed filters can be used for fan beam tomography and have potential applications in practical CT systems.

  3. Expectation maximization (EM) algorithms using polar symmetries for computed tomography (CT) image reconstruction.

    PubMed

    Rodríguez-Alvarez, M J; Soriano, A; Iborra, A; Sánchez, F; González, A J; Conde, P; Hernández, L; Moliner, L; Orero, A; Vidal, L F; Benlloch, J M

    2013-09-01

    We suggest a symmetric-polar pixellation scheme which makes possible a reduction of the computational cost for expectation maximization (EM) iterative algorithms. The proposed symmetric-polar pixellation allows us to deal with 3D images as a whole problem without dividing the 3D problem into 2D slices approach. Performance evaluation of each approach in terms of stability and image quality is presented. Exhaustive comparisons between all approaches were conducted in a 2D based image reconstruction model. From these 2D approaches, that showing the best performances were finally implemented and evaluated in a 3D based image reconstruction model. Comparison to 3D images reconstructed with FBP is also presented. Although the algorithm is presented in the context of computed tomography (CT) image reconstruction, it can be applied to any other tomographic technique as well, due to the fact that the only requirement is a scanning geometry involving measurements of an object under different projection angles. Real data have been acquired with a small animal (CT) scanner to verify the proposed mathematical description of the CT system. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Effect of low-dose CT and iterative reconstruction on trabecular bone microstructure assessment

    NASA Astrophysics Data System (ADS)

    Kopp, Felix K.; Baum, Thomas; Nasirudin, Radin A.; Mei, Kai; Garcia, Eduardo G.; Burgkart, Rainer; Rummeny, Ernst J.; Bauer, Jan S.; Noël, Peter B.

    2016-03-01

    The trabecular bone microstructure is an important factor in the development of osteoporosis. It is well known that its deterioration is one effect when osteoporosis occurs. Previous research showed that the analysis of trabecular bone microstructure enables more precise diagnoses of osteoporosis compared to a sole measurement of the mineral density. Microstructure parameters are assessed on volumetric images of the bone acquired either with high-resolution magnetic resonance imaging, high-resolution peripheral quantitative computed tomography or high-resolution computed tomography (CT), with only CT being applicable to the spine, which is one of clinically most relevant fracture sites. However, due to the high radiation exposure for imaging the whole spine these measurements are not applicable in current clinical routine. In this work, twelve vertebrae from three different donors were scanned with standard and low radiation dose. Trabecular bone microstructure parameters were assessed for CT images reconstructed with statistical iterative reconstruction (SIR) and analytical filtered backprojection (FBP). The resulting structure parameters were correlated to the biomechanically determined fracture load of each vertebra. Microstructure parameters assessed for low-dose data reconstructed with SIR significantly correlated with fracture loads as well as parameters assessed for standard-dose data reconstructed with FBP. Ideal results were achieved with low to zero regularization strength yielding microstructure parameters not significantly different from those assessed for standard-dose FPB data. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

  5. Reconstruction of cochlea based on micro-CT and histological images of the human inner ear.

    PubMed

    Bellos, Christos; Rigas, George; Spiridon, Ioannis F; Bibas, Athanasios; Iliopoulou, Dimitra; Böhnke, Frank; Koutsouris, Dimitrios; Fotiadis, Dimitrios I

    2014-01-01

    The study of the normal function and pathology of the inner ear has unique difficulties as it is inaccessible during life and, so, conventional techniques of pathologic studies such as biopsy and surgical excision are not feasible, without further impairing function. Mathematical modelling is therefore particularly attractive as a tool in researching the cochlea and its pathology. The first step towards efficient mathematical modelling is the reconstruction of an accurate three dimensional (3D) model of the cochlea that will be presented in this paper. The high quality of the histological images is being exploited in order to extract several sections of the cochlea that are not visible on the micro-CT (mCT) images (i.e., scala media, spiral ligament, and organ of Corti) as well as other important sections (i.e., basilar membrane, Reissner membrane, scala vestibule, and scala tympani). The reconstructed model is being projected in the centerline of the coiled cochlea, extracted from mCT images, and represented in the 3D space. The reconstruction activities are part of the SIFEM project, which will result in the delivery of an infrastructure, semantically interlinking various tools and libraries (i.e., segmentation, reconstruction, and visualization tools) with the clinical knowledge, which is represented by existing data, towards the delivery of a robust multiscale model of the inner ear.

  6. A multi-resolution approach to retrospectively-gated cardiac micro-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Clark, D. P.; Johnson, G. A.; Badea, C. T.

    2014-03-01

    In preclinical research, micro-CT is commonly used to provide anatomical information; however, there is significant interest in using this technology to obtain functional information in cardiac studies. The fastest acquisition in 4D cardiac micro-CT imaging is achieved via retrospective gating, resulting in irregular angular projections after binning the projections into phases of the cardiac cycle. Under these conditions, analytical reconstruction algorithms, such as filtered back projection, suffer from streaking artifacts. Here, we propose a novel, multi-resolution, iterative reconstruction algorithm inspired by robust principal component analysis which prevents the introduction of streaking artifacts, while attempting to recover the highest temporal resolution supported by the projection data. The algorithm achieves these results through a unique combination of the split Bregman method and joint bilateral filtration. We illustrate the algorithm's performance using a contrast-enhanced, 2D slice through the MOBY mouse phantom and realistic projection acquisition and reconstruction parameters. Our results indicate that the algorithm is robust to under sampling levels of only 34 projections per cardiac phase and, therefore, has high potential in reducing both acquisition times and radiation dose. Another potential advantage of the multi-resolution scheme is the natural division of the reconstruction problem into a large number of independent sub-problems which can be solved in parallel. In future work, we will investigate the performance of this algorithm with retrospectively-gated, cardiac micro-CT data.

  7. Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

    NASA Astrophysics Data System (ADS)

    Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

    2017-03-01

    In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

  8. SparseCT: interrupted-beam acquisition and sparse reconstruction for radiation dose reduction

    NASA Astrophysics Data System (ADS)

    Koesters, Thomas; Knoll, Florian; Sodickson, Aaron; Sodickson, Daniel K.; Otazo, Ricardo

    2017-03-01

    State-of-the-art low-dose CT methods reduce the x-ray tube current and use iterative reconstruction methods to denoise the resulting images. However, due to compromises between denoising and image quality, only moderate dose reductions up to 30-40% are accepted in clinical practice. An alternative approach is to reduce the number of x-ray projections and use compressed sensing to reconstruct the full-tube-current undersampled data. This idea was recognized in the early days of compressed sensing and proposals for CT dose reduction appeared soon afterwards. However, no practical means of undersampling has yet been demonstrated in the challenging environment of a rapidly rotating CT gantry. In this work, we propose a moving multislit collimator as a practical incoherent undersampling scheme for compressed sensing CT and evaluate its application for radiation dose reduction. The proposed collimator is composed of narrow slits and moves linearly along the slice dimension (z), to interrupt the incident beam in different slices for each x-ray tube angle (θ). The reduced projection dataset is then reconstructed using a sparse approach, where 3D image gradients are employed to enforce sparsity. The effects of the collimator slits on the beam profile were measured and represented as a continuous slice profile. SparseCT was tested using retrospective undersampling and compared against commercial current-reduction techniques on phantoms and in vivo studies. Initial results suggest that SparseCT may enable higher performance than current-reduction, particularly for high dose reduction factors.

  9. GPU-accelerated regularized iterative reconstruction for few-view cone beam CT

    SciTech Connect

    Matenine, Dmitri; Goussard, Yves

    2015-04-15

    Purpose: The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. Methods: The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it is implemented on a graphics processing unit, using parallelization to accelerate computations. Results: The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1–2 min and are compatible with the typical clinical workflow for nonreal-time applications. Conclusions: Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.

  10. GPU-accelerated regularized iterative reconstruction for few-view cone beam CT.

    PubMed

    Matenine, Dmitri; Goussard, Yves; Després, Philippe

    2015-04-01

    The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it is implemented on a graphics processing unit, using parallelization to accelerate computations. The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1-2 min and are compatible with the typical clinical workflow for nonreal-time applications. Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.

  11. Effective dose estimation during conventional and CT urography

    NASA Astrophysics Data System (ADS)

    Alzimami, K.; Sulieman, A.; Omer, E.; Suliman, I. I.; Alsafi, K.

    2014-11-01

    Intravenous urography (IVU) and CT urography (CTU) are efficient radiological examinations for the evaluation of the urinary system disorders. However patients are exposed to a significant radiation dose. The objectives of this study are to: (i) measure and compare patient radiation dose by computed tomography urography (CTU) and conventional intravenous urography (IVU) and (ii) evaluate organ equivalent dose and cancer risks from CTU and IVU imaging procedures. A total of 141 patients were investigated. A calibrated CT machine (Siemens-Somatom Emotion duo) was used for CTU, while a Shimadzu X ray machine was used for IVU. Thermoluminescence dosimeters (TLD-GR200A) were used to measure patients' entrance surface doses (ESD). TLDs were calibrated under reproducible reference conditions. Patients radiation dose values (DLP) for CTU were 172±61 mGy cm, CTDIvol 4.75±2 mGy and effective dose 2.58±1 mSv. Patient cancer probabilities were estimated to be 1.4 per million per CTU examination. Patients ESDs values for IVU were 21.62±5 mGy, effective dose 1.79±1 mSv. CT involves a higher effective dose than IVU. In this study the radiation dose is considered low compared to previous studies. The effective dose from CTU procedures was 30% higher compared to IVU procedures. Wide dose variation between patient doses suggests that optimization is not fulfilled yet.

  12. Oxygen transport properties estimation by DSMC-CT simulations

    SciTech Connect

    Bruno, Domenico; Frezzotti, Aldo; Ghiroldi, Gian Pietro

    2014-12-09

    Coupling DSMC simulations with classical trajectories calculations is emerging as a powerful tool to improve predictive capabilities of computational rarefied gas dynamics. The considerable increase of computational effort outlined in the early application of the method (Koura,1997) can be compensated by running simulations on massively parallel computers. In particular, GPU acceleration has been found quite effective in reducing computing time (Ferrigni,2012; Norman et al.,2013) of DSMC-CT simulations. The aim of the present work is to study rarefied Oxygen flows by modeling binary collisions through an accurate potential energy surface, obtained by molecular beams scattering (Aquilanti, et al.,1999). The accuracy of the method is assessed by calculating molecular Oxygen shear viscosity and heat conductivity following three different DSMC-CT simulation methods. In the first one, transport properties are obtained from DSMC-CT simulations of spontaneous fluctuation of an equilibrium state (Bruno et al, Phys. Fluids, 23, 093104, 2011). In the second method, the collision trajectory calculation is incorporated in a Monte Carlo integration procedure to evaluate the Taxman’s expressions for the transport properties of polyatomic gases (Taxman,1959). In the third, non-equilibrium zero and one-dimensional rarefied gas dynamic simulations are adopted and the transport properties are computed from the non-equilibrium fluxes of momentum and energy. The three methods provide close values of the transport properties, their estimated statistical error not exceeding 3%. The experimental values are slightly underestimated, the percentage deviation being, again, few percent.

  13. Novel iterative reconstruction method with optimal dose usage for partially redundant CT-acquisition

    NASA Astrophysics Data System (ADS)

    Bruder, H.; Raupach, R.; Sunnegardh, J.; Allmendinger, T.; Klotz, E.; Stierstorfer, K.; Flohr, T.

    2015-11-01

    In CT imaging, a variety of applications exist which are strongly SNR limited. However, in some cases redundant data of the same body region provide additional quanta. Examples: in dual energy CT, the spatial resolution has to be compromised to provide good SNR for material decomposition. However, the respective spectral dataset of the same body region provides additional quanta which might be utilized to improve SNR of each spectral component. Perfusion CT is a high dose application, and dose reduction is highly desirable. However, a meaningful evaluation of perfusion parameters might be impaired by noisy time frames. On the other hand, the SNR of the average of all time frames is extremely high. In redundant CT acquisitions, multiple image datasets can be reconstructed and averaged to composite image data. These composite image data, however, might be compromised with respect to contrast resolution and/or spatial resolution and/or temporal resolution. These observations bring us to the idea of transferring high SNR of composite image data to low SNR ‘source’ image data, while maintaining their resolution. It has been shown that the noise characteristics of CT image data can be improved by iterative reconstruction (Popescu et al 2012 Book of Abstracts, 2nd CT Meeting (Salt Lake City, UT) p 148). In case of data dependent Gaussian noise it can be modelled with image-based iterative reconstruction at least in an approximate manner (Bruder et al 2011 Proc. SPIE 7961 79610J). We present a generalized update equation in image space, consisting of a linear combination of the previous update, a correction term which is constrained by the source image data, and a regularization prior, which is initialized by the composite image data. This iterative reconstruction approach we call bimodal reconstruction (BMR). Based on simulation data it is shown that BMR can improve low contrast detectability, substantially reduces the noise power and has the potential to recover

  14. Novel iterative reconstruction method with optimal dose usage for partially redundant CT-acquisition.

    PubMed

    Bruder, H; Raupach, R; Sunnegardh, J; Allmendinger, T; Klotz, E; Stierstorfer, K; Flohr, T

    2015-11-07

    In CT imaging, a variety of applications exist which are strongly SNR limited. However, in some cases redundant data of the same body region provide additional quanta. Examples in dual energy CT, the spatial resolution has to be compromised to provide good SNR for material decomposition. However, the respective spectral dataset of the same body region provides additional quanta which might be utilized to improve SNR of each spectral component. Perfusion CT is a high dose application, and dose reduction is highly desirable. However, a meaningful evaluation of perfusion parameters might be impaired by noisy time frames. On the other hand, the SNR of the average of all time frames is extremely high.In redundant CT acquisitions, multiple image datasets can be reconstructed and averaged to composite image data. These composite image data, however, might be compromised with respect to contrast resolution and/or spatial resolution and/or temporal resolution. These observations bring us to the idea of transferring high SNR of composite image data to low SNR 'source' image data, while maintaining their resolution.It has been shown that the noise characteristics of CT image data can be improved by iterative reconstruction (Popescu et al 2012 Book of Abstracts, 2nd CT Meeting (Salt Lake City, UT) p 148). In case of data dependent Gaussian noise it can be modelled with image-based iterative reconstruction at least in an approximate manner (Bruder et al 2011 Proc. SPIE 7961 79610J). We present a generalized update equation in image space, consisting of a linear combination of the previous update, a correction term which is constrained by the source image data, and a regularization prior, which is initialized by the composite image data. This iterative reconstruction approach we call bimodal reconstruction (BMR). Based on simulation data it is shown that BMR can improve low contrast detectability, substantially reduces the noise power and has the potential to recover spatial

  15. Surgical anatomy of the frontal recess--is there a benefit in multiplanar CT-reconstruction?

    PubMed

    Leunig, A; Sommer, B; Betz, C S; Sommer, F

    2008-09-01

    Anatomical variations in the sinus region are not necessarily pathological, but they may complicate the anatomy of the lateral nasal wall and contribute to the occurrence or persistence of chronic inflammatory diseases. In this study the interpretations of initial coronal CT scans were significantly altered following multiplanar CT-reconstruction. Assuming that a multiplanar analysis includes coronal views, we may conclude that imaging in three planes yields more information and provides a substantial benefit in the planning and performance of a surgical procedure on the paranasal sinuses.

  16. "High-precision, reconstructed 3D model" of skull scanned by conebeam CT: Reproducibility verified using CAD/CAM data.

    PubMed

    Katsumura, Seiko; Sato, Keita; Ikawa, Tomoko; Yamamura, Keiko; Ando, Eriko; Shigeta, Yuko; Ogawa, Takumi

    2016-01-01

    Computed tomography (CT) scanning has recently been introduced into forensic medicine and dentistry. However, the presence of metal restorations in the dentition can adversely affect the quality of three-dimensional reconstruction from CT scans. In this study, we aimed to evaluate the reproducibility of a "high-precision, reconstructed 3D model" obtained from a conebeam CT scan of dentition, a method that might be particularly helpful in forensic medicine. We took conebeam CT and helical CT images of three dry skulls marked with 47 measuring points; reconstructed three-dimensional images; and measured the distances between the points in the 3D images with a computer-aided design/computer-aided manufacturing (CAD/CAM) marker. We found that in comparison with the helical CT, conebeam CT is capable of reproducing measurements closer to those obtained from the actual samples. In conclusion, our study indicated that the image-reproduction from a conebeam CT scan was more accurate than that from a helical CT scan. Furthermore, the "high-precision reconstructed 3D model" facilitates reliable visualization of full-sized oral and maxillofacial regions in both helical and conebeam CT scans.

  17. Developing milk industry estimates for dose reconstruction projects

    SciTech Connect

    Beck, D.M.; Darwin, R.F. )

    1991-01-01

    One of the most important contributors to radiation doses from hanford during the 1944-1947 period was radioactive iodine. Consumption of milk from cows that ate vegetation contaminated with iodine is likely the dominant pathway of human exposure. To estimate the doses people could have received from this pathway, it is necessary to reconstruct the amount of milk consumed by people living near Hanford, the source of the milk, and the type of feed that the milk cows ate. This task is challenging because the dairy industry has undergone radical changes since the end of World War 2, and records that document the impact of these changes on the study area are scarce. Similar problems are faced by researchers on most dose reconstruction efforts. The purpose of this work is to document and evaluate the methods used on the Hanford Environmental Dose Reconstruction (HEDR) Project to reconstruct the milk industry and to present preliminary results.

  18. Performance analysis of model based iterative reconstruction with dictionary learning in transportation security CT

    NASA Astrophysics Data System (ADS)

    Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno

    2016-05-01

    In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.

  19. Dual-resolution image reconstruction for region-of-interest CT scan

    NASA Astrophysics Data System (ADS)

    Jin, S. O.; Shin, K. Y.; Yoo, S. K.; Kim, J. G.; Kim, K. H.; Huh, Y.; Lee, S. Y.; Kwon, O.-K.

    2014-07-01

    In ordinary CT scan, so called full field-of-view (FFOV) scan, in which the x-ray beam span covers the whole section of the body, a large number of projections are necessary to reconstruct high resolution images. However, excessive x-ray dose is a great concern in FFOV scan. Region-of-interest (ROI) scan is a method to visualize the ROI in high resolution while reducing the x-ray dose. But, ROI scan suffers from bright-band artifacts which may hamper CT-number accuracy. In this study, we propose an image reconstruction method to eliminate the band artifacts in the ROI scan. In addition to the ROI scan with high sampling rate in the view direction, we get FFOV projection data with much lower sampling rate. Then, we reconstruct images in the compressed sensing (CS) framework with dual resolutions, that is, high resolution in the ROI and low resolution outside the ROI. For the dual-resolution image reconstruction, we implemented the dual-CS reconstruction algorithm in which data fidelity and total variation (TV) terms were enforced twice in the framework of adaptive steepest descent projection onto convex sets (ASD-POCS). The proposed method has remarkably reduced the bright-band artifacts at around the ROI boundary, and it has also effectively suppressed the streak artifacts over the entire image. We expect the proposed method can be greatly used for dual-resolution imaging with reducing the radiation dose, artifacts and scan time.

  20. Evaluation of accuracy of 3D reconstruction images using multi-detector CT and cone-beam CT

    PubMed Central

    Kim, Mija; YI, Won-Jin; Heo, Min-Suk; Lee, Sam-Sun; Choi, Soon-Chul

    2012-01-01

    Purpose This study was performed to determine the accuracy of linear measurements on three-dimensional (3D) images using multi-detector computed tomography (MDCT) and cone-beam computed tomography (CBCT). Materials and Methods MDCT and CBCT were performed using 24 dry skulls. Twenty-one measurements were taken on the dry skulls using digital caliper. Both types of CT data were imported into OnDemand software and identification of landmarks on the 3D surface rendering images and calculation of linear measurements were performed. Reproducibility of the measurements was assessed using repeated measures ANOVA and ICC, and the measurements were statistically compared using a Student t-test. Results All assessments under the direct measurement and image-based measurements on the 3D CT surface rendering images using MDCT and CBCT showed no statistically difference under the ICC examination. The measurements showed no differences between the direct measurements of dry skull and the image-based measurements on the 3D CT surface rendering images (P>.05). Conclusion Three-dimensional reconstructed surface rendering images using MDCT and CBCT would be appropriate for 3D measurements. PMID:22474645

  1. Patient-specific dose estimation for pediatric chest CT

    SciTech Connect

    Li Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

    2008-12-15

    Current methods for organ and effective dose estimations in pediatric CT are largely patient generic. Physical phantoms and computer models have only been developed for standard/limited patient sizes at discrete ages (e.g., 0, 1, 5, 10, 15 years old) and do not reflect the variability of patient anatomy and body habitus within the same size/age group. In this investigation, full-body computer models of seven pediatric patients in the same size/protocol group (weight: 11.9-18.2 kg) were created based on the patients' actual multi-detector array CT (MDCT) data. Organs and structures in the scan coverage were individually segmented. Other organs and structures were created by morphing existing adult models (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. Organ and effective dose of these patients from a chest MDCT scan protocol (64 slice LightSpeed VCT scanner, 120 kVp, 70 or 75 mA, 0.4 s gantry rotation period, pitch of 1.375, 20 mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated to simulate radiation transport in the same CT system. The seven patients had normalized effective dose of 3.7-5.3 mSv/100 mAs (coefficient of variation: 10.8%). Normalized lung dose and heart dose were 10.4-12.6 mGy/100 mAs and 11.2-13.3 mGy/100 mAs, respectively. Organ dose variations across the patients were generally small for large organs in the scan coverage (<7%), but large for small organs in the scan coverage (9%-18%) and for partially or indirectly exposed organs (11%-77%). Normalized effective dose correlated weakly with body weight (correlation coefficient: r=-0.80). Normalized lung dose and heart dose correlated strongly with mid-chest equivalent diameter (lung: r=-0.99, heart: r=-0.93); these strong correlation relationships can be used to estimate patient-specific organ dose for

  2. A case of pulmonary artery intimal sarcoma diagnosed with multislice CT scan with 3D reconstruction.

    PubMed

    Choi, Eui-Young; Yoon, Young-Won; Kwon, Hyuck Moon; Kim, Dongsoo; Park, Byung-Eun; Hong, Yoo-Sun; Koo, Ja-Seung; Kim, Tae-Hoon; Kim, Hyun-Seung

    2004-06-30

    Pulmonary artery intimal sarcoma is a rare highly lethal disease, with additional retrograde extension to pulmonic valve and right ventricle being an extremely rare condition. It is frequently mistaken for pulmonary thromboembolism. We report a case of 64-year-old woman with progressive dyspnea initially suspected and treated for pulmonary thromboembolism. Her helical chest CT scan with 3 dimensional (3D) reconstruction combined with echocardiography revealed a compacting main pulmonary artery mass extending to the right ventricular outflow tract and the right pulmonary artery. After excision of the mass, the patient's condition improved dramatically, and the pathologic findings revealed pulmonary intimal sarcoma. This report emphasizes that helical chest CT with 3D reconstruction can be an important tool to differentiate the characteristics of pulmonary artery lesions, such as intimal sarcoma and thromboembolism.

  3. Projection domain denoising method based on dictionary learning for low-dose CT image reconstruction.

    PubMed

    Zhang, Haiyan; Zhang, Liyi; Sun, Yunshan; Zhang, Jingyu

    2015-01-01

    Reducing X-ray tube current is one of the widely used methods for decreasing the radiation dose. Unfortunately, the signal-to-noise ratio (SNR) of the projection data degrades simultaneously. To improve the quality of reconstructed images, a dictionary learning based penalized weighted least-squares (PWLS) approach is proposed for sinogram denoising. The weighted least-squares considers the statistical characteristic of noise and the penalty models the sparsity of sinogram based on dictionary learning. Then reconstruct CT image using filtered back projection (FBP) algorithm from the denoised sinogram. The proposed method is particularly suitable for the projection data with low SNR. Experimental results show that the proposed method can get high-quality CT images when the signal to noise ratio of projection data declines sharply.

  4. Radiation dose reduction in medical x-ray CT via Fourier-based iterative reconstruction.

    PubMed

    Fahimian, Benjamin P; Zhao, Yunzhe; Huang, Zhifeng; Fung, Russell; Mao, Yu; Zhu, Chun; Khatonabadi, Maryam; DeMarco, John J; Osher, Stanley J; McNitt-Gray, Michael F; Miao, Jianwei

    2013-03-01

    A Fourier-based iterative reconstruction technique, termed Equally Sloped Tomography (EST), is developed in conjunction with advanced mathematical regularization to investigate radiation dose reduction in x-ray CT. The method is experimentally implemented on fan-beam CT and evaluated as a function of imaging dose on a series of image quality phantoms and anonymous pediatric patient data sets. Numerical simulation experiments are also performed to explore the extension of EST to helical cone-beam geometry. EST is a Fourier based iterative algorithm, which iterates back and forth between real and Fourier space utilizing the algebraically exact pseudopolar fast Fourier transform (PPFFT). In each iteration, physical constraints and mathematical regularization are applied in real space, while the measured data are enforced in Fourier space. The algorithm is automatically terminated when a proposed termination criterion is met. Experimentally, fan-beam projections were acquired by the Siemens z-flying focal spot technology, and subsequently interleaved and rebinned to a pseudopolar grid. Image quality phantoms were scanned at systematically varied mAs settings, reconstructed by EST and conventional reconstruction methods such as filtered back projection (FBP), and quantified using metrics including resolution, signal-to-noise ratios (SNRs), and contrast-to-noise ratios (CNRs). Pediatric data sets were reconstructed at their original acquisition settings and additionally simulated to lower dose settings for comparison and evaluation of the potential for radiation dose reduction. Numerical experiments were conducted to quantify EST and other iterative methods in terms of image quality and computation time. The extension of EST to helical cone-beam CT was implemented by using the advanced single-slice rebinning (ASSR) method. Based on the phantom and pediatric patient fan-beam CT data, it is demonstrated that EST reconstructions with the lowest scanner flux setting of 39 m

  5. Cubic Hermite Bezier spline based reconstruction of implanted aortic valve stents from CT images.

    PubMed

    Gessat, Michael; Altwegg, Lukas; Frauenfelder, Thomas; Plass, André; Falk, Volkmar

    2011-01-01

    Mechanical forces and strain induced by transcatheter aortic valve implantation are usually named as origins for postoperative left ventricular arrhythmia associated with the technique. No quantitative data has been published so far to substantiate this common belief. As a first step towards quantitative analysis of the biomechanic situation at the aortic root after transapical aortic valve implantation, we present a spline-based method for reconstruction of the implanted stent from CT images and for locally measuring the deformation of the stent.

  6. SU-D-207-04: GPU-Based 4D Cone-Beam CT Reconstruction Using Adaptive Meshing Method

    SciTech Connect

    Zhong, Z; Gu, X; Iyengar, P; Mao, W; Wang, J; Guo, X

    2015-06-15

    Purpose: Due to the limited number of projections at each phase, the image quality of a four-dimensional cone-beam CT (4D-CBCT) is often degraded, which decreases the accuracy of subsequent motion modeling. One of the promising methods is the simultaneous motion estimation and image reconstruction (SMEIR) approach. The objective of this work is to enhance the computational speed of the SMEIR algorithm using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the tetrahedral mesh based on the features of a reference phase 4D-CBCT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. After the mesh generation, the updated motion model and other phases of 4D-CBCT can be obtained by matching the 4D-CBCT projection images at each phase with the corresponding forward projections of the deformed reference phase of 4D-CBCT. The entire process of this 4D-CBCT reconstruction method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its tremendous parallel computing ability. Results: A 4D XCAT digital phantom was used to test the proposed mesh-based image reconstruction algorithm. The image Result shows both bone structures and inside of the lung are well-preserved and the tumor position can be well captured. Compared to the previous voxel-based CPU implementation of SMEIR, the proposed method is about 157 times faster for reconstructing a 10 -phase 4D-CBCT with dimension 256×256×150. Conclusion: The GPU-based parallel 4D CBCT reconstruction method uses the feature-based mesh for estimating motion model and demonstrates equivalent image Result with previous voxel-based SMEIR approach, with significantly improved computational speed.

  7. The impact of iterative reconstruction on image quality and radiation dose in thoracic and abdominal CT.

    PubMed

    Kalmar, Peter I; Quehenberger, Franz; Steiner, Jürgen; Lutfi, Andre; Bohlsen, Dennis; Talakic, Emina; Hassler, Eva Maria; Schöllnast, Helmut

    2014-08-01

    To compare the image quality and radiation dose between iterative reconstruction (IR) and standard filtered back projection (FBP) in CT of the chest and abdomen. Thoracic CT was performed in 50 patients (38 male, 12 female; mean age, 51 ± 23 yrs; range, 7-85 yrs) and abdominal CT was performed in 50 patients (36 male, 14 female; mean age, 62 ± 13 yrs; range, 20-85 yrs), using IR as well as FBP for image reconstruction. Image noise was quantitatively assessed measuring standard deviation of Hounsfield Units (HU) in defined regions of interest in subcutaneous tissue. Scan length and Computed Tomography Dose Index (CTDI) were documented. Scan length, image noise, and CTDI of both reconstruction techniques were compared by using paired tests according to the nature of variables (McNemar test or Student t test). Overall subjective image quality and subjective image noise were compared. There was no significant difference between the protocols in terms of mean scan length (p>0.05). Image noise was statistically significantly higher with IR, although the difference was clinically insignificant (13.3 ± 3.0 HU and 13.6 ± 3.0 HU for thoracic CT and 11.5 ± 3.1 HU and 11.7 ± 3.0 HU for abdominal CT, p<0.05). There was no significant difference in overall subjective image quality and subjective image noise. The radiation dose was significantly lower with IR. Volume-weighted CTDI decreased by 64% (6.2 ± 2.5 mGy versus 17.1 ± 9.5 mGy, p<0.001) for thoracic CT and by 58% (7.8 ± 4.6 mGy versus 18.5 ± 8.6 mGy, p<0.001) for abdominal CT. Our study shows that in thoracic and abdominal CT with IR, there is no clinically significant impact on image quality, yet a significant radiation dose reduction compared to FBP. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  8. Analysis of Cone-Beam Artifacts in off-Centered Circular CT for Four Reconstruction Methods

    PubMed Central

    Peyrin, F.; Sappey-Marinier, D.

    2006-01-01

    Cone-beam (CB) acquisition is increasingly used for truly three-dimensional X-ray computerized tomography (CT). However, tomographic reconstruction from data collected along a circular trajectory with the popular Feldkamp algorithm is known to produce the so-called CB artifacts. These artifacts result from the incompleteness of the source trajectory and the resulting missing data in the Radon space increasing with the distance to the plane containing the source orbit. In the context of the development of integrated PET/CT microscanners, we introduced a novel off-centered circular CT cone-beam geometry. We proposed a generalized Feldkamp formula (α-FDK) adapted to this geometry, but reconstructions suffer from increased CB artifacts. In this paper, we evaluate and compare four different reconstruction methods for correcting CB artifacts in off-centered geometry. We consider the α-FDK algorithm, the shift-variant FBP method derived from the T-FDK, an FBP method based on the Grangeat formula, and an iterative algebraic method (SART). The results show that the low contrast artifacts can be efficiently corrected by the shift-variant method and the SART method to achieve good quality images at the expense of increased computation time, but the geometrical deformations are still not compensated for by these techniques. PMID:23165048

  9. Quantification of airway morphometry: the effect of CT acquisition and reconstruction parameters

    NASA Astrophysics Data System (ADS)

    Leader, J. Ken; Zheng, Bin; Sciurba, Frank C.; Coxson, Harvey O.; Fuhrman, Carl R.; McMurray, Jessica M.; Park, Sang C.; Maitz, Glenn S.; Gur, David

    2007-03-01

    This study measured the accuracy of our airway quantification scheme using phantoms airway under different CT protocols. Airway remodeling is associated with several thoracic diseases (e.g., chronic bronchitis, asthma, and bronchiectasis), and, therefore, quantification of airway remodeling may have wide clinical application. Our scheme assigns pixels partial membership in the airway wall and lumen based on the pixel's HU value, which is intended to account for partial volume averaging inherent in CT image reconstruction. Twenty-four phantom airways with an outer diameter from 2.6 to 14.0 mm and wall thicknesses from 0.5 to 2.0 mm were analyzed. The absolute differences between measurements supplied by the manufacture and computed from CT images acquired at 40 mAs and reconstructed at 1.25 mm thickness using GE's "soft" and "lung" reconstruction kernels for lumen area ranged from 1.4% to 49.3% and 0.4% to 33.0%, respectively, and for wall area ranged from 0.3% to 118.0% and 2.1 to 92.9%, respectively. Accuracy typically improved as the kernel's spatial frequency increased. Airways whose wall thickness was close to the pixels dimensions were challenging to quantify. The partial membership assignment of our airway quantification accurately computed airway morphometry across a range of phantom airway sizes.

  10. Towards local progression estimation of pulmonary emphysema using CT.

    PubMed

    Staring, M; Bakker, M E; Stolk, J; Shamonin, D P; Reiber, J H C; Stoel, B C

    2014-02-01

    Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying linearity assumption

  11. 3D cardiac motion reconstruction from CT data and tagged MRI.

    PubMed

    Wang, Xiaoxu; Mihalef, Viorel; Qian, Zhen; Voros, Szilard; Metaxas, Dimitris

    2012-01-01

    In this paper we present a novel method for left ventricle (LV) endocardium motion reconstruction using high resolution CT data and tagged MRI. High resolution CT data provide anatomic details on the LV endocardial surface, such as the papillary muscle and trabeculae carneae. Tagged MRI provides better time resolution. The combination of these two imaging techniques can give us better understanding on left ventricle motion. The high resolution CT images are segmented with mean shift method and generate the LV endocardium mesh. The meshless deformable model built with high resolution endocardium surface from CT data fit to the tagged MRI of the same phase. 3D deformation of the myocardium is computed with the Lagrangian dynamics and local Laplacian deformation. The segmented inner surface of left ventricle is compared with the heart inner surface picture and show high agreement. The papillary muscles are attached to the inner surface with roots. The free wall of the left ventricle inner surface is covered with trabeculae carneae. The deformation of the heart wall and the papillary muscle in the first half of the cardiac cycle is presented. The motion reconstruction results are very close to the live heart video.

  12. Objective assessment of image quality and dose reduction in CT iterative reconstruction

    SciTech Connect

    Vaishnav, J. Y. Jung, W. C.; Popescu, L. M.; Zeng, R.; Myers, K. J.

    2014-07-15

    Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve. Methods: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction. Results: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance. Conclusions: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality.

  13. Adapted morphing model for 3D volume reconstruction applied to abdominal CT images

    NASA Astrophysics Data System (ADS)

    Fadeev, Aleksey; Eltonsy, Nevine; Tourassi, Georgia; Martin, Robert; Elmaghraby, Adel

    2005-04-01

    The purpose of this study was to develop a 3D volume reconstruction model for volume rendering and apply this model to abdominal CT data. The model development includes two steps: (1) interpolation of given data for a complete 3D model, and (2) visualization. First, CT slices are interpolated using a special morphing algorithm. The main idea of this algorithm is to take a region from one CT slice and locate its most probable correspondence in the adjacent CT slice. The algorithm determines the transformation function of the region in between two adjacent CT slices and interpolates the data accordingly. The most probable correspondence of a region is obtained using correlation analysis between the given region and regions of the adjacent CT slice. By applying this technique recursively, taking progressively smaller subregions within a region, a high quality and accuracy interpolation is obtained. The main advantages of this morphing algorithm are 1) its applicability not only to parallel planes like CT slices but also to general configurations of planes in 3D space, and 2) its fully automated nature as it does not require control points to be specified by a user compared to most morphing techniques. Subsequently, to visualize data, a specialized volume rendering card (TeraRecon VolumePro 1000) was used. To represent data in 3D space, special software was developed to convert interpolated CT slices to 3D objects compatible with the VolumePro card. Visual comparison between the proposed model and linear interpolation clearly demonstrates the superiority of the proposed model.

  14. Tight-frame based iterative image reconstruction for spectral breast CT

    PubMed Central

    Zhao, Bo; Gao, Hao; Ding, Huanjun; Molloi, Sabee

    2013-01-01

    Purpose: To investigate tight-frame based iterative reconstruction (TFIR) technique for spectral breast computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The experimental data were acquired with a fan-beam breast CT system based on a cadmium zinc telluride photon-counting detector. The images were reconstructed with a varying number of projections using the TFIR and filtered backprojection (FBP) techniques. The image quality between these two techniques was evaluated. The image's spatial resolution was evaluated using a high-resolution phantom, and the contrast to noise ratio (CNR) was evaluated using a postmortem breast sample. The postmortem breast samples were decomposed into water, lipid, and protein contents based on images reconstructed from TFIR with 204 projections and FBP with 614 projections. The volumetric fractions of water, lipid, and protein from the image-based measurements in both TFIR and FBP were compared to the chemical analysis. Results: The spatial resolution and CNR were comparable for the images reconstructed by TFIR with 204 projections and FBP with 614 projections. Both reconstruction techniques provided accurate quantification of water, lipid, and protein composition of the breast tissue when compared with data from the reference standard chemical analysis. Conclusions: Accurate breast tissue decomposition can be done with three fold fewer projection images by the TFIR technique without any reduction in image spatial resolution and CNR. This can result in a two-third reduction of the patient dose in a multislit and multislice spiral CT system in addition to the reduced scanning time in this system. PMID:23464320

  15. Radiation Dose Consideration in Kidney Stone CT Examinations: Integration of Iterative Reconstruction Algorithms With Routine Clinical Practice.

    PubMed

    Andrabi, Yasir; Pianykh, Oleg; Agrawal, Mukta; Kambadakone, Avinash; Blake, Michael A; Sahani, Dushyant V

    2015-05-01

    The objective of our study was to evaluate three commercially available iterative reconstruction (IR) algorithms-ASiR, iDOSE, and SAFIRE-and conventional filtered back projection (FBP) on image quality and radiation dose in kidney stone CT examinations. During the 6-month study period, 684 unenhanced kidney stone CT examinations of consecutive adults were performed on 17 CT scanners (GE Healthcare [vendor 1], n = 12 scanners; Philips Healthcare [vendor 2], n = 2; Siemens Health-care [vendor 3], n = 3); these examinations were retrieved using dose-monitoring software (eXposure). A total of 347 kidney stone CT examinations were reconstructed using FBP, and 337 examinations were processed using IR (ASiR, n = 248; iDOSE, n = 50; SAFIRE, n = 39). The standard-dose scanning parameters for FBP scanners included a tube potential of 120 kVp, a tube current of 75-450 mA for vendor 1 and a Quality Reference mAs of 160-180 for vendor 3, and a slice thickness of 2.5 or 5 mm. The dose-modified protocol for the IR scanners included a higher noise index (1.4 times higher than the standard-dose FBP protocol) for vendor 1, a lower reference tube current-exposure time product for vendor 2 (150 reference mAs), and a lower Quality Reference mAs for vendor 3 (120 Quality Reference mAs). Three radiologists independently reviewed 60 randomly sampled kidney stone CT examinations for image quality, noise, and artifacts. Objective noise and attenuation were also determined. Size-specific dose estimates (SSDEs) were compared using ANOVA. Significantly higher subjective and objective measurements of image noise were found in FBP examinations compared with dose-modified IR examinations (p < 0.05). The radiation dose was substantially lower for the dose-modified IR examinations than the standard-dose FBP examinations (mean SSDE ± SD: 8.1 ± 3.8 vs 11.6 ± 3.6 mGy, respectively) (p < 0.0001), but the radiation dose was comparable among the three IR techniques (ASiR, 7.8 ± 3.1 mGy; iDOSE, 7.5

  16. Parameter space visualizer: an interactive parameter selection interface for iterative CT reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Xu, Wei; Mueller, Klaus

    2010-02-01

    Previous work indicated that using ordered subsets (OS-SIRT) for iterative CT can optimize the reconstruction performance once optimal settings for parameters such as number of subsets and relaxation factor have been identified. However, recent work also indicated that the optimal settings have dependent relations with regards to the quality of the projection data (such as SNR-level), which are hard to obtain a-priori. In addition, users may also have preferences in trading off between the dependent parameters, such as reconstruction speed and quality, which makes these (independent) parameters even more difficult to determine in an automated manner. Therefore, we devise an effective parameter space navigation interface allowing users to interactively assist parameter selection for iterative CT reconstruction algorithms (here for OS-SIRT). It is based on a 2D scatter plot with six display modes to show different features of the reconstruction results based on the user preferences. It also enables a dynamic visualization by gradual parameter alteration for illustrating the rate of impact of a given parameter constellation. Finally, we note the generality of our approach, which could be applied to assist any parameter selection related systems.

  17. SART-Type Half-Threshold Filtering Approach for CT Reconstruction

    PubMed Central

    YU, HENGYONG; WANG, GE

    2014-01-01

    The ℓ1 regularization problem has been widely used to solve the sparsity constrained problems. To enhance the sparsity constraint for better imaging performance, a promising direction is to use the ℓp norm (0 < p < 1) and solve the ℓp minimization problem. Very recently, Xu et al. developed an analytic solution for the ℓ1∕2 regularization via an iterative thresholding operation, which is also referred to as half-threshold filtering. In this paper, we design a simultaneous algebraic reconstruction technique (SART)-type half-threshold filtering framework to solve the computed tomography (CT) reconstruction problem. In the medical imaging filed, the discrete gradient transform (DGT) is widely used to define the sparsity. However, the DGT is noninvertible and it cannot be applied to half-threshold filtering for CT reconstruction. To demonstrate the utility of the proposed SART-type half-threshold filtering framework, an emphasis of this paper is to construct a pseudoinverse transforms for DGT. The proposed algorithms are evaluated with numerical and physical phantom data sets. Our results show that the SART-type half-threshold filtering algorithms have great potential to improve the reconstructed image quality from few and noisy projections. They are complementary to the counterparts of the state-of-the-art soft-threshold filtering and hard-threshold filtering. PMID:25530928

  18. Optimisation of reconstruction for the registration of CT liver perfusion sequences

    NASA Astrophysics Data System (ADS)

    Romain, B.; Letort, V.; Lucidarme, O.; d'Alché-Buc, F.; Rouet, L.

    2012-02-01

    Objective. CT abdominal perfusion is frequently used to evaluate tumor evolution when patients are undergoing antiangiogenic therapy. Parameters depending on longer-term dynamics of the diffusion of the contrast medium (e. g. permeability) could help assessing the treatment efficacy. To this end, dynamic image sequences are obtained while patients breath freely. Prior to any analysis, one needs to compensate the respiratory motion. The goal of our study is to optimize the CT reconstruction parameters (filter of reconstruction, thickness of image volumes) for our registration method. We also aim at proposing relevant criteria allowing to quantify the registration quality. Methods. Registration is computed in 4 steps: z-global rigid registration, local refinements with multiresolution blockmatching, regularization and warping. Two new criteria are defined to evaluate the quality of registration: one for spatial evaluation and the other for temporal evaluation. Results. The two measures decrease after registration (58% and 10% average decrease for the best reconstruction parameters for the spatial and temporal criteria respectively) which is consistent with visual inspection of the images. They are therefore used to determine the best combination of reconstruction parameters.

  19. Joint Reconstruction of Multi-channel, Spectral CT Data via Constrained Total Nuclear Variation Minimization

    PubMed Central

    La Rivière, Patrick J.

    2015-01-01

    We explore the use of the recently proposed “total nuclear variation” (TVN) as a regularizer for reconstructing multi-channel, spectral CT images. This convex penalty is a natural extension of the total variation (TV) to vector-valued images and has the advantage of encouraging common edge locations and a shared gradient direction among image channels. We show how it can be incorporated into a general, data-constrained reconstruction framework and derive update equations based on the first-order, primal-dual algorithm of Chambolle and Pock. Early simulation studies based on the numerical XCAT phantom indicate that the inter-channel coupling introduced by the TVN leads to better preservation of image features at high levels of regularization, compared to independent, channel-by-channel TV reconstructions. PMID:25658985

  20. Convex-hull mass estimates of the dodo (Raphus cucullatus): application of a CT-based mass estimation technique

    PubMed Central

    O’Mahoney, Thomas G.; Kitchener, Andrew C.; Manning, Phillip L.; Sellers, William I.

    2016-01-01

    The external appearance of the dodo (Raphus cucullatus, Linnaeus, 1758) has been a source of considerable intrigue, as contemporaneous accounts or depictions are rare. The body mass of the dodo has been particularly contentious, with the flightless pigeon alternatively reconstructed as slim or fat depending upon the skeletal metric used as the basis for mass prediction. Resolving this dichotomy and obtaining a reliable estimate for mass is essential before future analyses regarding dodo life history, physiology or biomechanics can be conducted. Previous mass estimates of the dodo have relied upon predictive equations based upon hind limb dimensions of extant pigeons. Yet the hind limb proportions of dodo have been found to differ considerably from those of their modern relatives, particularly with regards to midshaft diameter. Therefore, application of predictive equations to unusually robust fossil skeletal elements may bias mass estimates. We present a whole-body computed tomography (CT) -based mass estimation technique for application to the dodo. We generate 3D volumetric renders of the articulated skeletons of 20 species of extant pigeons, and wrap minimum-fit ‘convex hulls’ around their bony extremities. Convex hull volume is subsequently regressed against mass to generate predictive models based upon whole skeletons. Our best-performing predictive model is characterized by high correlation coefficients and low mean squared error (a = − 2.31, b = 0.90, r2 = 0.97, MSE = 0.0046). When applied to articulated composite skeletons of the dodo (National Museums Scotland, NMS.Z.1993.13; Natural History Museum, NHMUK A.9040 and S/1988.50.1), we estimate eviscerated body masses of 8–10.8 kg. When accounting for missing soft tissues, this may equate to live masses of 10.6–14.3 kg. Mass predictions presented here overlap at the lower end of those previously published, and support recent suggestions of a relatively slim dodo. CT-based reconstructions provide a

  1. Convex-hull mass estimates of the dodo (Raphus cucullatus): application of a CT-based mass estimation technique.

    PubMed

    Brassey, Charlotte A; O'Mahoney, Thomas G; Kitchener, Andrew C; Manning, Phillip L; Sellers, William I

    2016-01-01

    The external appearance of the dodo (Raphus cucullatus, Linnaeus, 1758) has been a source of considerable intrigue, as contemporaneous accounts or depictions are rare. The body mass of the dodo has been particularly contentious, with the flightless pigeon alternatively reconstructed as slim or fat depending upon the skeletal metric used as the basis for mass prediction. Resolving this dichotomy and obtaining a reliable estimate for mass is essential before future analyses regarding dodo life history, physiology or biomechanics can be conducted. Previous mass estimates of the dodo have relied upon predictive equations based upon hind limb dimensions of extant pigeons. Yet the hind limb proportions of dodo have been found to differ considerably from those of their modern relatives, particularly with regards to midshaft diameter. Therefore, application of predictive equations to unusually robust fossil skeletal elements may bias mass estimates. We present a whole-body computed tomography (CT) -based mass estimation technique for application to the dodo. We generate 3D volumetric renders of the articulated skeletons of 20 species of extant pigeons, and wrap minimum-fit 'convex hulls' around their bony extremities. Convex hull volume is subsequently regressed against mass to generate predictive models based upon whole skeletons. Our best-performing predictive model is characterized by high correlation coefficients and low mean squared error (a = - 2.31, b = 0.90, r (2) = 0.97, MSE = 0.0046). When applied to articulated composite skeletons of the dodo (National Museums Scotland, NMS.Z.1993.13; Natural History Museum, NHMUK A.9040 and S/1988.50.1), we estimate eviscerated body masses of 8-10.8 kg. When accounting for missing soft tissues, this may equate to live masses of 10.6-14.3 kg. Mass predictions presented here overlap at the lower end of those previously published, and support recent suggestions of a relatively slim dodo. CT-based reconstructions provide a means of

  2. TU-A-12A-07: CT-Based Biomarkers to Characterize Lung Lesion: Effects of CT Dose, Slice Thickness and Reconstruction Algorithm Based Upon a Phantom Study

    SciTech Connect

    Zhao, B; Tan, Y; Tsai, W; Lu, L; Schwartz, L; So, J; Goldman, J; Lu, Z

    2014-06-15

    Purpose: Radiogenomics promises the ability to study cancer tumor genotype from the phenotype obtained through radiographic imaging. However, little attention has been paid to the sensitivity of image features, the image-based biomarkers, to imaging acquisition techniques. This study explores the impact of CT dose, slice thickness and reconstruction algorithm on measuring image features using a thorax phantom. Methods: Twentyfour phantom lesions of known volume (1 and 2mm), shape (spherical, elliptical, lobular and spicular) and density (-630, -10 and +100 HU) were scanned on a GE VCT at four doses (25, 50, 100, and 200 mAs). For each scan, six image series were reconstructed at three slice thicknesses of 5, 2.5 and 1.25mm with continuous intervals, using the lung and standard reconstruction algorithms. The lesions were segmented with an in-house 3D algorithm. Fifty (50) image features representing lesion size, shape, edge, and density distribution/texture were computed. Regression method was employed to analyze the effect of CT dose, slice of thickness and reconstruction algorithm on these features adjusting 3 confounding factors (size, density and shape of phantom lesions). Results: The coefficients of CT dose, slice thickness and reconstruction algorithm are presented in Table 1 in the supplementary material. No significant difference was found between the image features calculated on low dose CT scans (25mAs and 50mAs). About 50% texture features were found statistically different between low doses and high doses (100 and 200mAs). Significant differences were found for almost all features when calculated on 1.25mm, 2.5mm, and 5mm slice thickness images. Reconstruction algorithms significantly affected all density-based image features, but not morphological features. Conclusions: There is a great need to standardize the CT imaging protocols for radiogenomics study because CT dose, slice thickness and reconstruction algorithm impact quantitative image features to

  3. PItcHPERFeCT: Primary Intracranial Hemorrhage Probability Estimation using Random Forests on CT.

    PubMed

    Muschelli, John; Sweeney, Elizabeth M; Ullman, Natalie L; Vespa, Paul; Hanley, Daniel F; Crainiceanu, Ciprian M

    2017-01-01

    Intracerebral hemorrhage (ICH), where a blood vessel ruptures into areas of the brain, accounts for approximately 10-15% of all strokes. X-ray computed tomography (CT) scanning is largely used to assess the location and volume of these hemorrhages. Manual segmentation of the CT scan using planimetry by an expert reader is the gold standard for volume estimation, but is time-consuming and has within- and across-reader variability. We propose a fully automated segmentation approach using a random forest algorithm with features extracted from X-ray computed tomography (CT) scans. The Minimally Invasive Surgery plus rt-PA in ICH Evacuation (MISTIE) trial was a multi-site Phase II clinical trial that tested the safety of hemorrhage removal using recombinant-tissue plasminogen activator (rt-PA). For this analysis, we use 112 baseline CT scans from patients enrolled in the MISTE trial, one CT scan per patient. ICH was manually segmented on these CT scans by expert readers. We derived a set of imaging predictors from each scan. Using 10 randomly-selected scans, we used a first-pass voxel selection procedure based on quantiles of a set of predictors and then built 4 models estimating the voxel-level probability of ICH. The models used were: 1) logistic regression, 2) logistic regression with a penalty on the model parameters using LASSO, 3) a generalized additive model (GAM) and 4) a random forest classifier. The remaining 102 scans were used for model validation.For each validation scan, the model predicted the probability of ICH at each voxel. These voxel-level probabilities were then thresholded to produce binary segmentations of the hemorrhage. These masks were compared to the manual segmentations using the Dice Similarity Index (DSI) and the correlation of hemorrhage volume of between the two segmentations. We tested equality of median DSI using the Kruskal-Wallis test across the 4 models. We tested equality of the median DSI from sets of 2 models using a Wilcoxon

  4. Cardiac PET/CT with Rb-82: optimization of image acquisition and reconstruction parameters.

    PubMed

    Chilra, P; Gnesin, S; Allenbach, G; Monteiro, M; Prior, J O; Vieira, L; Pires Jorge, J A

    2017-12-01

    Our aim was to characterize the influence of time-of-flight (TOF) and point spread function (PSF) recovery corrections, as well as ordered subset expectation maximization (OSEM) reconstruction parameters, in (82)Rb PET/CT quantification of myocardial blood flow (MBF) and myocardial flow reserve (MFR). Rest and stress list-mode dynamic (82)Rb PET acquisition data from 10 patients without myocardial flow defects and 10 patients with myocardial blood flow defects were reconstructed retrospectively. OSEM reconstructions were performed with Gaussian filters of 4, 6, and 8 mm, different iterations, and subset numbers (2 × 24; 2 × 16; 3 × 16; 4 × 16). Rest and stress global, regional, and segmental MBF and MFR were computed from time activity curves with FlowQuant(©) software. Left ventricular segmentation using the 17-segment American Heart Association model was obtained. Whole left ventricle (LV) MBF at rest and stress were 0.97 ± 0.30 and 2.30 ± 1.00 mL/min/g, respectively, and MFR was 2.40 ± 1.13. Concordance was excellent and all reconstruction parameters had no significant impact on MBF, except for the exclusion of TOF which led to significantly decreased concordance in rest and stress MBF in patients with or without perfusion defects on a coronary artery basis and in MFR in patients with perfusion defects. Changes in reconstruction parameters in perfusion (82)Rb PET/CT studies influence quantitative MBF analysis. The inclusion of TOF information in the tomographic reconstructions had significant impact in MBF quantification.

  5. Automatic selection of an optimal systolic and diastolic reconstruction windows for dual-source CT coronary angiography

    NASA Astrophysics Data System (ADS)

    Seifarth, H.; Puesken, M.; Wienbeck, S.; Maintz, D.; Heindel, W.; Juergens, K.-U.

    2008-03-01

    Purpose: To assess the performance of a motion map algorithm to automatically determine the optimal systolic and diastolic reconstruction window for coronary CT Angiography using Dual Source CT. Materials and Methods: Dual Source coronary CT angiography data sets (Somatom Definition, Siemens Medical Solutions) from 50 consecutive patients were included in the analysis. Optimal systolic and diastolic reconstruction windows were determined using a motion map algorithm (BestPhase, Siemens Medical Solutions). Additionally data sets were reconstructed in 5% steps throughout the RR-interval. For each major vessel (RCA, LAD and LCX) an optimal systolic and diastolic reconstruction window was manually determined by two independent readers using volume rendering displays. Image quality was rated using a five-point scale (1 = no motion artifacts, 5 = severe motion artifacts over entire length of the vessel). Results: The mean heart rate during the scan was 72.4bpm (+/-15.8bpm). Median systolic and diastolic reconstruction windows using the BestPhase algorithm were at 37% and 73% RR. The median manually selected systolic reconstruction window was 35 %, 30% and 35% for RCA, LAD, and LCX. For all vessels the median observer selected diastolic reconstruction window was 75%. Mean image quality using the BestPhase algorithm was 2.4 +/-0.9 for systolic reconstructions and 1.9 +/-1.1 for diastolic reconstructions. Using the manual approach, the mean image quality was 1.9 +/-0.5 and 1.7 +/-0.8 respectively. There was a significant difference in image quality between automatically and manually determined systolic reconstructions (p<0.01) but there was no significant difference in image quality in diastolic reconstructions. Conclusion: Automatic determination of the optimal reconstruction interval using the BestPhase algorithm is feasible and yields reconstruction windows similar to observer selected reconstruction windows. In diastolic reconstructions overall image quality is similar

  6. Quantitative image reconstruction for dual-isotope parathyroid SPECT/CT: phantom experiments and sample patient studies

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Chamoiseau, S.; Celler, A.

    2012-08-01

    We investigated the quantitative accuracy of the model-based dual-isotope single-photon emission computed tomography (DI-SPECT) reconstructions that use Klein-Nishina expressions to estimate the scattered photon contributions to the projection data. Our objective was to examine the ability of the method to recover the absolute activities pertaining to both radiotracers: Tc-99m and I-123. We validated our method through a series of phantom experiments performed using a clinical hybrid SPECT/CT camera (Infinia Hawkeye, GE Healthcare). Different activity ratios and different attenuating media were used in these experiments to create cross-talk effects of varying severity, which can occur in clinical studies. Accurate model-based corrections for scatter and cross-talk with CT attenuation maps allowed for the recovery of the absolute activities from DI-SPECT/CT scans with errors that ranged 0-10% for both radiotracers. The unfavorable activity ratios increased the computational burden but practically did not affect the resulting accuracy. The visual analysis of parathyroid patient data demonstrated that our model-based processing improved adenoma/background contrast and enhanced localization of small or faint adenomas.

  7. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    SciTech Connect

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-07-15

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  8. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    PubMed Central

    Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.; Raval, Amish N.; Van Lysel, Michael S.; Speidel, Michael A.

    2014-01-01

    Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937

  9. SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

    SciTech Connect

    Wu, P; Mao, T; Gong, S; Wang, J; Niu, T; Sheng, K; Xie, Y

    2016-06-15

    Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimization trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R

  10. Reconstruction of a cone-beam CT image via forward iterative projection matching

    SciTech Connect

    Brock, R. Scott; Docef, Alen; Murphy, Martin J.

    2010-12-15

    Purpose: To demonstrate the feasibility of reconstructing a cone-beam CT (CBCT) image by deformably altering a prior fan-beam CT (FBCT) image such that it matches the anatomy portrayed in the CBCT projection data set. Methods: A prior FBCT image of the patient is assumed to be available as a source image. A CBCT projection data set is obtained and used as a target image set. A parametrized deformation model is applied to the source FBCT image, digitally reconstructed radiographs (DRRs) that emulate the CBCT projection image geometry are calculated and compared to the target CBCT projection data, and the deformation model parameters are adjusted iteratively until the DRRs optimally match the CBCT projection data set. The resulting deformed FBCT image is hypothesized to be an accurate representation of the patient's anatomy imaged by the CBCT system. The process is demonstrated via numerical simulation. A known deformation is applied to a prior FBCT image and used to create a synthetic set of CBCT target projections. The iterative projection matching process is then applied to reconstruct the deformation represented in the synthetic target projections; the reconstructed deformation is then compared to the known deformation. The sensitivity of the process to the number of projections and the DRR/CBCT projection mismatch is explored by systematically adding noise to and perturbing the contrast of the target projections relative to the iterated source DRRs and by reducing the number of projections. Results: When there is no noise or contrast mismatch in the CBCT projection images, a set of 64 projections allows the known deformed CT image to be reconstructed to within a nRMS error of 1% and the known deformation to within a nRMS error of 7%. A CT image nRMS error of less than 4% is maintained at noise levels up to 3% of the mean projection intensity, at which the deformation error is 13%. At 1% noise level, the number of projections can be reduced to 8 while maintaining

  11. Analytical cone-beam reconstruction using a multi-source inverse geometry CT system

    NASA Astrophysics Data System (ADS)

    Yin, Zhye; De Man, Bruno; Pack, Jed

    2007-03-01

    In a 3rd generation CT system, a single source projects the entire field of view (FOV) onto a large detector opposite the source. In multi-source CT imaging, a multitude of sources sequentially project a part of the FOV on a much smaller detector. These sources may be distributed in both the trans-axial and axial directions in order to jointly cover the entire FOV. Scan data from multiple sources in the axial direction provide complementary information, which is not available in a conventional single-source CT system. In this work, an analytical 3D cone-beam reconstruction algorithm for multi-source CT is proposed. This approach has three distinctive features. First, multi-source data are re-binned transaxially to multiple offset third-generation datasets. Second, data points in sinograms from multiple source sets are either accepted or rejected for contribution to the backprojection of a given voxel. Third, instead of using a ramp filter, a Hilbert transform is combined with a parallel derivative to form the filtering mechanism. Phantom simulations are performed using a multi-source CT geometry and compared to conventional 3rd generation CT geometry. We show that multi-source CT can extend the axial scan coverage to 120mm without cone-beam artifacts, while a third-generation geometry results in compromised image quality at 60mm of axial coverage. Moreover, given that the cone-angle in the proposed geometry is limited to 7 degrees, there are no degrading effects such as the Heel effect and scattered radiation, unlike in a third-generation geometry with comparable coverage. An additional benefit is the uniform flux profile resulting in uniform image noise throughout the FOV and a uniform dose absorption profile.

  12. Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

    SciTech Connect

    Li, Ke; Tang, Jie; Chen, Guang-Hong

    2014-04-15

    Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial

  13. Estimation of the firing distance through micro-CT analysis of gunshot wounds.

    PubMed

    Cecchetto, Giovanni; Giraudo, Chiara; Amagliani, Alessandro; Viel, Guido; Fais, Paolo; Cavarzeran, Fabiano; Feltrin, Giampietro; Ferrara, Santo Davide; Montisci, Massimo

    2011-03-01

    Estimation of the firing range is often critical for reconstructing gunshot fatalities, where the main measurable evidence is the gunshot residue (GSR). In the present study intermediate-range gunshot wounds have been analysed by means of a micro-computed tomography (micro-CT) coupled to an image analysis software in order to quantify the powder particles and to determine the firing distance. A total of 50 shootings were performed on skin sections obtained from human legs surgically amputated for medical reasons. For each tested distance (5, 15, 23, 30 and 40 cm), firing was carried out perpendicularly at the samples using a 7.65-mm pistol loaded with jacketed bullets. Uninjured skin sections were used as controls. By increasing the firing distance, micro-CT analysis demonstrated a clear decreasing trend in the mean GSR percentage, particularly for shots fired from more than 15 cm. For distances under 23 cm, the powder particles were concentrated on the epidermis and dermis around the hole, and inside the cavity; while, at greater distances, they were deposited only on the skin surface. Statistical analysis showed a nonlinear relationship between the amount of GSR deposits and the firing range, well explained by a Gaussian-like function. The proposed method allowed a good discrimination for all the tested distances, proving to be an objective, rapid and inexpensive tool for estimating the firing range in intermediate-range gunshot wounds.

  14. Impact of PET/CT image reconstruction methods and liver uptake normalization strategies on quantitative image analysis.

    PubMed

    Kuhnert, Georg; Boellaard, Ronald; Sterzer, Sergej; Kahraman, Deniz; Scheffler, Matthias; Wolf, Jürgen; Dietlein, Markus; Drzezga, Alexander; Kobe, Carsten

    2016-02-01

    In oncological imaging using PET/CT, the standardized uptake value has become the most common parameter used to measure tracer accumulation. The aim of this analysis was to evaluate ultra high definition (UHD) and ordered subset expectation maximization (OSEM) PET/CT reconstructions for their potential impact on quantification. We analyzed 40 PET/CT scans of lung cancer patients who had undergone PET/CT. Standardized uptake values corrected for body weight (SUV) and lean body mass (SUL) were determined in the single hottest lesion in the lung and normalized to the liver for UHD and OSEM reconstruction. Quantitative uptake values and their normalized ratios for the two reconstruction settings were compared using the Wilcoxon test. The distribution of quantitative uptake values and their ratios in relation to the reconstruction method used were demonstrated in the form of frequency distribution curves, box-plots and scatter plots. The agreement between OSEM and UHD reconstructions was assessed through Bland-Altman analysis. A significant difference was observed after OSEM and UHD reconstruction for SUV and SUL data tested (p < 0.0005 in all cases). The mean values of the ratios after OSEM and UHD reconstruction showed equally significant differences (p < 0.0005 in all cases). Bland-Altman analysis showed that the SUV and SUL and their normalized values were, on average, up to 60 % higher after UHD reconstruction as compared to OSEM reconstruction. OSEM and HD reconstruction brought a significant difference for SUV and SUL, which remained constantly high after normalization to the liver, indicating that standardization of reconstruction and the use of comparable SUV measurements are crucial when using PET/CT.

  15. Robust image reconstruction enhancement based on Gaussian mixture model estimation

    NASA Astrophysics Data System (ADS)

    Zhao, Fan; Zhao, Jian; Han, Xizhen; Wang, He; Liu, Bochao

    2016-03-01

    The low quality of an image is often characterized by low contrast and blurred edge details. Gradients have a direct relationship with image edge details. More specifically, the larger the gradients, the clearer the image details become. Robust image reconstruction enhancement based on Gaussian mixture model estimation is proposed here. First, image is transformed to its gradient domain, obtaining the gradient histogram. Second, the gradient histogram is estimated and extended using a Gaussian mixture model, and the predetermined function is constructed. Then, using histogram specification technology, the gradient field is enhanced with the constraint of the predetermined function. Finally, a matrix sine transform-based method is applied to reconstruct the enhanced image from the enhanced gradient field. Experimental results show that the proposed algorithm can effectively enhance different types of images such as medical image, aerial image, and visible image, providing high-quality image information for high-level processing.

  16. Estimation of Observer Performance for Reduced Radiation Dose Levels in CT: Eliminating Reduced Dose Levels That Are Too Low Is the First Step.

    PubMed

    Fletcher, Joel G; Yu, Lifeng; Fidler, Jeff L; Levin, David L; DeLone, David R; Hough, David M; Takahashi, Naoki; Venkatesh, Sudhakar K; Sykes, Anne-Marie G; White, Darin; Lindell, Rebecca M; Kotsenas, Amy L; Campeau, Norbert G; Lehman, Vance T; Bartley, Adam C; Leng, Shuai; Holmes, David R; Toledano, Alicia Y; Carter, Rickey E; McCollough, Cynthia H

    2017-07-01

    This study aims to estimate observer performance for a range of dose levels for common computed tomography (CT) examinations (detection of liver metastases or pulmonary nodules, and cause of neurologic deficit) to prioritize noninferior dose levels for further analysis. Using CT data from 131 examinations (abdominal CT, 44; chest CT, 44; head CT, 43), CT images corresponding to 4%-100% of the routine clinical dose were reconstructed with filtered back projection or iterative reconstruction. Radiologists evaluated CT images, marking specified targets, providing confidence scores, and grading image quality. Noninferiority was assessed using reference standards, reader agreement rules, and jackknife alternative free-response receiver operating characteristic figures of merit. Reader agreement required that a majority of readers at lower dose identify target lesions seen by the majority of readers at routine dose. Reader agreement identified dose levels lower than 50% and 4% to have inadequate performance for detection of hepatic metastases and pulmonary nodules, respectively, but could not exclude any low dose levels for head CT. Estimated differences in jackknife alternative free-response receiver operating characteristic figures of merit between routine and lower dose configurations found that only the lowest dose configurations tested (ie, 30%, 4%, and 10% of routine dose levels for abdominal, chest, and head CT examinations, respectively) did not meet criteria for noninferiority. At lower doses, subjective image quality declined before observer performance. Iterative reconstruction was only beneficial when filtered back projection did not result in noninferior performance. Opportunity exists for substantial radiation dose reduction using existing CT technology for common diagnostic tasks. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  17. Patient-specific dose estimation for pediatric chest CT

    PubMed Central

    Li, Xiang; Samei, Ehsan; Segars, W. Paul; Sturgeon, Gregory M.; Colsher, James G.; Frush, Donald P.

    2008-01-01

    Current methods for organ and effective dose estimations in pediatric CT are largely patient generic. Physical phantoms and computer models have only been developed for standard/limited patient sizes at discrete ages (e.g., 0, 1, 5, 10, 15years old) and do not reflect the variability of patient anatomy and body habitus within the same size/age group. In this investigation, full-body computer models of seven pediatric patients in the same size/protocol group (weight: 11.9–18.2kg) were created based on the patients’ actual multi-detector array CT (MDCT) data. Organs and structures in the scan coverage were individually segmented. Other organs and structures were created by morphing existing adult models (developed from visible human data) to match the framework defined by the segmented organs, referencing the organ volume and anthropometry data in ICRP Publication 89. Organ and effective dose of these patients from a chest MDCT scan protocol (64 slice LightSpeed VCT scanner, 120kVp, 70 or 75mA, 0.4s gantry rotation period, pitch of 1.375, 20mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated to simulate radiation transport in the same CT system. The seven patients had normalized effective dose of 3.7–5.3mSv∕100mAs (coefficient of variation: 10.8%). Normalized lung dose and heart dose were 10.4–12.6mGy∕100mAs and 11.2–13.3mGy∕100mAs, respectively. Organ dose variations across the patients were generally small for large organs in the scan coverage (<7%), but large for small organs in the scan coverage (9%–18%) and for partially or indirectly exposed organs (11%–77%). Normalized effective dose correlated weakly with body weight (correlation coefficient:r=−0.80). Normalized lung dose and heart dose correlated strongly with mid-chest equivalent diameter (lung: r=−0.99, heart: r=−0.93); these strong correlation relationships can be used to estimate patient

  18. Global near-surface temperature estimation using statistical reconstruction techniques

    NASA Astrophysics Data System (ADS)

    Morice, C. P.; Rayner, N. A.; Kennedy, J.

    2015-12-01

    Incomplete and non-uniform observational coverage of the globe is a prominent source of uncertainty in instrumental records of global near-surface temperature change. In this study the capabilities of a range of statistical analysis methods are assessed in producing improved estimates of global near-surface temperature change since the mid 19th century for observational coverage in the HadCRUT4 data set. Methods used include those that interpolate according to local correlation structure (kriging) and reduced space methods that learn large-scale temperature patterns. The performance of each method in estimating regional and global temperature changes has been benchmarked in application to a subset of CMIP5 simulations. Model fields are sub-sampled and simulated observational errors added to emulate observational data, permitting assessment of temperature field reconstruction algorithms in controlled tests in which globally complete temperature fields are known. The reconstruction methods have also been applied to the HadCRUT4 data set, yielding a range of estimates of global near-surface temperature change since the mid 19th century. Results show relatively increased warming in the global average over the 21st century owing to reconstruction of temperatures in high northern latitudes, supporting the findings of Cowtan & Way (2014) and Karl et al. (2015). While there is broad agreement between estimates of global and hemispheric changes throughout much of the 20th and 21st century, agreement is reduced in the 19th and early 20th century. This finding is supported by the climate model trials that highlight uncertainty in reconstructing data sparse regions, most notably in the Southern Hemisphere in the 19th century. These results underline the importance of continued data rescue activities, such as those of the International Surface Temperature Initiative and ACRE. The results of this study will form an addition to the HadCRUT4 global near-surface temperature data

  19. Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods

    SciTech Connect

    Chen, Baiyu; Christianson, Olav; Wilson, Joshua M.; Samei, Ehsan

    2014-07-15

    Purpose: For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. Methods: The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPS{sub task}). The in-plane resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPS{sub task} is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precision of the methodology, images of known noise and resolution properties were simulated. The NPS{sub task} and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPS{sub task} and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). Results: To achieve NPS{sub task} measurements with <10% error, the

  20. A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

    SciTech Connect

    Yan, Hao; Folkerts, Michael; Jiang, Steve B. E-mail: steve.jiang@UTSouthwestern.edu; Jia, Xun E-mail: steve.jiang@UTSouthwestern.edu; Zhen, Xin; Li, Yongbao; Pan, Tinsu; Cervino, Laura

    2014-07-15

    Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase

  1. Three-dimensional focus of attention for iterative cone-beam micro-CT reconstruction

    NASA Astrophysics Data System (ADS)

    Benson, T. M.; Gregor, J.

    2006-09-01

    Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts of computer cycles and associated memory. In this paper, we show that the computational burden can be reduced by limiting the reconstruction to a small, well-defined portion of the image volume. We first discuss using the support region defined by the set of voxels covered by all of the projection views. We then present a data-driven preprocessing technique called focus of attention that heuristically separates both image and projection data into object and background before reconstruction, thereby further reducing the reconstruction region of interest. We present experimental results for both methods based on mouse data and a parallelized implementation of the SIRT algorithm. The computational savings associated with the support region are substantial. However, the results for focus of attention are even more impressive in that only about one quarter of the computer cycles and memory are needed compared with reconstruction of the entire image volume. The image quality is not compromised by either method.

  2. 3D Alternating Direction TV-Based Cone-Beam CT Reconstruction with Efficient GPU Implementation

    PubMed Central

    Cai, Ailong; Zhang, Hanming; Li, Lei; Xi, Xiaoqi; Guan, Min; Li, Jianxin

    2014-01-01

    Iterative image reconstruction (IIR) with sparsity-exploiting methods, such as total variation (TV) minimization, claims potentially large reductions in sampling requirements. However, the computation complexity becomes a heavy burden, especially in 3D reconstruction situations. In order to improve the performance for iterative reconstruction, an efficient IIR algorithm for cone-beam computed tomography (CBCT) with GPU implementation has been proposed in this paper. In the first place, an algorithm based on alternating direction total variation using local linearization and proximity technique is proposed for CBCT reconstruction. The applied proximal technique avoids the horrible pseudoinverse computation of big matrix which makes the proposed algorithm applicable and efficient for CBCT imaging. The iteration for this algorithm is simple but convergent. The simulation and real CT data reconstruction results indicate that the proposed algorithm is both fast and accurate. The GPU implementation shows an excellent acceleration ratio of more than 100 compared with CPU computation without losing numerical accuracy. The runtime for the new 3D algorithm is about 6.8 seconds per loop with the image size of 256 × 256 × 256 and 36 projections of the size of 512 × 512. PMID:25045400

  3. Detection of coronary artery stenosis with sub-milliSievert radiation dose by prospectively ECG-triggered high-pitch spiral CT angiography and iterative reconstruction.

    PubMed

    Yin, Wei-Hua; Lu, Bin; Hou, Zhi-Hui; Li, Nan; Han, Lei; Wu, Yong-Jian; Niu, Hong-Xia; Silverman, Justin R; Nicola De Cecco, Carlo; Schoepf, U Joseph

    2013-11-01

    To evaluate the diagnostic accuracy of sub-milliSievert (mSv) coronary CT angiography (cCTA) using prospectively ECG-triggered high-pitch spiral CT acquisition combined with iterative image reconstruction. Forty consecutive patients (52.9 ± 8.7 years; 30 men) underwent dual-source cCTA using prospectively ECG-triggered high-pitch spiral acquisition. The tube current-time product was set to 50 % of standard-of-care CT examinations. Images were reconstructed with sinogram-affirmed iterative reconstruction. Image quality was scored and diagnostic performance for detection of ≥50 % stenosis was determined with catheter coronary angiography (CCA) as the reference standard. CT was successfully performed in all 40 patients. Of the 601 assessable coronary segments, 543 (90.3 %) had diagnostic image quality. Per-patient sensitivity for detection of ≥50 % stenosis was 95.7 % [95 % confidence interval (CI), 76.0-99.8 %] and specificity was 94.1 % (95 % CI, 69.2-99.7 %). Per-vessel sensitivity was 89.5 % (95 % CI, 77.8-95.6 %) with 93.2 % specificity (95 % CI, 86.0-97.0 %). The area under the receiver-operating characteristic curve on per-patient and per-vessel levels was 0.949 and 0.913. Mean effective dose was 0.58 ± 0.17 mSv. Mean size-specific dose estimate was 3.14 ± 1.15 mGy. High-pitch prospectively ECG-triggered cCTA combined with iterative image reconstruction provides high diagnostic accuracy with a radiation dose below 1 mSv for detection of coronary artery stenosis. • Cardiac CT with sub-milliSievert radiation dose is feasible in many patients • High-pitch spiral CT acquisition with iterative reconstruction detects coronary stenosis accurately. • Iterative reconstruction increases who can benefit from low-radiation cardiac CT.

  4. Performance estimation for threat detection in CT systems

    NASA Astrophysics Data System (ADS)

    Montgomery, Trent; Karl, W. Clem; Castañón, David A.

    2017-05-01

    Detecting the presence of hazardous materials in suitcases and carry-on luggage is an important problem in aviation security. As the set of threats is expanding, there is a corresponding need to increase the capabilities of explosive detection systems to address these threats. However, there is a lack of principled tools for predicting the performance of alternative designs for detection systems. In this paper, we describe an approach for computing bounds on the achievable classification performance of material discrimination systems based on empirical statistics that estimate the f-divergence of the underlying features. Our approach can be used to examine alternative physical observation modalities and measurement configurations, as well as variations in reconstruction and feature extraction algorithms.

  5. Iterative reconstruction of cone-beam CT data on a cluster

    NASA Astrophysics Data System (ADS)

    Benson, Thomas M.; Gregor, Jens

    2007-02-01

    Three-dimensional iterative reconstruction of large CT data sets poses several challenges in terms of the associated computational and memory requirements. In this paper, we present results obtained by implementing a computational framework for reconstructing axial cone-beam CT data using a cluster of inexpensive dualprocessor PCs. In particular, we discuss our parallelization approach, which uses POSIX threads and message passing (MPI) for local and remote load distribution, as well as the interaction of that load distribution with the implementation of ordered subset based algorithms. We also consider a heuristic data-driven 3D focus of attention algorithm that reduces the amount of data that must be considered for many data sets. Furthermore, we present a modification to the SIRT algorithm that reduces the amount of data that must be communicated between processes. Finally, we introduce a method of separating the work in such a way that some computation can be overlapped with the MPI communication thus further reducing the overall run-time. We summarize the performance results using reconstructions of experimental data.

  6. Acceleration of EM-Based 3D CT Reconstruction Using FPGA.

    PubMed

    Choi, Young-Kyu; Cong, Jason

    2016-06-01

    Reducing radiation doses is one of the key concerns in computed tomography (CT) based 3D reconstruction. Although iterative methods such as the expectation maximization (EM) algorithm can be used to address this issue, applying this algorithm to practice is difficult due to the long execution time. Our goal is to decrease this long execution time to an order of a few minutes, so that low-dose 3D reconstruction can be performed even in time-critical events. In this paper we introduce a novel parallel scheme that takes advantage of numerous block RAMs on field-programmable gate arrays (FPGAs). Also, an external memory bandwidth reduction strategy is presented to reuse both the sinogram and the voxel intensity. Moreover, a customized processing engine based on the FPGA is presented to increase overall throughput while reducing the logic consumption. Finally, a hardware and software flow is proposed to quickly construct a design for various CT machines. The complete reconstruction system is implemented on an FPGA-based server-class node. Experiments on actual patient data show that a 26.9 × speedup can be achieved over a 16-thread multicore CPU implementation.

  7. The PRIMA collaboration: Preliminary results in FBP reconstruction of pCT data

    NASA Astrophysics Data System (ADS)

    Vanzi, Eleonora; Bruzzi, Mara; Bucciolini, Marta; Cirrone, G. A. Pablo; Civinini, Carlo; Cuttone, Giacomo; Lo Presti, Domenico; Pallotta, Stefania; Pugliatti, Cristina; Randazzo, Nunzio; Romano, Francesco; Scaringella, Monica; Sipala, Valeria; Stancampiano, Concetta; Talamonti, Cinzia; Zani, Margherita

    2013-12-01

    A first prototype of proton Computed Tomography (pCT) scanner, made of four planes and a calorimeter, has been developed by the PRIMA (PRoton IMAging) Italian collaboration and first results concerning tomographic image reconstruction of experimentally acquired data are discussed in this paper. The Filtered Back-Projection (FBP) algorithm was used to reconstruct projections of a phantom acquired with a 62 MeV proton beam. Image noise and spatial resolution were assessed for different parameters of the filter used, with and without selection strategies on proton directions. A satisfactory image quality (0.88 mm resolution and 2.5% noise) was achieved even when the backprojection line was defined using only the line connecting the impact points on the second and third planes and all the data were used, irrespective of the proton direction and residual energy. Probably due to the specific detector-phantom arrangement used in this experiment and due to the substantial reduction of the number of useful events, cuts on proton directions did not increase the image resolution significantly. The results confirm the good performances of the PRIMA scanner prototype. They also demonstrate that FBP can produce images of sufficient quality to be used for patient positioning and to initialize iterative pCT reconstruction methods.

  8. Low-dose multiphase abdominal CT reconstruction with phase-induced swap prior

    NASA Astrophysics Data System (ADS)

    Selim, Mona; Rashed, Essam A.; Kudo, Hiroyuki

    2016-10-01

    Multiphase abdominal CT is an imaging protocol in which the patient is scanned at different phases before and after the injection of a contrast agent. Reconstructed images with different concentrations of contrast material provide useful information for effective detection of abnormalities. However, several scanning during a short period of time eventually increase the patient radiation dose to a remarkable value up to a risky level. Reducing the patient dose by modulating the x-ray tube current or acquiring the projection data through a small number of views are known to degrade the image quality and reduce the possibility to be useful for diagnosis purpose. In this work, we propose a novel multiphase abdominal CT imaging protocol with patient dose reduction and high image quality. The image reconstruction cost function consists of two terms, namely the data fidelity term and penalty term to enforce the anatomical similarity in successive contrast phase reconstruction. The prior information, named phase-induced swap prior (PISP) is computed using total variation minimization of image acquired from different contrast phases. The new method is evaluated through a simulation study using digital abdominal phantom and real data and results are promising.

  9. Utilizing the Hotelling template as a tool for CT image reconstruction algorithm design

    NASA Astrophysics Data System (ADS)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2012-02-01

    Design of image reconstruction algorithms for CT can be significantly aided by useful metrics of image quality. Useful metrics, however, are difficult to develop due to the high-dimensionality of the CT imaging system, lack of spatial invariance in the imaging system, and a high degree of correlation among the image voxels. Although true task-based evaluation on realistic imaging tasks can be time-consuming, and a given task may be insensitive to the image reconstruction algorithm, task-based metrics can still prove useful in many contexts. For example, model observers that mimic performance of the imaging system on specific tasks can provide a low-dimensional measure of image quality while still accounting for many of the salient properties of the system and object being scanned. In this work, ideal observer performance is computed on a single detection task. The modeled signal for detection is taken to be very small - size on the order of a detector bin - and inspection of the accompanying Hotelling template is suggested. We hypothesize that improved detection on small signals may be sensitive to the reconstruction algorithm. Further, we hypothesize that structurally simple Hotelling templates may correlate with high human observer performance.

  10. A fast CT reconstruction scheme for a general multi-core PC.

    PubMed

    Zeng, Kai; Bai, Erwei; Wang, Ge

    2007-01-01

    Expensive computational cost is a severe limitation in CT reconstruction for clinical applications that need real-time feedback. A primary example is bolus-chasing computed tomography (CT) angiography (BCA) that we have been developing for the past several years. To accelerate the reconstruction process using the filtered backprojection (FBP) method, specialized hardware or graphics cards can be used. However, specialized hardware is expensive and not flexible. The graphics processing unit (GPU) in a current graphic card can only reconstruct images in a reduced precision and is not easy to program. In this paper, an acceleration scheme is proposed based on a multi-core PC. In the proposed scheme, several techniques are integrated, including utilization of geometric symmetry, optimization of data structures, single-instruction multiple-data (SIMD) processing, multithreaded computation, and an Intel C++ compilier. Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. Our scheme achieves a speedup of about 40, which can be further improved by several folds using the latest quad-core processors.

  11. Towards local progression estimation of pulmonary emphysema using CT

    SciTech Connect

    Staring, M. Bakker, M. E.; Shamonin, D. P.; Reiber, J. H. C.; Stoel, B. C.; Stolk, J.

    2014-02-15

    Purpose: Whole lung densitometry on chest CT images is an accepted method for measuring tissue destruction in patients with pulmonary emphysema in clinical trials. Progression measurement is required for evaluation of change in health condition and the effect of drug treatment. Information about the location of emphysema progression within the lung may be important for the correct interpretation of drug efficacy, or for determining a treatment plan. The purpose of this study is therefore to develop and validate methods that enable the local measurement of lung density changes, which requires proper modeling of the effect of respiration on density. Methods: Four methods, all based on registration of baseline and follow-up chest CT scans, are compared. The first naïve method subtracts registered images. The second employs the so-called dry sponge model, where volume correction is performed using the determinant of the Jacobian of the transformation. The third and the fourth introduce a novel adaptation of the dry sponge model that circumvents its constant-mass assumption, which is shown to be invalid. The latter two methods require a third CT scan at a different inspiration level to estimate the patient-specific density-volume slope, where one method employs a global and the other a local slope. The methods were validated on CT scans of a phantom mimicking the lung, where mass and volume could be controlled. In addition, validation was performed on data of 21 patients with pulmonary emphysema. Results: The image registration method was optimized leaving a registration error below half the slice increment (median 1.0 mm). The phantom study showed that the locally adapted slope model most accurately measured local progression. The systematic error in estimating progression, as measured on the phantom data, was below 2 gr/l for a 70 ml (6%) volume difference, and 5 gr/l for a 210 ml (19%) difference, if volume correction was applied. On the patient data an underlying

  12. The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique.

    PubMed

    Kwon, Heejin; Cho, Jinhan; Oh, Jongyeong; Kim, Dongwon; Cho, Junghyun; Kim, Sanghyun; Lee, Sangyun; Lee, Jihyun

    2015-10-01

    To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. 27 consecutive patients (mean body mass index: 23.55 kg m(-2) underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19-49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. This study represents the first clinical research experiment to use ASIR-V, the newest version of

  13. Quantitative SPECT/CT reconstruction for 177Lu and 177Lu/90Y targeted radionuclide therapies

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Piwowarska-Bilska, H.; Celler, A.; Birkenfeld, B.

    2012-09-01

    We investigated the quantitative accuracy of SPECT/CT imaging studies as would be performed before and after targeted radionuclide therapy (TRT) using phantom experiments with (i) 99mTc, (ii) 177Lu and (iii) 90Y/177Lu. While the experiment with 99mTc imitated a diagnostic scan, the experiments with 177Lu and 90Y/177Lu modeled post-therapy acquisitions. At the next stage, we reconstructed images from pre- and post-therapy patient studies. The data were first reconstructed using two methods with limited corrections for the physics effects. Then, to generate quantitatively accurate absolute activity distributions, we applied a hybrid (model-based and window-based) reconstruction strategy where some of the physics effects were accurately modeled while corrections for other effects were empirical and based on information obtained from the projection data. The accuracies of absolute activity recovered by the hybrid method from the six phantom experiments were very similar to each other and acceptable for potential use in TRT. When measured in identical regions of interest, the 99mTc activity was reconstructed with errors ranging between -3.3% and 2.9%, while the 177Lu activity was reconstructed from experiments with 177Lu and 90Y/177Lu with errors ranging between -1.6% and 1.6%. The reconstruction algorithms with limited corrections led to larger and case-specific errors as might have been expected. From a clinical prospective, our results showed that physics-based reconstructions improved resolution of images corresponding to both diagnostic scans with 99mTc and post-therapy scans with 177Lu. Our analysis of patient study demonstrated that lack of corrections led to overestimation of activities in organs and tumor by 29-39% for the diagnostic scan with 99mTc and by 105-218% for post-therapy scan with 177Lu.

  14. A knowledge-based iterative model reconstruction algorithm: can super-low-dose cardiac CT be applicable in clinical settings?

    PubMed

    Oda, Seitaro; Utsunomiya, Daisuke; Funama, Yoshinori; Katahira, Kazuhiro; Honda, Keiichi; Tokuyasu, Shinichi; Vembar, Mani; Yuki, Hideaki; Noda, Katsuo; Oshima, Shuichi; Yamashita, Yasuyuki

    2014-01-01

    To investigate whether "full" iterative reconstruction, a knowledge-based iterative model reconstruction (IMR), enables radiation dose reduction by 80% at cardiac computed tomography (CT). A total of 23 patients (15 men, eight women; mean age 64.3 ± 13.4 years) who underwent retrospectively electrocardiography-gated cardiac CT with dose modulation were evaluated. We compared full-dose (FD; 730 mAs) images reconstructed with filtered back projection (FBP) technique and the low-dose (LD; 146 mAs) images reconstructed with FBP and IMR techniques. Objective and subjective image quality parameters were compared among the three different CT images. There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of LD-IMR (18.3 ± 10.6 Hounsfield units [HU]) was significantly lowest among the three reconstructions (41.9 ± 15.3 HU for FD-FBP and 109.9 ± 42.6 HU for LD-FBP; P < .01). The contrast-to-noise ratio of LD-IMR was better than that of FD-FBP and LD-FBP (P < .01). Visual evaluation score was also highest for LD-IMR. The IMR can provide improved image quality at super-low-dose cardiac CT with 20% of the standard tube current. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  15. Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

    SciTech Connect

    Brady, S. L.; Yee, B. S.; Kaufman, R. A.

    2012-09-15

    Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more

  16. Estimation of food consumption. Hanford Environmental Dose Reconstruction Project

    SciTech Connect

    Callaway, J.M. Jr.

    1992-04-01

    The research reported in this document was conducted as a part of the Hanford Environmental Dose Reconstruction (HEDR) Project. The objective of the HEDR Project is to estimate the radiation doses that people could have received from operations at the Hanford Site. Information required to estimate these doses includes estimates of the amounts of potentially contaminated foods that individuals in the region consumed during the study period. In that general framework, the objective of the Food Consumption Task was to develop a capability to provide information about the parameters of the distribution(s) of daily food consumption for representative groups in the population for selected years during the study period. This report describes the methods and data used to estimate food consumption and presents the results developed for Phase I of the HEDR Project.

  17. Polychromatic sparse image reconstruction and mass attenuation spectrum estimation via B-spline basis function expansion

    SciTech Connect

    Gu, Renliang E-mail: ald@iastate.edu; Dogandžić, Aleksandar E-mail: ald@iastate.edu

    2015-03-31

    We develop a sparse image reconstruction method for polychromatic computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. To obtain a parsimonious measurement model parameterization, we first rewrite the measurement equation using our mass-attenuation parameterization, which has the Laplace integral form. The unknown mass-attenuation spectrum is expanded into basis functions using a B-spline basis of order one. We develop a block coordinate-descent algorithm for constrained minimization of a penalized negative log-likelihood function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and sparsity of the density map image in the wavelet domain. This algorithm alternates between a Nesterov’s proximal-gradient step for estimating the density map image and an active-set step for estimating the incident spectrum parameters. Numerical simulations demonstrate the performance of the proposed scheme.

  18. Evaluations of multiplanar reconstruction in CT recognition of lumbar disk disease

    SciTech Connect

    Rosenthal, D.I.; Stauffer, A.E.; Davis, K.R.; Ganott, M.; Taveras, J.M.

    1984-07-01

    Axial computed tomographic (CT) images were compared with sagittal and coronal reformations and myelograms in 60 patients to evaluate the diagnostic usefulness of multiplanar reconstructions for the recognition of lumbar disk disease. The axial CT scans were most sensitive and specific. The sagittal scans were helpful in evaluating the neural foramina, the size of the disk bulge into the spinal canal, especially at L5-S1, and patients with spondylolisthesis. The coronal images were the least informative, although they contributed to the evaluation of lumbar nerve roots. The myelograms and the sagittal images were equally useful in the detection of herniated disk, but axial scans were superior to either. It was concluded that reformatted sagittal and coronal images are not required if all axial images are normal.

  19. A curve-filtered FDK (C-FDK) reconstruction algorithm for circular cone-beam CT.

    PubMed

    Li, Liang; Xing, Yuxiang; Chen, Zhiqiang; Zhang, Li; Kang, Kejun

    2011-01-01

    Circular cone-beam CT is one of the most popular configurations in both medical and industrial applications. The FDK algorithm is the most popular method for circular cone-beam CT. However, with increasing cone-angle the cone-beam artifacts associated with the FDK algorithm deteriorate because the circular trajectory does not satisfy the data sufficiency condition. Along with an experimental evaluation and verification, this paper proposed a curve-filtered FDK (C-FDK) algorithm. First, cone-parallel projections are rebinned from the native cone-beam geometry in two separate directions. C-FDK rebins and filters projections along different curves from T-FDK in the centrally virtual detector plane. Then, numerical experiments are done to validate the effectiveness of the proposed algorithm by comparing with both FDK and T-FDK reconstruction. Without any other extra trajectories supplemental to the circular orbit, C-FDK has a visible image quality improvement.

  20. CT scans and 3D reconstructions of Florida manatee (Trichechus manatus latirostris) heads and ear bones.

    PubMed

    Chapla, Marie E; Nowacek, Douglas P; Rommel, Sentiel A; Sadler, Valerie M

    2007-06-01

    The auditory anatomy of the Florida manatee (Trichechus manatus latirostris) was investigated using computerized tomography (CT), three-dimensional reconstructions, and traditional dissection of heads removed during necropsy. The densities (kg/m3) of the soft tissues of the head were measured directly using the displacement method and those of the soft tissues and bone were calculated from CT measurements (Hounsfield units). The manatee's fatty tissue was significantly less dense than the other soft tissues within the head (p<0.05). The squamosal bone was significantly less dense than the other bones of the head (p<0.05). Measurements of the ear bones (tympanic, periotic, malleus, incus, and stapes) collected during dissection revealed that the ossicular chain was overly massive for the mass of the tympanoperiotic complex.

  1. Compressive Sampling Based Interior Reconstruction for Dynamic Carbon Nanotube Micro-CT

    PubMed Central

    Yu, Hengyong; Cao, Guohua; Burk, Laurel; Lee, Yueh; Lu, Jianping; Santago, Pete; Zhou, Otto; Wang, Ge

    2010-01-01

    In the computed tomography (CT) field, one recent invention is the so-called carbon nanotube (CNT) based field emission x-ray technology. On the other hand, compressive sampling (CS) based interior tomography is a new innovation. Combining the strengths of these two novel subjects, we apply the interior tomography technique to local mouse cardiac imaging using respiration and cardiac gating with a CNT based micro-CT scanner. The major features of our method are: (1) it does not need exact prior knowledge inside an ROI; and (2) two orthogonal scout projections are employed to regularize the reconstruction. Both numerical simulations and in vivo mouse studies are performed to demonstrate the feasibility of our methodology. PMID:19923686

  2. Applications of the Medipix3-CT in combination with iterative reconstruction techniques

    NASA Astrophysics Data System (ADS)

    Fischer, F.; Procz, S.; Fauler, A.; Fiederle, M.

    2016-02-01

    The pixelated semiconductor detectors of the Medipix family with their photon-counting abilities offer the possibility of high quality X-ray radiography as well as computed tomography. The generated signal from each photon is amplified and shaped before it is compared to an energy threshold. For a photon with an energy above the threshold the counter is incremented by one count. Photons below the operator-defined threshold do not increment the counter and therefore do not participate in the image formation. Furthermore, compared to other detectors like scintillators, an additional conversion step is dispensed due to the direct converting nature of photon-counting detectors, leading to a higher signal-to-noise-ratio. Additionally, the photon processing capabilities of photon-counting detectors allow photons to be weighted equally and not proportional to their energy as it is the case for charge integrating devices, where high energy photons are weighted stronger than low energy photons. Compared to integrating devices, this leads to an increase in contrast for images of both high and low contrast objects, hence improve object information. The use of photon-counting detectors in combination with iterative reconstruction techniques based on OSEM (ordered subset expectation maximization) algorithms is the basis of our computed tomography scans for material analysis. Due to its ability to operate with highly undersampled data sets, iterative reconstruction offers the possibility to decrease dose in CT scans. In order to identify the limits of the data set reduction, a first series of scans was performed to test, under real conditions, the CT-image quality when a strongly reduced amount of projections is used for reconstruction. In addition, the effect of a total variation minimization tool on these undersampled data sets was evaluated. Furthermore, this paper includes a number of recent CT-results with scans performed at two different setups within our facility.

  3. Effect of voxel size on the accuracy of 3D reconstructions with cone beam CT

    PubMed Central

    Maret, D; Telmon, N; Peters, O A; Lepage, B; Treil, J; Inglèse, J M; Peyre, A; Kahn, J L; Sixou, M

    2012-01-01

    Objectives The various types of cone beam CT (CBCT) differ in several technical characteristics, notably their spatial resolution, which is defined by the acquisition voxel size. However, data are still lacking on the effects of voxel size on the metric accuracy of three-dimensional (3D) reconstructions. This study was designed to assess the effect of isotropic voxel size on the 3D reconstruction accuracy and reproducibility of CBCT data. Methods The study sample comprised 70 teeth (from the Institut d’Anatomie Normale, Strasbourg, France). The teeth were scanned with a KODAK 9500 3D® CBCT (Carestream Health, Inc., Marne-la-Vallée, France), which has two voxel sizes: 200 µm (CBCT 200 µm group) and 300 µm (CBCT 300 µm group). These teeth had also been scanned with the KODAK 9000 3D® CBCT (Carestream Health, Inc.) (CBCT 76 µm group) and the SCANCO Medical micro-CT XtremeCT (SCANCO Medical, Brüttisellen, Switzerland) (micro-CT 41 µm group) considered as references. After semi-automatic segmentation with AMIRA® software (Visualization Sciences Group, Burlington, MA), tooth volumetric measurements were obtained. Results The Bland–Altman method showed no difference in tooth volumes despite a slight underestimation for the CBCT 200 µm and 300 µm groups compared with the two reference groups. The underestimation was statistically significant for the volumetric measurements of the CBCT 300 µm group relative to the two reference groups (Passing–Bablok method). Conclusions CBCT is not only a tool that helps in diagnosis and detection but it has the complementary advantage of being a measuring instrument, the accuracy of which appears connected to the size of the voxels. Future applications of such measurements with CBCT are discussed. PMID:23166362

  4. Effect of voxel size on the accuracy of 3D reconstructions with cone beam CT.

    PubMed

    Maret, D; Telmon, N; Peters, O A; Lepage, B; Treil, J; Inglèse, J M; Peyre, A; Kahn, J L; Sixou, M

    2012-12-01

    The various types of cone beam CT (CBCT) differ in several technical characteristics, notably their spatial resolution, which is defined by the acquisition voxel size. However, data are still lacking on the effects of voxel size on the metric accuracy of three-dimensional (3D) reconstructions. This study was designed to assess the effect of isotropic voxel size on the 3D reconstruction accuracy and reproducibility of CBCT data. The study sample comprised 70 teeth (from the Institut d'Anatomie Normale, Strasbourg, France). The teeth were scanned with a KODAK 9500 3D® CBCT (Carestream Health, Inc., Marne-la-Vallée, France), which has two voxel sizes: 200 µm (CBCT 200 µm group) and 300 µm (CBCT 300 µm group). These teeth had also been scanned with the KODAK 9000 3D® CBCT (Carestream Health, Inc.) (CBCT 76 µm group) and the SCANCO Medical micro-CT XtremeCT (SCANCO Medical, Brüttisellen, Switzerland) (micro-CT 41 µm group) considered as references. After semi-automatic segmentation with AMIRA® software (Visualization Sciences Group, Burlington, MA), tooth volumetric measurements were obtained. The Bland-Altman method showed no difference in tooth volumes despite a slight underestimation for the CBCT 200 µm and 300 µm groups compared with the two reference groups. The underestimation was statistically significant for the volumetric measurements of the CBCT 300 µm group relative to the two reference groups (Passing-Bablok method). CBCT is not only a tool that helps in diagnosis and detection but it has the complementary advantage of being a measuring instrument, the accuracy of which appears connected to the size of the voxels. Future applications of such measurements with CBCT are discussed.

  5. Spatial estimates of snow water equivalent from reconstruction

    NASA Astrophysics Data System (ADS)

    Rittger, Karl; Bair, Edward H.; Kahl, Annelen; Dozier, Jeff

    2016-08-01

    Operational ground-based measurements of snow water equivalent (SWE) do not adequately explain spatial variability in mountainous terrain. To address this problem, we combine satellite-based retrievals of fractional snow cover for the period 2000 to 2011 with spatially distributed energy balance calculations to reconstruct SWE values throughout each melt season in the Sierra Nevada of California. Modeled solar radiation, longwave radiation, and air temperature from NLDAS drive the snowmelt model. The modeled solar radiation compares well to ground observations, but modeled longwave radiation is slightly lower than observations. Validation of reconstructed SWE with snow courses and our own snow surveys shows that the model can accurately estimate SWE at the sampled locations in a variety of topographic settings for a range of wet to dry years. The relationships of SWE with elevation and latitude are significantly different for wet, mean and dry years as well as between drainages. In all the basins studied, the relationship between remaining SWE and snow-covered area (SCA) becomes increasingly correlated from March to July as expected because SCA is an important model input. Though the SWE is calculated retrospectively SCA observations are available in near-real time and combined with historical reconstructions may be sufficient for estimating SWE with more confidence as the melt season progresses.

  6. The impact of image reconstruction bias on PET/CT 90Y dosimetry after radioembolization.

    PubMed

    Tapp, Katie N; Lea, William B; Johnson, Matthew S; Tann, Mark; Fletcher, James W; Hutchins, Gary D

    2014-09-01

    PET/CT imaging after radioembolization is a viable method for determining the posttreatment (90)Y distribution in the liver. Low true-to-random coincidence ratios in (90)Y PET studies limit the quantitative accuracy of these studies when reconstruction algorithms optimized for traditional PET imaging are used. This study examined these quantitative limitations and assessed the feasibility of generating radiation dosimetry maps in liver regions with high and low (90)Y concentrations. (90)Y PET images were collected on a PET/CT scanner and iteratively reconstructed with the vendor-supplied reconstruction algorithm. PET studies on a Jaszczak cylindric phantom were performed to determine quantitative accuracy and minimum detectable concentration (MDC). (90)Y and (18)F point-source studies were used to investigate the possible increase in detected random coincidence events due to bremsstrahlung photons. Retrospective quantitative analyses were performed on (90)Y PET/CT images obtained after 65 right or left hepatic artery radioembolizations in 59 patients. Quantitative image errors were determined by comparing the measured image activity with the assayed (90)Y activity. PET images were converted to dose maps through convolution with voxel S values generated using MCNPX, a Monte Carlo N-particle transport code system for multiparticle and high-energy applications. Tumor and parenchyma doses and potential bias based on measurements found below the MDC were recorded. Random coincidences were found to increase in (90)Y acquisitions, compared with (18)F acquisitions, at similar positron emission rates because of bremsstrahlung photons. Positive bias was observed in all images. Quantitative accuracy was achieved for phantom inserts above the MDC of 1 MBq/mL. The mean dose to viable tumors was 183.6 ± 156.5 Gy, with an average potential bias of 3.3 ± 6.4 Gy. The mean dose to the parenchyma was 97.1 ± 22.1 Gy, with an average potential bias of 8.9 ± 4.9 Gy. The low signal

  7. Multiplanar CT reconstruction of the jaw: a new way for implant diagnostics

    NASA Astrophysics Data System (ADS)

    Gursky, S.; Wittek, Werner; Wilke, Walter; Schulz, H.; Lieberenz, S.

    1990-11-01

    For preoperative planning of dental implantations pictorial representations are required that permit to evaluate the size of teeth holes, size and structure of jaw bones, position of the mandibular channel and of the alveolar nerve. Since normal transaxial. CT images do not meet these requirements special secondary reconstructions adapted to jaw anatomy are necessary: -panoramic secondary cuts The cut line follows jaw curvature and represents a similar view as orthopantomographic pictures. (see Fig.1) -oblique secondary cuts That are plane cuts perpendicular to the panoramic cut line. (see Fig.2)

  8. Agenesis of dorsal pancreas confirmed by three-dimensional reconstruction CT

    PubMed Central

    Zhou, Yang; Chen, Munan; Liu, Yang

    2014-01-01

    Agenesis of the dorsal pancreas (ADP) is a rare congenital pancreatic malformation in which all or part of the dorsal pancreatic body is absent. ADP is usually confirmed by magnetic resonance cholangiopancreatography (MRCP) or endoscopic retrograde cholangiopancreatography (ERCP), but these methods are undesirable to patients because of strict limitations or invasiveness. We propose abdominal contrast-enhanced and three-dimensional reconstruction CT images as an improved method for ADP diagnosis, and present a case study of ADP confirmed with these methods. PMID:25356189

  9. Image reconstruction and image quality evaluation for a 16-slice CT scanner.

    PubMed

    Flohr, Th; Stierstorfer, K; Bruder, H; Simon, J; Polacin, A; Schaller, S

    2003-05-01

    We present a theoretical overview and a performance evaluation of a novel approximate reconstruction algorithm for cone-beam spiral CT, the adaptive multiple plane reconstruction (AMPR), which has been introduced by Schaller, Flohr et al. [Proc. SPIE Int. Symp. Med. Imag. 4322, 113-127 (2001)] AMPR has been implemented in a recently introduced 16-slice CT scanner. We present a detailed algorithmic description of AMPR which allows for a free selection of the spiral pitch. We show that dose utilization is better than 90% independent of the pitch. We give an overview on the z-reformation functions chosen to allow for a variable selection of the spiral slice width at arbitrary pitch values. To investigate AMPR image quality we present images of anthropomorphic phantoms and initial patient results. We present measurements of spiral slice sensitivity profiles (SSPs) and measurements of the maximum achievable transverse resolution, both in the isocenter and off-center. We discuss the pitch dependence of image noise measured in a centered 20 cm water phantom. Using the AMPR approach, cone-beam artifacts are considerably reduced for the 16-slice scanner investigated. Image quality in MPRs is independent of the pitch and equivalent to a single-slice CT system at pitch p approximately 1.5. The full width at half-maximum (FWHM) of the spiral SSPs shows only minor variations as a function of the pitch, nominal, and measured values differ by less than 0.2 mm. With 16 x 0.75 mm collimation, the measured FWHM of the smallest reconstructed slice is about 0.9 mm. Using this slice width and overlapping image reconstruction, cylindrical holes with 0.6 mm diameter can be resolved in a z-resolution phantom. Image noise for constant effective mAs is nearly independent of the pitch. Measured and theoretically expected dose utilization are in good agreement. Meanwhile, clinical practice has demonstrated the excellent image quality and the increased diagnostic capability that is obtained

  10. Dose reduction in CT urography and vasculature phantom studies using model-based iterative reconstruction.

    PubMed

    Page, Leland; Wei, Wei; Kundra, Vikas; Rong, John

    2016-11-08

    To evaluate the feasibility of radiation dose reduction using model-based iterative reconstruction (MBIR) for evaluating the ureters and vasculature in a phantom, a tissue-equivalent CT dose phantom was scanned using a 64-channel CT scan-ner. Tubes of varying diameters filled with different dilutions of a contrast agent, simulating ureters or vessels, were inserted into the center of the phantom. Each combination was scanned using an existing renal protocol at 140 kVp or 120 kVp, yielding a display volumetric CT dose index (CTDIvol) of 24 mGy. The scans were repeated using reduced scan techniques to achieve lower radiation doses down to 0.8 mGy. The images were reconstructed using filtered back-projection (FBP) and model-based iterative reconstruction (MBIR). The noise and contrast-to-noise ratio (CNR) was measured for each contrast object. Comparisons between the two reconstruction methods at different dose levels were evaluated using a factorial design. At each CTDIvol the measured image noise was lower using MBIR compared to FBP (p < 0.0001). At low doses, the percent change in measured image noise between FBP and MBIR was larger. For the 12 mm object simulating a ureter or large vessel with an HU of 600, the measured CNR using MBIR at a CTDIvol of 1.7 mGy was greater than the CNR of FBP at a CTIDvol of 24 mGy (p < 0.0001). For the 5 mm object simulating a medium-sized vessel with a HU of 250, the mea-sured CNR using MBIR at a CTDIvol of 1.7 mGy was equivalent to that of FBP at a CTDIvol of 24 mGy. For the 2 mm, 100 HU object simulating a small vessel, the measured CNR using MBIR at a CTDIvol of 1.7 mGy was equivalent to that of FBP at a CTDIvol of 24 mGy. Low-dose (3.6 mGy) CT imaging of vasculature and ureter phantoms using MBIR results in similar noise and CNR compared to FBP at approximately one-sixth the dose. This suggests that, using MBIR, a one milliSievert exam of the ureters and vasculature may be clinically possible whilst still maintaining adequate

  11. Reconstruction of financial networks for robust estimation of systemic risk

    NASA Astrophysics Data System (ADS)

    Mastromatteo, Iacopo; Zarinelli, Elia; Marsili, Matteo

    2012-03-01

    In this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as maximum entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such an algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information that regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.

  12. Convergence of SART + OS + TV iterative reconstruction algorithm for optical CT imaging of gel dosimeters

    NASA Astrophysics Data System (ADS)

    Du, Yi; Yu, Gongyi; Xiang, Xincheng; Wang, Xiangang; De Deene, Yves

    2017-05-01

    Computational simulations are used to investigate the convergence of a hybrid iterative algorithm for optical CT reconstruction, i.e. the simultaneous algebraic reconstruction technique (SART) integrated with ordered subsets (OS) iteration and total variation (TV) minimization regularization, or SART+OS+TV for short. The influence of parameter selection to reach convergence, spatial dose gradient integrity, MTF and convergent speed are discussed. It’s shown that the results of SART+OS+TV algorithm converge to the true values without significant bias, and MTF and convergent speed are affected by different parameter sets used for iterative calculation. In conclusion, the performance of the SART+OS+TV depends on parameter selection, which also implies that careful parameter tuning work is required and necessary for proper spatial performance and fast convergence.

  13. A novel reconstruction tool (syngo DynaCT Head Clear) in the post-processing of DynaCT images to reduce artefacts and improve image quality.

    PubMed

    Lescher, Stephanie; Reh, Christina; Hoelter, Maya Christina; Czeppan, Katja; Porto, Luciana; Blasel, Stella; Berkefeld, Joachim; Wagner, Marlies

    2016-01-19

    Latest generations of flat detector (FD) neuroangiography systems are able to obtain CT-like images of the brain parenchyma. Owing to the geometry of the C-arm system, cone beam artifacts are common and reduce image quality, especially at the periphery of the field of view. An advanced reconstruction algorithm (syngo DynaCT Head Clear) tackles these artifacts by using a modified interpolation-based 3D correction algorithm to improve image quality. Eleven volumetric datasets from FD-CT scans were reconstructed with the standard algorithm as well as with the advanced algorithm. In a two-step data analysis process, two reviewers compared dedicated regions of the skull and brain in both reconstruction modes using a 5-point scale (1, much better; 5, much worse; advanced vs standard algorithm). Both reviewers were blinded to the reconstruction mode. In a second step, two additional observers independently evaluated image quality of the 3D data (non-comparative evaluation) in dedicated regions also using a 5-point scale (1, not diagnostically evaluable; 5, good quality, perfectly usable for diagnosis) for both reconstruction algorithms. Both in the comparative evaluation of dedicated brain regions and in the independent analysis of the FD-CT datasets the observers rated a better image quality if the advanced algorithm was used. The improvement in image quality was statistically significant at both the supraganglionic (p=0.018) and the infratentorial (p=0.002) levels. The advanced reconstruction algorithm reduces typical artifacts in FD-CT images and improves image quality at the periphery of the field of view. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  14. Optimization of the alpha image reconstruction - an iterative CT-image reconstruction with well-defined image quality metrics.

    PubMed

    Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

    2017-09-01

    Optimization of the AIR-algorithm for improved convergence and performance. The AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

  15. The influence of CT dose and reconstruction parameters on automated detection of small pulmonary nodules

    NASA Astrophysics Data System (ADS)

    Ochs, Robert; Angel, Erin; Boedeker, Kirsten; Petkovska, Iva; Panknin, Christoph; Goldin, Jonathan; Aberle, Denise; McNitt-Gray, Michael; Brown, Matthew

    2006-03-01

    The aim of our investigation was to assess the influence of both CT acquisition dose and reconstruction kernel on computer-aided detection (CAD) of pulmonary nodules. Our hypothesis is that the detection of small nodules is affected by the noise characteristics of the image and the signal to noise ratio of the nodule and bronchiovascular anatomy. Knowledge gained from this experiment will assist in developing an advanced CAD system designed to detect smaller and more subtle nodules with minimal false positives. Eleven research subjects were selected from the Lung Image Database Consortium (LIDC) database based on our inclusion criteria of: 1) having at least one nodule and 2) available raw CT projection data for the series that our institution submitted to the LIDC study. Using the original raw projection data, research software simulated raw projection data acquired with a dose reduced 32-40% from the original scan. Projection data for both dose levels was reconstructed with smooth to very sharp kernels (B10f, B30f, B50f, and B70f). The resulting series were used to investigate the influence of dose and reconstruction kernel on CAD performance. A prototype CAD system was used to investigate changes in sensitivity and false positives with varying imaging parameters. In a sub-study, the prototype system was compared to a commercial CAD system. We did not have enough subjects to conclude significance, but the results indicate our research system had a higher sensitivity with the smooth or medium reconstruction kernels than with the sharper kernels. The sensitivity was similar for both dose levels. The false positive rate was higher with the smooth kernels and the lower dose levels.

  16. Prognostic value of Tissue Transition Projection 3D transparent wall CT reconstructions in bowel ischemia.

    PubMed

    Moschetta, Marco; Scardapane, Arnaldo; Telegrafo, Michele; Lucarelli, Nicola Maria; Lorusso, Valentina; Angelelli, Giuseppe; Stabile Ianora, Amato Antonio

    2016-10-01

    Multi-detector computed tomography (MDCT) represents the gold standard in patients with acute abdomen syndrome and suspected bowel ischemia. It provides a correct diagnosis and contributes to appropriate treatment planning. This study aims to evaluate the role of 3D Tissue Transition Projection (TTP) transparent wall CT reconstruction for detecting the degree of bowel dilatation and to correlate this finding with the aetiology and prognosis in patients affected by mesenteric infarction. Forty-seven patients affected by bowel infarction due to vascular obstruction (arterial in 66% of cases, venous in 34%) were assessed by MDCT examination searching for the degree of bowel dilatation (subdivided into 4 groups: entire small bowel (SB); ≥50% of SB; < 50% of SB; large bowel only). Two blinded radiologists evaluated TTP 3D transparent wall and multi-planar reconstructions. Chi square test was used to correlate CT findings with the disease course and the mortality rate. Cohen's kappa statistics was used in order to assess inter-observer agreement. The overall mortality rate was 64%, with a 90% value for arterial forms and 10% in case of venous infarctions. The entire SB (n = 10) or a ≥50% SB dilatation (n = 16) correlated with poor prognosis in all cases (p < 0.05); a <50% SB dilatation (n = 16) correlated with good prognosis in 87.5% of cases (p < 0.05). A large bowel only dilatation (n = 5) did not show a significant prognostic value (p = 0.13). Almost perfect agreement between the two readers was found (k = 0.84). MDCT offers different reconstruction software for diagnosing bowel ischemia. 3D TTP transparent wall reconstructions represent a rapid and automatic tool for identifying loop dilatation, which significantly correlates with an arterial aetiology and poor prognosis. Copyright © 2016. Published by Elsevier Ltd.

  17. Total variation superiorization in dual-energy CT reconstruction for proton therapy treatment planning

    NASA Astrophysics Data System (ADS)

    Zhu, Jiahua; Penfold, Scott

    2017-04-01

    Proton therapy is a precise form of radiotherapy in which the range of an energetic beam of protons within a patient must be accurately known. The current approach based on single-energy computed tomography (SECT) can lead to uncertainties in the proton range of approximately 3%. This range of uncertainty may lead to under-dosing of the tumour or over-dosing of healthy tissues. Dual-energy CT (DECT) theoretically has the potential to reduce these range uncertainties by quantifying electron density and the effective atomic number. In practice, however, DECT images reconstructed with filtered backprojection (FBP) tend to suffer from high levels of noise. The objective of the current work was to examine the effect of total variation superiorization (TVS) on proton therapy planning accuracy when compared with FBP. A virtual CT scanner was created with the Monte Carlo toolkit Geant4. Tomographic images were reconstructed with FBP and TVS combined with diagonally relaxed orthogonal projections (TVS-DROP). A total variation minimization (TVM) filter was also applied to the image reconstructed with FBP (FBP-TVM). Quantitative accuracy and variance of proton relative stopping power (RSP) derived from each image set was assessed. Mean RSPs were comparable with each image; however, the standard deviation of pixel values with TVS-DROP was reduced by a factor of 0.44 compared with the FBP image and a factor of 0.66 when compared with the FBP-TVM image. Proton doses calculated with the TVS-DROP image set were also better able to predict a reference dose distribution when compared with the FBP and FBP-TVM image sets. The study demonstrated the potential advantages of TVS-DROP as an image reconstruction method for DECT applied to proton therapy treatment planning.

  18. A prospective feasibility study of sub-millisievert abdominopelvic CT using iterative reconstruction in Crohn's disease.

    PubMed

    O'Neill, Siobhan B; Mc Laughlin, Patrick D; Crush, Lee; O'Connor, Owen J; Mc Williams, Sebastian R; Craig, Orla; Mc Garrigle, Anne Marie; O'Neill, Fiona; Bye, Jackie; Ryan, Max F; Shanahan, Fergus; Maher, Michael M

    2013-09-01

    Iterative reconstruction (IR) allows diagnostic CT imaging with less radiation exposure than filtered back projection (FBP). We studied an IR low-dose CT abdomen/pelvis (LDCTAP) protocol, designed to image at an effective dose (ED) approximating 1 mSv in patients with Crohn's disease (CD). Forty patients, mean age 37 ± 13.4 years (range 17-69), with CD underwent two synchronous CT protocols (conventional-dose (CDCTAP) and LDCTAP). CDCTAP and LDCTAP images were compared for diagnostic acceptability, yield, image quality and ED (in millisieverts). The optimal level of IR for LDCTAP was also studied. LDCTAP yielded a mean ED of 1.3 ± 0.8 mSv compared with 4.7 ± 2.9 mSv for CDCTAP, reducing ED by 73.7 ± 3.3 % (mean dose reduction, 3.5 ± 2.1 mSv; P < 0.001) and dose length product by 73.6 ± 2.6 % (P < 0.001). Sub-millisievert (0.84 mSv) imaging was performed for patients with a body mass index (BMI) less than 25 (i.e. 63 % of our cohort). LDCTAP resulted in increased image noise and reduced diagnostic acceptability compared with CDCTAP despite use of IR, but detection of extra-luminal complications was comparable. Patients with suspected active CD can be adequately imaged using LDCTAP, yielding comparable information regarding extent, activity and complications of CD compared with CDCTAP, but with 74 % less dose. LDCTAP at doses equivalent to that of two abdominal radiographs represents a feasible alternative to CDCTAP. • Radiation dose is a concern when imaging patients with Crohn's disease. • New techniques allow low-dose abdominopelvic CT with acceptable image quality. • Using hybrid iterative reconstruction, its diagnostic yield compares well with that of conventional CT. • Sub-millisievert CT of patients with Crohn's disease appears technically and clinically feasible.

  19. Retrospective IMRT dose reconstruction based on cone-beam CT and MLC log-file.

    PubMed

    Lee, Louis; Le, Quynh-Thu; Xing, Lei

    2008-02-01

    Head-and-neck (HN) cone-beam computed tomography (CBCT) can be exploited to probe the IMRT dose delivered to a patient taking into account the interfraction anatomic variation and any potential inaccuracy in the IMRT delivery. The aim of this work is to reconstruct the intensity-modulated radiation therapy dose delivered to an HN patient using the CBCT and multileaf collimator (MLC) log-files. A cylindrical CT phantom was used for calibrating the electron density and validating the procedures of the dose reconstruction. Five HN patients were chosen, and for each patient, CBCTs were performed on three separate fractions spaced every 2 weeks starting from the first fraction. The respective MLC log-files were retrieved and converted into fluence maps. The dose was then reconstructed on the corresponding CBCT with the regenerated fluence maps. The reconstructed dose distribution, dosimetric endpoints, and DVHs were compared with that of the treatment plan. Phantom study showed that HN CBCT can be directly used for dose reconstruction. For most treatment sessions, the CBCT-based dose reconstructions yielded DVHs of the targets close (within 3%) to that of the original treatment plans. However, dosimetric changes (within 10%) due to anatomic variations caused by setup inaccuracy, organ deformation, tumour shrinkage, or weight loss (or a combination of these) were observed for the critical organs. The methodology we established affords an objective dosimetric basis for the clinical decision on whether a replanning is necessary during the course of treatment and provides a valuable platform for adaptive therapy in future.

  20. Computational methods estimating uncertainties for profile reconstruction in scatterometry

    NASA Astrophysics Data System (ADS)

    Gross, H.; Rathsfeld, A.; Scholze, F.; Model, R.; Bär, M.

    2008-04-01

    The solution of the inverse problem in scatterometry, i.e. the determination of periodic surface structures from light diffraction patterns, is incomplete without knowledge of the uncertainties associated with the reconstructed surface parameters. With decreasing feature sizes of lithography masks, increasing demands on metrology techniques arise. Scatterometry as a non-imaging indirect optical method is applied to periodic line-space structures in order to determine geometric parameters like side-wall angles, heights, top and bottom widths and to evaluate the quality of the manufacturing process. The numerical simulation of the diffraction process is based on the finite element solution of the Helmholtz equation. The inverse problem seeks to reconstruct the grating geometry from measured diffraction patterns. Restricting the class of gratings and the set of measurements, this inverse problem can be reformulated as a non-linear operator equation in Euclidean spaces. The operator maps the grating parameters to the efficiencies of diffracted plane wave modes. We employ a Gauss-Newton type iterative method to solve this operator equation and end up minimizing the deviation of the measured efficiency or phase shift values from the simulated ones. The reconstruction properties and the convergence of the algorithm, however, is controlled by the local conditioning of the non-linear mapping and the uncertainties of the measured efficiencies or phase shifts. In particular, the uncertainties of the reconstructed geometric parameters essentially depend on the uncertainties of the input data and can be estimated by various methods. We compare the results obtained from a Monte Carlo procedure to the estimations gained from the approximative covariance matrix of the profile parameters close to the optimal solution and apply them to EUV masks illuminated by plane waves with wavelengths in the range of 13 nm.

  1. Iterative CT reconstruction with small pixel size: distance-driven forward projector versus Joseph's

    NASA Astrophysics Data System (ADS)

    Hahn, K.; Rassner, U.; Davidson, H. C.; Schöndube, H.; Stierstorfer, K.; Hornegger, J.; Noo, F.

    2015-03-01

    Over the last few years, iterative reconstruction methods have become an important research topic in x-ray CT imaging. This effort is motivated by increasing evidence that such methods may enable significant savings in terms of dose imparted to the patient. Conceptually, iterative reconstruction methods involve two important ingredients: the statistical model, which includes the forward projector, and a priori information in the image domain, which is expressed using a regularizer. Most often, the image pixel size is chosen to be equal (or close) to the detector pixel size (at field-of-view center). However, there are applications for which a smaller pixel size is desired. In this investigation, we focus on reconstruction with a pixel size that is twice smaller than the detector pixel size. Using such a small pixel size implies a large increase in computational effort when using the distance-driven method for forward projection, which models the detector size. On the other hand, the more efficient method of Joseph will create imbalances in the reconstruction of each pixel, in the sense that there will be large differences in the way each projection contributes to the pixels. The purpose of this work is to evaluate the impact of these imbalances on image quality in comparison with utilization of the distance-driven method. The evaluation involves computational effort, bias and noise metrics, and LROC analysis using human observers. The results show that Joseph's method largely remains attractive.

  2. Feasibility of GPU-assisted iterative image reconstruction for mobile C-arm CT

    NASA Astrophysics Data System (ADS)

    Pan, Yongsheng; Whitaker, Ross; Cheryauka, Arvi; Ferguson, Dave

    2009-02-01

    Computed tomography (CT) has been extensively studied and widely used for a variety of medical applications. The reconstruction of 3D images from a projection series is an important aspect of the modality. Reconstruction by filtered backprojection (FBP) is used by most manufacturers because of speed, ease of implementation, and relatively few parameters. Iterative reconstruction methods have a significant potential to provide superior performance with incomplete or noisy data, or with less than ideal geometries, such as cone-beam systems. However, iterative methods have a high computational cost, and regularization is usually required to reduce the effects of noise. The simultaneous algebraic reconstruction technique (SART) is studied in this paper, where the Feldkamp method (FDK) for filtered back projection is used as an initialization for iterative SART. Additionally, graphics hardware is utilized to increase the speed of SART implementation. Nvidia processors and compute unified device architecture (CUDA) form the platform for GPU computation. Total variation (TV) minimization is applied for the regularization of SART results. Preliminary results of SART on 3-D Shepp-Logan phantom using using TV regularization and GPU computation are presented in this paper. Potential improvements of the proposed framework are also discussed.

  3. Iterative reconstruction optimisations for high angle cone-beam micro-CT

    NASA Astrophysics Data System (ADS)

    Recur, B.; Fauconneau, M.; Kingston, A.; Myers, G.; Sheppard, A.

    2014-09-01

    We address several acquisition questions that have arisen for the high cone-angle helical-scanning micro-CT facility developed at the Australian National University. These challenges are generally known in medical and industrial cone-beam scanners but can be neglected in these systems. For our large datasets, with more than 20483 voxels, minimising the number of operations (or iterations) is crucial. Large cone-angles enable high signal-to-noise ratio imaging and a large helical pitch to be used. This introduces two challenges: (i) non-uniform resolution throughout the reconstruction, (ii) over-scan beyond the region-of-interest significantly increases re- quired reconstructed volume size. Challenge (i) can be addressed by using a double-helix or lower pitch helix but both solutions slow down iterations. Challenge (ii) can also be improved by using a lower pitch helix but results in more projections slowing down iterations. This may be overcome using less projections per revolution but leads to more iterations required. Here we assume a given total time for acquisition and a given reconstruction technique (SART) and seek to identify the optimal trajectory and number of projections per revolution in order to produce the best tomogram, minimise reconstruction time required, and minimise memory requirements.

  4. Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality--preliminary findings.

    PubMed

    Miéville, Frédéric A; Gudinchet, François; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Bochud, François O; Verdun, Francis R

    2011-09-01

    Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI(vol) 4.8-7.9 mGy, DLP 37.1-178.9 mGy·cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone.

  5. Methodology for reconstruction of historical food consumption estimates

    SciTech Connect

    Anderson, D.M.

    1992-05-01

    This report was written to provide the food consumption methodology to be used in the Hanford Environmental Dose Reconstruction (HDER) Project beyond Phase I (which ended in July 1990). In Phase I (Callaway 1992), baseline food consumption estimates (grams per day) for 10 primary food types in the original 10-county study region were derived from the 1977--1978 National Food Consumption Survey (USDA 1983). The baseline estimates were multiplied by the 1945:1977 ratios to produce consumption estimates for 1945. This ratio backcasting method used in Phase I to project consumption estimates from 1977 back to 1945 will be refined using additional USDA data to improve and document the acceptability of the ratios for deriving backcast consumption estimates. The number of food types and population groups will be expanded to provide more disaggregated estimates of food consumption. Food consumption estimates will be developed for 1945, 1951, and 1957. A database of individual diets will be created from which daily diets will be randomly selected for use in the dose model to calculate doses for reference individuals.

  6. The Effects of Metal on Size Specific Dose Estimation (SSDE) in CT: A Phantom Study

    NASA Astrophysics Data System (ADS)

    Alsanea, Maram M.

    Over the past number of years there has been a significant increase in the awareness of radiation dose from use of computed tomography (CT). Efforts have been made to reduce radiation dose from CT and to better quantify dose being delivered. However, unfortunately, these dose metrics such as CTDI vol are not a specific patient dose. In 2011, the size-specific dose estimation (SSDE) was introduced by AAPM TG-204 which accounts for the physical size of the patient. However, the approach presented in TG-204 ignores the importance of the attenuation differences in the body. In 2014, a newer methodology that accounted for tissue attenuation was introduced by the AAPM TG-220 based on the concept of water equivalent diameter, Dw. One of the limitation of TG-220 is that there is no estimation of the dose while highly attenuating objects such as metal is present in the body. The purpose of this research is to evaluate the accuracy of size-specific dose estimates in CT in the presence of simulated metal prostheses using a conventional PMMA CTDI phantom at different phantom diameter (body and head) and beam energy. Titanium, Cobalt- chromium and stainless steel alloys rods were used in the study. Two approaches were used as introduced by AAPM TG-204 and 220 utilizing the effective diameter and the Dw calculations. From these calculations, conversion factors have been derived that could be applied to the measured CTDIvol to convert it to specific patient dose, or size specific dose estimate, (SSDE). Radiation dose in tissue (f-factor = 0.94) was measured at various chamber positions with the presence of metal. Following, an average weighted tissue dose (AWTD) was calculated in a manner similar to the weighted CTDI (CTDIw). In general, for the 32 cm body phantom SSDE220 provided more accurate estimates of AWTD than did SSDE204. For smaller patient size, represented by the 16 cm head phantom, the SSDE204 was a more accurate estimate of AWTD that that of SSDE220. However, as the

  7. NUFFT-Based Iterative Image Reconstruction via Alternating Direction Total Variation Minimization for Sparse-View CT

    PubMed Central

    Zhang, Hanming; Li, Lei; Cai, Ailong

    2015-01-01

    Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT). Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV) regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging. PMID:26120355

  8. NUFFT-Based Iterative Image Reconstruction via Alternating Direction Total Variation Minimization for Sparse-View CT.

    PubMed

    Yan, Bin; Jin, Zhao; Zhang, Hanming; Li, Lei; Cai, Ailong

    2015-01-01

    Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT). Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV) regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging.

  9. Regularization Designs for Uniform Spatial Resolution and Noise Properties in Statistical Image Reconstruction for 3D X-ray CT

    PubMed Central

    Cho, Jang Hwan; Fessler, Jeffrey A.

    2014-01-01

    Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in [1] to 3D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in [1] with both phantom simulation and clinical reconstruction in 3D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT. PMID:25361500

  10. Regularization designs for uniform spatial resolution and noise properties in statistical image reconstruction for 3-D X-ray CT.

    PubMed

    Cho, Jang Hwan; Fessler, Jeffrey A

    2015-02-01

    Statistical image reconstruction methods for X-ray computed tomography (CT) provide improved spatial resolution and noise properties over conventional filtered back-projection (FBP) reconstruction, along with other potential advantages such as reduced patient dose and artifacts. Conventional regularized image reconstruction leads to spatially variant spatial resolution and noise characteristics because of interactions between the system models and the regularization. Previous regularization design methods aiming to solve such issues mostly rely on circulant approximations of the Fisher information matrix that are very inaccurate for undersampled geometries like short-scan cone-beam CT. This paper extends the regularization method proposed in to 3-D cone-beam CT by introducing a hypothetical scanning geometry that helps address the sampling properties. The proposed regularization designs were compared with the original method in with both phantom simulation and clinical reconstruction in 3-D axial X-ray CT. The proposed regularization methods yield improved spatial resolution or noise uniformity in statistical image reconstruction for short-scan axial cone-beam CT.

  11. Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction

    PubMed Central

    Yu, Lifeng; Li, Zhoubo; Manduca, Armando; Blezek, Daniel J.; Hough, David M.; Venkatesh, Sudhakar K.; Brickner, Gregory C.; Cernigliaro, Joseph C.; Hara, Amy K.; Fidler, Jeff L.; Lake, David S.; Shiung, Maria; Lewis, David; Leng, Shuai; Augustine, Kurt E.; Carter, Rickey E.; Holmes, David R.; McCollough, Cynthia H.

    2015-01-01

    Purpose To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). Materials and Methods This study was approved by the institutional review board and was compliant with HIPAA. Informed consent was obtained from patients for the retrospective use of medical records for research purposes. CT projection data from 33 abdominal and 27 liver or pancreas CT examinations were collected (median volume CT dose index, 13.8 and 24.0 mGy, respectively). Hepatic malignancy was defined by progression or regression or with histopathologic findings. Lower-dose data were created by using a validated noise insertion method (10.4 mGy for abdominal CT and 14.6 mGy for liver or pancreas CT) and images reconstructed with FBP, ANLM, and SAFIRE. Four readers evaluated routine-dose FBP images and all lower-dose images, circumscribing liver lesions and selecting diagnosis. The jackknife free-response receiver operating characteristic figure of merit (FOM) was calculated on a per–malignant nodule or per-mass basis. Noninferiority was defined by the lower limit of the 95% confidence interval (CI) of the difference between lower-dose and routine-dose FOMs being less than −0.10. Results Twenty-nine patients had 62 malignant hepatic nodules and masses. Estimated FOM differences between lower-dose FBP and lower-dose ANLM versus routine-dose FBP were noninferior (difference: −0.041 [95% CI: −0.090, 0.009] and −0.003 [95% CI: −0.052, 0.047], respectively). In patients with dedicated liver scans, lower-dose ANLM images were noninferior (difference: +0.015 [95% CI: −0.077, 0.106]), whereas lower-dose FBP images were not (difference −0.049 [95% CI:

  12. SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

    SciTech Connect

    Gingold, E; Dave, J

    2014-06-01

    Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurements included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.

  13. Non-local total-variation (NLTV) minimization combined with reweighted L1-norm for compressed sensing CT reconstruction

    NASA Astrophysics Data System (ADS)

    Kim, Hojin; Chen, Josephine; Wang, Adam; Chuang, Cynthia; Held, Mareike; Pouliot, Jean

    2016-09-01

    The compressed sensing (CS) technique has been employed to reconstruct CT/CBCT images from fewer projections as it is designed to recover a sparse signal from highly under-sampled measurements. Since the CT image itself cannot be sparse, a variety of transforms were developed to make the image sufficiently sparse. The total-variation (TV) transform with local image gradient in L1-norm was adopted in most cases. This approach, however, which utilizes very local information and penalizes the weight at a constant rate regardless of different degrees of spatial gradient, may not produce qualified reconstructed images from noise-contaminated CT projection data. This work presents a new non-local operator of total-variation (NLTV) to overcome the deficits stated above by utilizing a more global search and non-uniform weight penalization in reconstruction. To further improve the reconstructed results, a reweighted L1-norm that approximates the ideal sparse signal recovery of the L0-norm is incorporated into the NLTV reconstruction with additional iterates. This study tested the proposed reconstruction method (reweighted NLTV) from under-sampled projections of 4 objects and 5 experiments (1 digital phantom with low and high noise scenarios, 1 pelvic CT, and 2 CBCT images). We assessed its performance against the conventional TV, NLTV and reweighted TV transforms in the tissue contrast, reconstruction accuracy, and imaging resolution by comparing contrast-noise-ratio (CNR), normalized root-mean square error (nRMSE), and profiles of the reconstructed images. Relative to the conventional NLTV, combining the reweighted L1-norm with NLTV further enhanced the CNRs by 2-4 times and improved reconstruction accuracy. Overall, except for the digital phantom with low noise simulation, our proposed algorithm produced the reconstructed image with the lowest nRMSEs and the highest CNRs for each experiment.

  14. Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT

    PubMed Central

    Dunet, Vincent; Hachulla, Anne-Lise; Grimm, Jochen; Beigelman-Aubry, Catherine

    2016-01-01

    Background Model-based iterative reconstruction (MBIR) reduces image noise and improves image quality (IQ) but its influence on post-processing tools including maximal intensity projection (MIP) and minimal intensity projection (mIP) remains unknown. Purpose To evaluate the influence on IQ of MBIR on native, mIP, MIP axial and coronal reformats of reduced dose computed tomography (RD-CT) chest acquisition. Material and Methods Raw data of 50 patients, who underwent a standard dose CT (SD-CT) and a follow-up RD-CT with a CT dose index (CTDI) of 2–3 mGy, were reconstructed by MBIR and FBP. Native slices, 4-mm-thick MIP, and 3-mm-thick mIP axial and coronal reformats were generated. The relative IQ, subjective IQ, image noise, and number of artifacts were determined in order to compare different reconstructions of RD-CT with reference SD-CT. Results The lowest noise was observed with MBIR. RD-CT reconstructed by MBIR exhibited the best relative and subjective IQ on coronal view regardless of the post-processing tool. MBIR generated the lowest rate of artefacts on coronal mIP/MIP reformats and the highest one on axial reformats, mainly represented by distortions and stairsteps artifacts. Conclusion The MBIR algorithm reduces image noise but generates more artifacts than FBP on axial mIP and MIP reformats of RD-CT. Conversely, it significantly improves IQ on coronal views, without increasing artifacts, regardless of the post-processing technique. PMID:27635253

  15. Multi-material decomposition using statistical image reconstruction for spectral CT.

    PubMed

    Long, Yong; Fessler, Jeffrey A

    2014-08-01

    Spectral computed tomography (CT) provides information on material characterization and quantification because of its ability to separate different basis materials. Dual-energy (DE) CT provides two sets of measurements at two different source energies. In principle, two materials can be accurately decomposed from DECT measurements. However, many clinical and industrial applications require three or more material images. For triple-material decomposition, a third constraint, such as volume conservation, mass conservation or both, is required to solve three sets of unknowns from two sets of measurements. The recently proposed flexible image-domain (ID) multi-material decomposition) method assumes each pixel contains at most three materials out of several possible materials and decomposes a mixture pixel by pixel. We propose a penalized-likelihood (PL) method with edge-preserving regularizers for each material to reconstruct multi-material images using a similar constraint from sinogram data. We develop an optimization transfer method with a series of pixel-wise separable quadratic surrogate (PWSQS) functions to monotonically decrease the complicated PL cost function. The PWSQS algorithm separates pixels to allow simultaneous update of all pixels, but keeps the basis materials coupled to allow faster convergence rate than our previous proposed material- and pixel-wise SQS algorithms. Comparing with the ID method using 2-D fan-beam simulations, the PL method greatly reduced noise, streak and cross-talk artifacts in the reconstructed basis component images, and achieved much smaller root mean square errors.

  16. Multi-Material Decomposition Using Statistical Image Reconstruction for Spectral CT

    PubMed Central

    Long, Yong; Fessler, Jeffrey A.

    2014-01-01

    Spectral CT provides information on material characterization and quantification because of its ability to separate different basis materials. Dual-energy (DE) CT provides two sets of measurements at two different source energies. In principle, two materials can be accurately decomposed from DECT measurements. However, many clinical and industrial applications require three or more material images. For triple-material decomposition, a third constraint, such as volume conservation, mass conservation or both, is required to solve three sets of unknowns from two sets of measurements. The recently proposed flexible image-domain (ID) multi-material decomposition (MMD) method assumes each pixel contains at most three materials out of several possible materials and decomposes a mixture pixel by pixel. We propose a penalized-likelihood (PL) method with edge-preserving regularizers for each material to reconstruct multi-material images using a similar constraint from sinogram data. We develop an optimization transfer method with a series of pixel-wise separable quadratic surrogate (PWSQS) functions to monotonically decrease the complicated PL cost function. The PWSQS algorithm separates pixels to allow simultaneous update of all pixels, but keeps the basis materials coupled to allow faster convergence rate than our previous proposed material-and pixel-wise SQS algorithms. Comparing with the ID method using 2D fan-beam simulations, the PL method greatly reduced noise, streak and cross-talk artifacts in the reconstructed basis component images, and achieved much smaller root-mean-square (RMS) errors. PMID:24801550

  17. Construction and analysis of a head CT-scan database for craniofacial reconstruction.

    PubMed

    Tilotta, Françoise; Richard, Frédéric; Glaunès, Joan; Berar, Maxime; Gey, Servane; Verdeille, Stéphane; Rozenholc, Yves; Gaudy, J F

    2009-10-30

    This paper is devoted to the construction of a complete database which is intended to improve the implementation and the evaluation of automated facial reconstruction. This growing database is currently composed of 85 head CT-scans of healthy European subjects aged 20-65 years old. It also includes the triangulated surfaces of the face and the skull of each subject. These surfaces are extracted from CT-scans using an original combination of image-processing techniques which are presented in the paper. Besides, a set of 39 referenced anatomical skull landmarks were located manually on each scan. Using the geometrical information provided by triangulated surfaces, we compute facial soft-tissue depths at each known landmark positions. We report the average thickness values at each landmark and compare our measures to those of the traditional charts of [J. Rhine, C.E. Moore, Facial Tissue Thickness of American Caucasoïds, Maxwell Museum of Anthropology, Albuquerque, New Mexico, 1982] and of several recent in vivo studies [M.H. Manhein, G.A. Listi, R.E. Barsley, et al., In vivo facial tissue depth measurements for children and adults, Journal of Forensic Sciences 45 (1) (2000) 48-60; S. De Greef, P. Claes, D. Vandermeulen, et al., Large-scale in vivo Caucasian facial soft tissue thickness database for craniofacial reconstruction, Forensic Science International 159S (2006) S126-S146; R. Helmer, Schödelidentifizierung durch elektronische bildmischung, Kriminalistik Verlag GmbH, Heidelberg, 1984].

  18. Polyquant CT: direct electron and mass density reconstruction from a single polyenergetic source.

    PubMed

    Mason, Jonathan Hugh; Perelli, Alessandro; Nailon, William H; Davies, Michael E

    2017-10-05

    Quantifying material mass and electron density from computed tomography (CT) reconstructions can be highly valuable in certain medical practices, such as radiation therapy planning. However, uniquely parameterising the X-ray attenuation in terms of mass or electron density is an ill-posed problem when a single polyenergetic source is used with a spectrally indiscriminate detector. Existing approaches to single source polyenergetic modelling often impose consistency with a physical model, such as water--bone or photoelectric--Compton decompositions, which will either require detailed prior segmentation or restrictive energy dependencies, and may require further calibration to the quantity of interest. In this work, we introduce a data centric approach to fitting the attenuation with piecewise-linear functions directly to mass or electron density, and present a segmentation-free statistical reconstruction algorithm for exploiting it, with the same order of complexity as other iterative methods. We show how this allows both higher accuracy in attenuation modelling, and demonstrate its superior quantitative imaging, with numerical chest and metal implant data, and validate it with real cone-beam CT measurements. © 2017 Institute of Physics and Engineering in Medicine.

  19. Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

    NASA Astrophysics Data System (ADS)

    Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

    2011-03-01

    Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

  20. Fast X-Ray CT Image Reconstruction Using a Linearized Augmented Lagrangian Method with Ordered Subsets

    PubMed Central

    Nien, Hung; Fessler, Jeffrey A.

    2014-01-01

    Augmented Lagrangian (AL) methods for solving convex optimization problems with linear constraints are attractive for imaging applications with composite cost functions due to the empirical fast convergence rate under weak conditions. However, for problems such as X-ray computed tomography (CT) image reconstruction, where the inner least-squares problem is challenging and requires iterations, AL methods can be slow. This paper focuses on solving regularized (weighted) least-squares problems using a linearized variant of AL methods that replaces the quadratic AL penalty term in the scaled augmented Lagrangian with its separable quadratic surrogate (SQS) function, leading to a simpler ordered-subsets (OS) accelerable splitting-based algorithm, OS-LALM. To further accelerate the proposed algorithm, we use a second-order recursive system analysis to design a deterministic downward continuation approach that avoids tedious parameter tuning and provides fast convergence. Experimental results show that the proposed algorithm significantly accelerates the convergence of X-ray CT image reconstruction with negligible overhead and can reduce OS artifacts when using many subsets. PMID:25248178

  1. CT reconstruction from few-views with anisotropic edge-guided total variance

    NASA Astrophysics Data System (ADS)

    Rong, Junyan; Liu, Wenlei; Gao, Peng; Liao, Qimei; Jiao, Chun; Ma, Jianhua; Lu, Hongbing

    2016-06-01

    To overcome the oversmoothing drawback in the edge areas when reconstructing few-view CT with total variation (TV) minimization, in this paper, we propose an anisotropic edge-guided TV minimization framework for few-view CT reconstruction. In the framework, anisotropic TV is summed with pre-weighted image gradient and then used as the object function for minimizing. It includes edge-guided TV minimization (EGTV) and edge-guided adaptive-weighted TV minimization (EGAwTV) algorithms. For EGTV algorithm, the weights of the TV discretization term are updated by anisotropic edge information detected from the image, whereas the weights for EGAwTV are determined based on edge information and local image-intensity gradients. To solve the minimization problem of the proposed algorithm, a similar TV-based minimization implementation is developed to address the raw data fidelity and other constraints. The evaluation results using both computer simulations with the Shepp-Logan phantom and experimental data from a physical phantom demonstrate that the proposed algorithms exhibit noticeable gains in the merits of spatial resolution compared with the conventional TV and other modified TV algorithms.

  2. Fast X-ray CT image reconstruction using a linearized augmented Lagrangian method with ordered subsets.

    PubMed

    Nien, Hung; Fessler, Jeffrey A

    2015-02-01

    Augmented Lagrangian (AL) methods for solving convex optimization problems with linear constraints are attractive for imaging applications with composite cost functions due to the empirical fast convergence rate under weak conditions. However, for problems such as X-ray computed tomography (CT) image reconstruction, where the inner least-squares problem is challenging and requires iterations, AL methods can be slow. This paper focuses on solving regularized (weighted) least-squares problems using a linearized variant of AL methods that replaces the quadratic AL penalty term in the scaled augmented Lagrangian with its separable quadratic surrogate function, leading to a simpler ordered-subsets (OS) accelerable splitting-based algorithm, OS-LALM. To further accelerate the proposed algorithm, we use a second-order recursive system analysis to design a deterministic downward continuation approach that avoids tedious parameter tuning and provides fast convergence. Experimental results show that the proposed algorithm significantly accelerates the convergence of X-ray CT image reconstruction with negligible overhead and can reduce OS artifacts when using many subsets.

  3. Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction.

    PubMed

    Kim, Yookyung; Kim, Yoon Kyung; Lee, Bo Eun; Lee, Seok Jeong; Ryu, Yon Ju; Lee, Jin Hwa; Chang, Jung Hyun

    2015-06-01

    The purpose of this study is to assess the image quality and radiation dose reduction of ultra-low-dose CT using sinogram-affirmed iterative reconstruction (SAFIRE). This prospective study enrolled 25 patients who underwent three consecutive unenhanced CT scans including low-dose CT (120 kVp and 30 mAs) and two ultra-low-dose CT protocols (protocol A, 100 kVp and 20 mAs; protocol B, 80 kVp and 30 mAs) with image reconstruction using SAFIRE. The image quality and radiation dose reduction were assessed. The mean (± SD) effective radiation dose was 1.06 ± 0.11, 0.44 ± 0.05, and 0.31 ± 0.03 mSv for low-dose CT, ultra-low-dose CT protocol A, and ultra-low-dose CT protocol B, respectively. Overall image quality was determined as diagnostic in 100% of low-dose CT scans, 96% of ultra-low-dose CT protocol A scans, and 88% of ultra-low-dose CT protocol B scans. All patients with nondiagnostic quality images had a body mass index (weight in kilograms divided by the square of height in meters) greater than 25. There was no statistically significant difference in detection frequencies of 14 lesion types among the three CT protocols, but pulmonary emphysema was detected in fewer patients (3/25) in ultra-low-dose CT protocol B scans compared with ultra-low-dose CT protocol A scans (5/25) or low-dose CT scans (6/25). We measured the longest dimensions of 33 small solid nodules (3.8-12.4 mm in long diameter) and found no statistically significant difference in the values afforded by the three CT protocols (p = 0.135). Iterative reconstruction allows ultra-low-dose CT and affords acceptable image quality, allowing size measurements of solid pulmonary nodules to be made.

  4. A compressed sensing-based iterative algorithm for CT reconstruction and its possible application to phase contrast imaging.

    PubMed

    Li, Xueli; Luo, Shuqian

    2011-08-18

    Computed Tomography (CT) is a technology that obtains the tomogram of the observed objects. In real-world applications, especially the biomedical applications, lower radiation dose have been constantly pursued. To shorten scanning time and reduce radiation dose, one can decrease X-ray exposure time at each projection view or decrease the number of projections. Until quite recently, the traditional filtered back projection (FBP) method has been commonly exploited in CT image reconstruction. Applying the FBP method requires using a large amount of projection data. Especially when the exposure speed is limited by the mechanical characteristic of the imaging facilities, using FBP method may prolong scanning time and cumulate with a high dose of radiation consequently damaging the biological specimens. In this paper, we present a compressed sensing-based (CS-based) iterative algorithm for CT reconstruction. The algorithm minimizes the l1-norm of the sparse image as the constraint factor for the iteration procedure. With this method, we can reconstruct images from substantially reduced projection data and reduce the impact of artifacts introduced into the CT reconstructed image by insufficient projection information. To validate and evaluate the performance of this CS-base iterative algorithm, we carried out quantitative evaluation studies in imaging of both software Shepp-Logan phantom and real polystyrene sample. The former is completely absorption based and the later is imaged in phase contrast. The results show that the CS-based iterative algorithm can yield images with quality comparable to that obtained with existing FBP and traditional algebraic reconstruction technique (ART) algorithms. Compared with the common reconstruction from 180 projection images, this algorithm completes CT reconstruction from only 60 projection images, cuts the scan time, and maintains the acceptable quality of the reconstructed images.

  5. Practical reconstruction protocol for quantitative (90)Y bremsstrahlung SPECT/CT.

    PubMed

    Siman, W; Mikell, J K; Kappadath, S C

    2016-09-01

    To develop a practical background compensation (BC) technique to improve quantitative (90)Y-bremsstrahlung single-photon emission computed tomography (SPECT)/computed tomography (CT) using a commercially available imaging system. All images were acquired using medium-energy collimation in six energy windows (EWs), ranging from 70 to 410 keV. The EWs were determined based on the signal-to-background ratio in planar images of an acrylic phantom of different thicknesses (2-16 cm) positioned below a (90)Y source and set at different distances (15-35 cm) from a gamma camera. The authors adapted the widely used EW-based scatter-correction technique by modeling the BC as scaled images. The BC EW was determined empirically in SPECT/CT studies using an IEC phantom based on the sphere activity recovery and residual activity in the cold lung insert. The scaling factor was calculated from 20 clinical planar (90)Y images. Reconstruction parameters were optimized in the same SPECT images for improved image quantification and contrast. A count-to-activity calibration factor was calculated from 30 clinical (90)Y images. The authors found that the most appropriate imaging EW range was 90-125 keV. BC was modeled as 0.53× images in the EW of 310-410 keV. The background-compensated clinical images had higher image contrast than uncompensated images. The maximum deviation of their SPECT calibration in clinical studies was lowest (<10%) for SPECT with attenuation correction (AC) and SPECT with AC + BC. Using the proposed SPECT-with-AC + BC reconstruction protocol, the authors found that the recovery coefficient of a 37-mm sphere (in a 10-mm volume of interest) increased from 39% to 90% and that the residual activity in the lung insert decreased from 44% to 14% over that of SPECT images with AC alone. The proposed EW-based BC model was developed for (90)Y bremsstrahlung imaging. SPECT with AC + BC gave improved lesion detectability and activity quantification compared to SPECT with AC

  6. An angle-dependent estimation of CT x-ray spectrum from rotational transmission measurements

    SciTech Connect

    Lin, Yuan Samei, Ehsan; Ramirez-Giraldo, Juan Carlos; Gauthier, Daniel J.; Stierstorfer, Karl

    2014-06-15

    Purpose: Computed tomography (CT) performance as well as dose and image quality is directly affected by the x-ray spectrum. However, the current assessment approaches of the CT x-ray spectrum require costly measurement equipment and complicated operational procedures, and are often limited to the spectrum corresponding to the center of rotation. In order to address these limitations, the authors propose an angle-dependent estimation technique, where the incident spectra across a wide range of angular trajectories can be estimated accurately with only a single phantom and a single axial scan in the absence of the knowledge of the bowtie filter. Methods: The proposed technique uses a uniform cylindrical phantom, made of ultra-high-molecular-weight polyethylene and positioned in an off-centered geometry. The projection data acquired with an axial scan have a twofold purpose. First, they serve as a reflection of the transmission measurements across different angular trajectories. Second, they are used to reconstruct the cross sectional image of the phantom, which is then utilized to compute the intersection length of each transmission measurement. With each CT detector element recording a range of transmission measurements for a single angular trajectory, the spectrum is estimated for that trajectory. A data conditioning procedure is used to combine information from hundreds of collected transmission measurements to accelerate the estimation speed, to reduce noise, and to improve estimation stability. The proposed spectral estimation technique was validated experimentally using a clinical scanner (Somatom Definition Flash, Siemens Healthcare, Germany) with spectra provided by the manufacturer serving as the comparison standard. Results obtained with the proposed technique were compared against those obtained from a second conventional transmission measurement technique with two materials (i.e., Cu and Al). After validation, the proposed technique was applied to measure

  7. An angle-dependent estimation of CT x-ray spectrum from rotational transmission measurements.

    PubMed

    Lin, Yuan; Ramirez-Giraldo, Juan Carlos; Gauthier, Daniel J; Stierstorfer, Karl; Samei, Ehsan

    2014-06-01

    Computed tomography (CT) performance as well as dose and image quality is directly affected by the x-ray spectrum. However, the current assessment approaches of the CT x-ray spectrum require costly measurement equipment and complicated operational procedures, and are often limited to the spectrum corresponding to the center of rotation. In order to address these limitations, the authors propose an angle-dependent estimation technique, where the incident spectra across a wide range of angular trajectories can be estimated accurately with only a single phantom and a single axial scan in the absence of the knowledge of the bowtie filter. The proposed technique uses a uniform cylindrical phantom, made of ultra-high-molecular-weight polyethylene and positioned in an off-centered geometry. The projection data acquired with an axial scan have a twofold purpose. First, they serve as a reflection of the transmission measurements across different angular trajectories. Second, they are used to reconstruct the cross sectional image of the phantom, which is then utilized to compute the intersection length of each transmission measurement. With each CT detector element recording a range of transmission measurements for a single angular trajectory, the spectrum is estimated for that trajectory. A data conditioning procedure is used to combine information from hundreds of collected transmission measurements to accelerate the estimation speed, to reduce noise, and to improve estimation stability. The proposed spectral estimation technique was validated experimentally using a clinical scanner (Somatom Definition Flash, Siemens Healthcare, Germany) with spectra provided by the manufacturer serving as the comparison standard. Results obtained with the proposed technique were compared against those obtained from a second conventional transmission measurement technique with two materials (i.e., Cu and Al). After validation, the proposed technique was applied to measure spectra from the

  8. Image reconstruction and image quality evaluation for a dual source CT scanner.

    PubMed

    Flohr, T G; Bruder, H; Stierstorfer, K; Petersilka, M; Schmidt, B; McCollough, C H

    2008-12-01

    The authors present and evaluate concepts for image reconstruction in dual source CT (DSCT). They describe both standard spiral (helical) DSCT image reconstruction and electrocardiogram (ECG)-synchronized image reconstruction. For a compact mechanical design of the DSCT, one detector (A) can cover the full scan field of view, while the other detector (B) has to be restricted to a smaller, central field of view. The authors develop an algorithm for scan data completion, extrapolating truncated data of detector (B) by using data of detector (A). They propose a unified framework for convolution and simultaneous 3D backprojection of both (A) and (B) data, with similar treatment of standard spiral, ECG-gated spiral, and sequential (axial) scan data. In ECG-synchronized image reconstruction, a flexible scan data range per measurement system can be used to trade off temporal resolution for reduced image noise. Both data extrapolation and image reconstruction are evaluated by means of computer simulated data of anthropomorphic phantoms, by phantom measurements and patient studies. The authors show that a consistent filter direction along the spiral tangent on both detectors is essential to reduce cone-beam artifacts, requiring truncation of the extrapolated (B) data after convolution in standard spiral scans. Reconstructions of an anthropomorphic thorax phantom demonstrate good image quality and dose accumulation as theoretically expected for simultaneous 3D backprojection of the filtered (A) data and the truncated filtered (B) data into the same 3D image volume. In ECG-gated spiral modes, spiral slice sensitivity profiles (SSPs) show only minor dependence on the patient's heart rate if the spiral pitch is properly adapted. Measurements with a thin gold plate phantom result in effective slice widths (full width at half maximum of the SSP) of 0.63-0.69 mm for the nominal 0.6 mm slice and 0.82-0.87 mm for the nominal 0.75 mm slice. The visually determined through-plane (z

  9. Comparing performance of many-core CPUs and GPUs for static and motion compensated reconstruction of C-arm CT data.

    PubMed

    Hofmann, Hannes G; Keck, Benjamin; Rohkohl, Christopher; Hornegger, Joachim

    2011-01-01

    Interventional reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. Hardware optimization is not an option but mandatory for interventional image processing and, in particular, for image reconstruction due to the high demands on performance. Several groups have published fast analytical 3-D reconstruction on highly parallel hardware such as GPUs to mitigate this issue. The authors show that the performance of modern CPU-based systems is in the same order as current GPUs for static 3-D reconstruction and outperforms them for a recent motion compensated (3-D+time) image reconstruction algorithm. This work investigates two algorithms: Static 3-D reconstruction as well as a recent motion compensated algorithm. The evaluation was performed using a standardized reconstruction benchmark, RABBITCT, to get comparable results and two additional clinical data sets. The authors demonstrate for a parametric B-spline motion estimation scheme that the derivative computation, which requires many write operations to memory, performs poorly on the GPU and can highly benefit from modern CPU architectures with large caches. Moreover, on a 32-core Intel Xeon server system, the authors achieve linear scaling with the number of cores used and reconstruction times almost in the same range as current GPUs. Algorithmic innovations in the field of motion compensated image reconstruction may lead to a shift back to CPUs in the future. For analytical 3-D reconstruction, the authors show that the gap between GPUs and CPUs became smaller. It can be performed in less than 20 s (on-the-fly) using a 32-core server.

  10. [Cranial CT as basis for reconstruction of events and identification of a weapon].

    PubMed

    Madea, Burkhard

    2014-01-01

    Radiological findings, especially CT scans, are of great importance in the reconstruction of events and may also be helpful to identify the weapon used. This is illustrated by a briefly survived craniocerebral trauma whose origin was controversially discussed. A 51-year-old man had suffered a severe craniocerebral trauma in a robbery. The CT scans revealed fractures of the left parietal region, among them a spider's web fracture, on the cause of which opinions differed (fall or blow). It was also unclear which of the three confiscated objects (empty wine bottle, bending iron, wooden hammer) was used for the assault. Evaluation of the CT findings showed that at least two blows had obviously been inflicted to the cranial skull. Apart from several injuries of the scalp due to blows, the typical combination of findings in the occipital region and contre-coup lesions suggested that the head had also hit the ground due to a fall. The soft tissue injuries may have been caused by all the three confiscated objects. The bony injuries were most probably caused by the bending iron, whereas the wooden hammer and the wine bottle could be ruled out as the causative weapon or were at least highly improbable.

  11. Peripheral pulmonary arteries: identification at multi-slice spiral CT with 3D reconstruction.

    PubMed

    Coche, Emmanuel; Pawlak, Sebastien; Dechambre, Stéphane; Maldague, Baudouin

    2003-04-01

    Our objective was to analyze the peripheral pulmonary arteries using thin-collimation multi-slice spiral CT. Twenty consecutive patients underwent enhanced-spiral multi-slice CT using 1-mm collimation. Two observers analyzed the pulmonary arteries by consensus on a workstation. Each artery was identified on axial and 3D shaded-surface display reconstruction images. Each subsegmental artery was measured at a mediastinal window setting and compared with anatomical classifications. The location and branching of every subsegmental artery was recorded. The number of well-visualized sub-subsegmental arteries at a mediastinal window setting was compared with those visualized at a lung window setting. Of 800 subsegmental arteries, 769 (96%) were correctly visualized and 123 accessory subsegmental arteries were identified using the mediastinal window setting. One thousand ninety-two of 2019 sub-subsegmental arteries (54%) identified using the lung window setting were correctly visualized using the mediastinal window setting. Enhanced multi-slice spiral CT with thin collimation can be used to analyze precisely the subsegmental pulmonary arteries and may identify even more distal pulmonary arteries.

  12. Cranio-orbital reconstruction: safety and image quality of metallic implants on CT and MRI scanning.

    PubMed

    Sullivan, P K; Smith, J F; Rozzelle, A A

    1994-10-01

    A study was undertaken to evaluate the safety of magnetic resonance imaging (MRI) of metallic implants used in cranio-orbital reconstruction (stainless steel wire and titanium and Vitallium plates) and also to compare the degree of artifact created on computed tomographic (CT) scanning and MRI by each material. Samples of each material were tested for deflection (movement) in a 1.5-T MRI field and for temperature change under conditions simulating a clinical MRI scan. None of the materials exhibited any deflection, and none exhibited any significant temperature change compared with water. Standardized bars of each material and commonly used, commercially available titanium and Vitallium implants (plates, mesh) were evaluated for artifact. On blinded evaluation by three radiologists and on quantitative computer analysis of the CT images, the stainless steel produced the most artifact on both CT scan and MRI, followed by the Vitallium, with the least artifact caused by titanium. All the titanium images were felt to be acceptable to detect orbital pathology, while only the images with the thinnest Vitallium (micromesh) implant were acceptable.

  13. [On the clinical application of spiral CT three-dimensional reconstruction of middle ear ossicles].

    PubMed

    Sun, Jie; Liu, Zhilian; Zhang, Hua; Gong, Ruozhen; Wang, Haibo

    2012-10-01

    To investigate the CT virtual endoscopy (CTVE) shows the display method of the normal structure of the middle ear, and evaluation of middle ear disease, particularly in the value and significance of the connection status of the ossicular chain, established display ossicular chain and middle ear structure methods. Volume scanning with a spiral CT unit was performed in forty normal cases and thirty patients with suspected lesions of middle ear. Respectively, with Germany's Siemens (Siemens SOMATOM Sensation 16) spiral CT the Inner Ear scanner patients with axial scanning, reconstruction of the original image, the software selected Fly-through A, B, C the point approach CTVE imaging studies. Focus ossicular chain connection status, and chronic otitis media shown the results of surgery in exploratory image control. Normal group CTVE in the hammer bone, incus promontory, facial nerve, the lateral semicircular canal display rate was 100%; stapes, the two arch of the display rate in three display levels, respectively, to 57.5%, 70.0%, 97.5%; round window, oval window was 90.0%, 93.0%, 97.5%. Ossicular injury, displacement, interruption, deletion, deformity in cases of otitis media, trauma, temporal bone malformations. CTVE link relations between the three ossicles (such as interrupt, etc.) have a certain advantage. By choosing the appropriate approach, CTVE has a considerable advantage in the ossicles and their connections, relations as well as pathological state. By comparing CTVE in three different display levels,the technique of CTVE is considered to be an advantageous supplement of tomography.

  14. Impact of covariance modeling in dual-energy spectral CT image reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Yan; Yu, Zhou; Zou, Yu

    2015-03-01

    Dual-energy computed tomography (DECT) is a recent advancement in CT technology, which can potentially reduce artifacts and provide accurate quantitative information for diagnosis. Recently, statistical iterative reconstruction (SIR) methods were introduced to DECT for radiation dose reduction. The statistical noise modeling of measurement data plays an important role in SIR and impacts on the image quality. Contrary to the conventional CT projection data, of which noise is independent from ray to ray, in spectral CT the basis material sinogram data has strong correlations. In order to analyze the image quality improvement by applying correlated noise model, we compare the effects of two different noise models (i.e., correlated noise model and independent model by ignoring correlations) by analyzing the bias and variance trade-off. The results indicate that in the same bias level, the correlated noise modeling results in up to 20.02% noise reduction compared to the independent noise model. In addition, their impacts to different numerical are also evaluated. The results show that using the non-diagonal covariance matrix in SIR is challenging, where some numerical algorithms such as a direct application of separable paraboloidal surrogates (SPS) cannot converge to the correct results.

  15. Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence

    NASA Astrophysics Data System (ADS)

    Niu, Tianye; Ye, Xiaojing; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei

    2014-04-01

    Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai-Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GP-BB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp-Logan phantom, UPN achieves the same image quality as those of GP-BB and the Bregman-type methods, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the filtered backprojection (FBP) results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GP-BB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and fewer iterations.

  16. Accelerated barrier optimization compressed sensing (ABOCS) for CT reconstruction with improved convergence

    PubMed Central

    Niu, Tianye; Ye, Xiaojing; Fruhauf, Quentin; Petrongolo, Michael; Zhu, Lei

    2014-01-01

    Recently, we proposed a new algorithm of accelerated barrier optimization compressed sensing (ABOCS) for iterative CT reconstruction. The previous implementation of ABOCS uses gradient projection (GP) with a Barzilai-Borwein (BB) step-size selection scheme (GP-BB) to search for the optimal solution. The algorithm does not converge stably due to its non-monotonic behavior. In this paper, we further improve the convergence of ABOCS using the unknown-parameter Nesterov (UPN) method and investigate the ABOCS reconstruction performance on clinical patient data. Comparison studies are carried out on reconstructions of computer simulation, a physical phantom and a head-and-neck patient. In all of these studies, the ABOCS results using UPN show more stable and faster convergence than those of the GPBB method and a state-of-the-art Bregman-type method. As shown in the simulation study of the Shepp-Logan phantom, UPN achieves the same image quality as those of GPBB and the Bregman-type method, but reduces the iteration numbers by up to 50% and 90%, respectively. In the Catphan©600 phantom study, a high-quality image with relative reconstruction error (RRE) less than 3% compared to the full-view result is obtained using UPN with 17% projections (60 views). In the conventional filtered-backprojection (FBP) reconstruction, the corresponding RRE is more than 15% on the same projection data. The superior performance of ABOCS with the UPN implementation is further demonstrated on the head-and-neck patient. Using 25% projections (91 views), the proposed method reduces the RRE from 21% as in the FBP results to 7.3%. In conclusion, we propose UPN for ABOCS implementation. As compared to GPBB and the Bregman-type methods, the new method significantly improves the convergence with higher stability and less iterations. PMID:24625411

  17. Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

    PubMed

    Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

    2016-01-01

    To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features.

  18. Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability

    PubMed Central

    Kim, Hyungjin; Park, Chang Min; Lee, Myunghee; Park, Sang Joon; Song, Yong Sub; Lee, Jong Hyuk; Hwang, Eui Jin; Goo, Jin Mo

    2016-01-01

    Purpose To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. Methods Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two readers independently segmented the whole tumor volume. Fifteen radiomic features were extracted and compared among reconstruction algorithms. Intra- and inter-reader variability and inter-reconstruction algorithm variability were calculated using coefficients of variation (CVs) and then compared. Results Among the 15 features, 5 first-order tumor intensity features and 4 gray level co-occurrence matrix (GLCM)-based features showed significant differences (p<0.05) among reconstruction algorithms. As for the variability, effective diameter, sphericity, entropy, and GLCM entropy were the most robust features (CV≤5%). Inter-reader variability was larger than intra-reader or inter-reconstruction algorithm variability in 9 features. However, for entropy, homogeneity, and 4 GLCM-based features, inter-reconstruction algorithm variability was significantly greater than inter-reader variability (p<0.013). Conclusions Most of the radiomic features were significantly affected by the reconstruction algorithms. Inter-reconstruction algorithm variability was greater than inter-reader variability for entropy, homogeneity, and GLCM-based features. PMID:27741289

  19. CT Radiation Dose Optimization and Estimation: an Update for Radiologists

    PubMed Central

    2012-01-01

    In keeping with the increasing utilization of CT examinations, the greater concern about radiation hazards from examinations has been addressed. In this regard, CT radiation dose optimization has been given a great deal of attention by radiologists, referring physicians, technologists, and physicists. Dose-saving strategies are continuously evolving in terms of imaging techniques as well as dose management. Consequently, regular updates of this issue are necessary especially for radiologists who play a pivotal role in this activity. This review article will provide an update on how we can optimize CT dose in order to maximize the benefit-to-risk ratio of this clinically useful diagnostic imaging method. PMID:22247630

  20. CT radiation dose optimization and estimation: an update for radiologists.

    PubMed

    Goo, Hyun Woo

    2012-01-01

    In keeping with the increasing utilization of CT examinations, the greater concern about radiation hazards from examinations has been addressed. In this regard, CT radiation dose optimization has been given a great deal of attention by radiologists, referring physicians, technologists, and physicists. Dose-saving strategies are continuously evolving in terms of imaging techniques as well as dose management. Consequently, regular updates of this issue are necessary especially for radiologists who play a pivotal role in this activity. This review article will provide an update on how we can optimize CT dose in order to maximize the benefit-to-risk ratio of this clinically useful diagnostic imaging method.

  1. Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

    PubMed

    Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

    2015-05-01

    It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Reconstruction-plane-dependent weighted FDK algorithm for cone beam volumetric CT

    NASA Astrophysics Data System (ADS)

    Tang, Xiangyang; Hsieh, Jiang

    2005-04-01

    The original FDK algorithm has been extensively employed in medical and industrial imaging applications. With an increased cone angle, cone beam (CB) artifacts in images reconstructed by the original FDK algorithm deteriorate, since the circular trajectory does not satisfy the so-called data sufficiency condition (DSC). A few "circular plus" trajectories have been proposed in the past to reduce CB artifacts by meeting the DSC. However, the circular trajectory has distinct advantages over other scanning trajectories in practical CT imaging, such as cardiac, vascular and perfusion applications. In addition to looking into the DSC, another insight into the CB artifacts of the original FDK algorithm is the inconsistency between conjugate rays that are 180° apart in view angle. The inconsistence between conjugate rays is pixel dependent, i.e., it varies dramatically over pixels within the image plane to be reconstructed. However, the original FDK algorithm treats all conjugate rays equally, resulting in CB artifacts that can be avoided if appropriate view weighting strategy is exercised. In this paper, a modified FDK algorithm is proposed, along with an experimental evaluation and verification, in which the helical body phantom and a humanoid head phantom scanned by a volumetric CT (64 x 0.625 mm) are utilized. Without extra trajectories supplemental to the circular trajectory, the modified FDK algorithm applies reconstruction-plane-dependent view weighting on projection data before 3D backprojection, which reduces the inconsistency between conjugate rays by suppressing the contribution of one of the conjugate rays with a larger cone angle. Both computer-simulated and real phantom studies show that, up to a moderate cone angle, the CB artifacts can be substantially suppressed by the modified FDK algorithm, while advantages of the original FDK algorithm, such as the filtered backprojection algorithm structure, 1D ramp filtering, and data manipulation efficiency, can be

  3. Direct reconstruction in CT-analogous pharmacokinetic diffuse fluorescence tomography: two-dimensional simulative and experimental validations

    NASA Astrophysics Data System (ADS)

    Wang, Xin; Zhang, Yanqi; Zhang, Limin; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng

    2016-04-01

    We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.

  4. Direct reconstruction in CT-analogous pharmacokinetic diffuse fluorescence tomography: two-dimensional simulative and experimental validations.

    PubMed

    Wang, Xin; Zhang, Yanqi; Zhang, Limin; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng

    2016-04-30

    We present a generalized strategy for direct reconstruction in pharmacokinetic diffuse fluorescence tomography (DFT) with CT-analogous scanning mode, which can accomplish one-step reconstruction of the indocyanine-green pharmacokinetic-rate images within in vivo small animals by incorporating the compartmental kinetic model into an adaptive extended Kalman filtering scheme and using an instantaneous sampling dataset. This scheme, compared with the established indirect and direct methods, eliminates the interim error of the DFT inversion and relaxes the expensive requirement of the instrument for obtaining highly time-resolved date-sets of complete 360 deg projections. The scheme is validated by two-dimensional simulations for the two-compartment model and pilot phantom experiments for the one-compartment model, suggesting that the proposed method can estimate the compartmental concentrations and the pharmacokinetic-rates simultaneously with a fair quantitative and localization accuracy, and is well suitable for cost-effective and dense-sampling instrumentation based on the highly-sensitive photon counting technique.

  5. Mapping the nasal airways: using histology to enhance CT-based three-dimensional reconstruction in Nycticebus.

    PubMed

    Deleon, Valerie Burke; Smith, Timothy D

    2014-11-01

    Three-dimensional reconstructions of imaging data are an increasingly common approach for studying anatomical structure. However, certain aspects of anatomy, including microscopic structure and differentiating tissue types, continue to benefit from traditional histological analyses. We present here a detailed methodology for combining data from microCT and histological imaging to create 3D virtual reconstructions for visualization and further analyses. We used this approach to study the distribution of olfactory mucosa on ethmoturbinal I of an adult pygmy slow loris, Nycticebus pygmaeus. MicroCT imaging of the specimen was followed by processing, embedding, and sectioning for histological analysis. We identified corresponding