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Sample records for 4d image reconstruction

  1. Improved image quality and computation reduction in 4-D reconstruction of cardiac-gated SPECT images.

    PubMed

    Narayanan, M V; King, M A; Wernick, M N; Byrne, C L; Soares, E J; Pretorius, P H

    2000-05-01

    Spatiotemporal reconstruction of cardiac-gated SPECT images permits us to obtain valuable information related to cardiac function. However, the task of reconstructing this four-dimensional (4-D) data set is computation intensive. Typically, these studies are reconstructed frame-by-frame: a nonoptimal approach because temporal correlations in the signal are not accounted for. In this work, we show that the compression and signal decorrelation properties of the Karhunen-Loève (KL) transform may be used to greatly simplify the spatiotemporal reconstruction problem. The gated projections are first KL transformed in the temporal direction. This results in a sequence of KL-transformed projection images for which the signal components are uncorrelated along the time axis. As a result, the 4-D reconstruction task is simplified to a series of three-dimensional (3-D) reconstructions in the KL domain. The reconstructed KL components are subsequently inverse KL transformed to obtain the entire spatiotemporal reconstruction set. Our simulation and clinical results indicate that KL processing provides image sequences that are less noisy than are conventional frame-by-frame reconstructions. Additionally, by discarding high-order KL components that are dominated by noise, we can achieve savings in computation time because fewer reconstructions are needed in comparison to conventional frame-by-frame reconstructions.

  2. 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

  3. Constrain static target kinetic iterative image reconstruction for 4D cardiac CT imaging

    NASA Astrophysics Data System (ADS)

    Alessio, Adam M.; La Riviere, Patrick J.

    2011-03-01

    Iterative image reconstruction offers improved signal to noise properties for CT imaging. A primary challenge with iterative methods is the substantial computation time. This computation time is even more prohibitive in 4D imaging applications, such as cardiac gated or dynamic acquisition sequences. In this work, we propose only updating the time-varying elements of a 4D image sequence while constraining the static elements to be fixed or slowly varying in time. We test the method with simulations of 4D acquisitions based on measured cardiac patient data from a) a retrospective cardiac-gated CT acquisition and b) a dynamic perfusion CT acquisition. We target the kinetic elements with one of two methods: 1) position a circular ROI on the heart, assuming area outside ROI is essentially static throughout imaging time; and 2) select varying elements from the coefficient of variation image formed from fast analytic reconstruction of all time frames. Targeted kinetic elements are updated with each iteration, while static elements remain fixed at initial image values formed from the reconstruction of data from all time frames. Results confirm that the computation time is proportional to the number of targeted elements; our simulations suggest that <30% of elements need to be updated in each frame leading to >3 times reductions in reconstruction time. The images reconstructed with the proposed method have matched mean square error with full 4D reconstruction. The proposed method is amenable to most optimization algorithms and offers the potential for significant computation improvements, which could be traded off for more sophisticated system models or penalty terms.

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

    NASA Astrophysics Data System (ADS)

    Wang, Jing; Gu, Xuejun

    2014-03-01

    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 4DCBCT. 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). 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 (SART) technique coupled with total variation minimization. During the forward- and back-projection 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 SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.

  5. Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR).

    PubMed

    Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

    2016-08-01

    In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET. PMID:27385378

  6. Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

    NASA Astrophysics Data System (ADS)

    Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

    2016-08-01

    In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

  7. Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR).

    PubMed

    Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

    2016-08-01

    In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10-40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

  8. Respiratory motion correction in 4D-PET by simultaneous motion estimation and image reconstruction (SMEIR)

    NASA Astrophysics Data System (ADS)

    Kalantari, Faraz; Li, Tianfang; Jin, Mingwu; Wang, Jing

    2016-08-01

    In conventional 4D positron emission tomography (4D-PET), images from different frames are reconstructed individually and aligned by registration methods. Two issues that arise with this approach are as follows: (1) the reconstruction algorithms do not make full use of projection statistics; and (2) the registration between noisy images can result in poor alignment. In this study, we investigated the use of simultaneous motion estimation and image reconstruction (SMEIR) methods for motion estimation/correction in 4D-PET. A modified ordered-subset expectation maximization algorithm coupled with total variation minimization (OSEM-TV) was used to obtain a primary motion-compensated PET (pmc-PET) from all projection data, using Demons derived deformation vector fields (DVFs) as initial motion vectors. A motion model update was performed to obtain an optimal set of DVFs in the pmc-PET and other phases, by matching the forward projection of the deformed pmc-PET with measured projections from other phases. The OSEM-TV image reconstruction was repeated using updated DVFs, and new DVFs were estimated based on updated images. A 4D-XCAT phantom with typical FDG biodistribution was generated to evaluate the performance of the SMEIR algorithm in lung and liver tumors with different contrasts and different diameters (10–40 mm). The image quality of the 4D-PET was greatly improved by the SMEIR algorithm. When all projections were used to reconstruct 3D-PET without motion compensation, motion blurring artifacts were present, leading up to 150% tumor size overestimation and significant quantitative errors, including 50% underestimation of tumor contrast and 59% underestimation of tumor uptake. Errors were reduced to less than 10% in most images by using the SMEIR algorithm, showing its potential in motion estimation/correction in 4D-PET.

  9. 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

  10. Fully 4D motion-compensated reconstruction of cardiac SPECT images

    NASA Astrophysics Data System (ADS)

    Gravier, Erwan; Yang, Yongyi; King, Michael A.; Jin, Mingwu

    2006-09-01

    In this paper, we investigate the benefits of a spatiotemporal approach for reconstruction of image sequences. In the proposed approach, we introduce a temporal prior in the form of motion compensation to account for the statistical correlations among the frames in a sequence, and reconstruct all the frames collectively as a single function of space and time. The reconstruction algorithm is derived based on the maximum a posteriori estimate, for which the one-step late expectation-maximization algorithm is used. We demonstrated the method in our experiments using simulated single photon emission computed tomography (SPECT) cardiac perfusion images. The four-dimensional (4D) gated mathematical cardiac-torso phantom was used for simulation of gated SPECT perfusion imaging with Tc-99m-sestamibi. In addition to bias-variance analysis and time activity curves, we also used a channelized Hotelling observer to evaluate the detectability of perfusion defects in the reconstructed images. Our experimental results demonstrated that the incorporation of temporal regularization into image reconstruction could significantly improve the accuracy of cardiac images without causing any significant cross-frame blurring that may arise from the cardiac motion. This could lead to not only improved detection of perfusion defects, but also improved reconstruction of the heart wall which is important for functional assessment of the myocardium. This work was supported in part by the National Institutes of Health under grant no HL65425.

  11. [Super-resolution reconstruction of lung 4D-CT images based on fast sub-pixel motion estimation].

    PubMed

    Xiao, Shan; Wang, Tingting; Lü, Qingwen; Zhang, Yu

    2015-07-01

    Super-resolution image reconstruction techniques play an important role for improving image resolution of lung 4D-CT. We presents a super-resolution approach based on fast sub-pixel motion estimation to reconstruct lung 4D-CT images. A fast sub-pixel motion estimation method was used to estimate the deformation fields between "frames", and then iterative back projection (IBP) algorithm was employed to reconstruct high-resolution images. Experimental results showed that compared with traditional interpolation method and super-resolution reconstruction algorithm based on full search motion estimation, the proposed method produced clearer images with significantly enhanced image structure details and reduced time for computation.

  12. Application of adaptive kinetic modelling for bias propagation reduction in direct 4D image reconstruction

    NASA Astrophysics Data System (ADS)

    Kotasidis, F. A.; Matthews, J. C.; Reader, A. J.; Angelis, G. I.; Zaidi, H.

    2014-10-01

    Parametric imaging in thoracic and abdominal PET can provide additional parameters more relevant to the pathophysiology of the system under study. However, dynamic data in the body are noisy due to the limiting counting statistics leading to suboptimal kinetic parameter estimates. Direct 4D image reconstruction algorithms can potentially improve kinetic parameter precision and accuracy in dynamic PET body imaging. However, construction of a common kinetic model is not always feasible and in contrast to post-reconstruction kinetic analysis, errors in poorly modelled regions may spatially propagate to regions which are well modelled. To reduce error propagation from erroneous model fits, we implement and evaluate a new approach to direct parameter estimation by incorporating a recently proposed kinetic modelling strategy within a direct 4D image reconstruction framework. The algorithm uses a secondary more general model to allow a less constrained model fit in regions where the kinetic model does not accurately describe the underlying kinetics. A portion of the residuals then is adaptively included back into the image whilst preserving the primary model characteristics in other well modelled regions using a penalty term that trades off the models. Using fully 4D simulations based on dynamic [15O]H2O datasets, we demonstrate reduction in propagation-related bias for all kinetic parameters. Under noisy conditions, reductions in bias due to propagation are obtained at the cost of increased noise, which in turn results in increased bias and variance of the kinetic parameters. This trade-off reflects the challenge of separating the residuals arising from poor kinetic modelling fits from the residuals arising purely from noise. Nonetheless, the overall root mean square error is reduced in most regions and parameters. Using the adaptive 4D image reconstruction improved model fits can be obtained in poorly modelled regions, leading to reduced errors potentially propagating

  13. 5D respiratory motion model based image reconstruction algorithm for 4D cone-beam computed tomography

    NASA Astrophysics Data System (ADS)

    Liu, Jiulong; Zhang, Xue; Zhang, Xiaoqun; Zhao, Hongkai; Gao, Yu; Thomas, David; Low, Daniel A.; Gao, Hao

    2015-11-01

    4D cone-beam computed tomography (4DCBCT) reconstructs a temporal sequence of CBCT images for the purpose of motion management or 4D treatment in radiotherapy. However the image reconstruction often involves the binning of projection data to each temporal phase, and therefore suffers from deteriorated image quality due to inaccurate or uneven binning in phase, e.g., under the non-periodic breathing. A 5D model has been developed as an accurate model of (periodic and non-periodic) respiratory motion. That is, given the measurements of breathing amplitude and its time derivative, the 5D model parametrizes the respiratory motion by three time-independent variables, i.e., one reference image and two vector fields. In this work we aim to develop a new 4DCBCT reconstruction method based on 5D model. Instead of reconstructing a temporal sequence of images after the projection binning, the new method reconstructs time-independent reference image and vector fields with no requirement of binning. The image reconstruction is formulated as a optimization problem with total-variation regularization on both reference image and vector fields, and the problem is solved by the proximal alternating minimization algorithm, during which the split Bregman method is used to reconstruct the reference image, and the Chambolle's duality-based algorithm is used to reconstruct the vector fields. The convergence analysis of the proposed algorithm is provided for this nonconvex problem. Validated by the simulation studies, the new method has significantly improved image reconstruction accuracy due to no binning and reduced number of unknowns via the use of the 5D model.

  14. Constrained reconstructions for 4D intervention guidance.

    PubMed

    Kuntz, J; Flach, B; Kueres, R; Semmler, W; Kachelriess, M; Bartling, S

    2013-05-21

    Image-guided interventions are an increasingly important part of clinical minimally invasive procedures. However, up to now they cannot be performed under 4D (3D + time) guidance due to the exceedingly high x-ray dose. In this work we investigate the applicability of compressed sensing reconstructions for highly undersampled CT datasets combined with the incorporation of prior images in order to yield low dose 4D intervention guidance. We present a new reconstruction scheme prior image dynamic interventional CT (PrIDICT) that accounts for specific image features in intervention guidance and compare it to PICCS and ASD-POCS. The optimal parameters for the dose per projection and the numbers of projections per reconstruction are determined in phantom simulations and measurements. In vivo experiments in six pigs are performed in a cone-beam CT; measured doses are compared to current gold-standard intervention guidance represented by a clinical fluoroscopy system. Phantom studies show maximum image quality for identical overall doses in the range of 14 to 21 projections per reconstruction. In vivo studies reveal that interventional materials can be followed in 4D visualization and that PrIDICT, compared to PICCS and ASD-POCS, shows superior reconstruction results and fewer artifacts in the periphery with dose in the order of biplane fluoroscopy. These results suggest that 4D intervention guidance can be realized with today's flat detector and gantry systems using the herein presented reconstruction scheme.

  15. Constrained reconstructions for 4D intervention guidance

    NASA Astrophysics Data System (ADS)

    Kuntz, J.; Flach, B.; Kueres, R.; Semmler, W.; Kachelrieß, M.; Bartling, S.

    2013-05-01

    Image-guided interventions are an increasingly important part of clinical minimally invasive procedures. However, up to now they cannot be performed under 4D (3D + time) guidance due to the exceedingly high x-ray dose. In this work we investigate the applicability of compressed sensing reconstructions for highly undersampled CT datasets combined with the incorporation of prior images in order to yield low dose 4D intervention guidance. We present a new reconstruction scheme prior image dynamic interventional CT (PrIDICT) that accounts for specific image features in intervention guidance and compare it to PICCS and ASD-POCS. The optimal parameters for the dose per projection and the numbers of projections per reconstruction are determined in phantom simulations and measurements. In vivo experiments in six pigs are performed in a cone-beam CT; measured doses are compared to current gold-standard intervention guidance represented by a clinical fluoroscopy system. Phantom studies show maximum image quality for identical overall doses in the range of 14 to 21 projections per reconstruction. In vivo studies reveal that interventional materials can be followed in 4D visualization and that PrIDICT, compared to PICCS and ASD-POCS, shows superior reconstruction results and fewer artifacts in the periphery with dose in the order of biplane fluoroscopy. These results suggest that 4D intervention guidance can be realized with today’s flat detector and gantry systems using the herein presented reconstruction scheme.

  16. Advanced image reconstruction strategies for 4D prostate DCE-MRI: steps toward clinical practicality

    NASA Astrophysics Data System (ADS)

    Stinson, Eric G.; Borisch, Eric A.; Froemming, Adam T.; Kawashima, Akira; Young, Phillip M.; Warndahl, Brent A.; Grimm, Roger C.; Manduca, Armando; Riederer, Stephen J.; Trzasko, Joshua D.

    2015-09-01

    Dynamic contrast-enhanced (DCE) MRI is an important tool for the detection and characterization of primary and recurring prostate cancer. Advanced reconstruction strategies (e.g., sparse or low-rank regression) provide improved depiction of contrast dynamics and pharmacokinetic parameters; however, the high computation cost of reconstructing 4D (3D+time, 50+ frames) datasets typically inhibits their routine clinical use. Here, a novel alternating direction method-of-multipliers (ADMM) optimization strategy is described that enables these methods to be executed in ∠5 minutes, and thus within the standard clinical workflow. After overviewing the mechanics of this approach, high-performance implementation strategies will be discussed and demonstrated through clinical cases.

  17. Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation–maximization reconstruction

    NASA Astrophysics Data System (ADS)

    Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

    2016-08-01

    Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation–maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10–20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were

  18. Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

    NASA Astrophysics Data System (ADS)

    Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

    2016-08-01

    Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were

  19. Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction.

    PubMed

    Karakatsanis, Nicolas A; Casey, Michael E; Lodge, Martin A; Rahmim, Arman; Zaidi, Habib

    2016-08-01

    Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible (18)F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published (18)F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were

  20. SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

    SciTech Connect

    Kim, D; Kang, S; Kim, T; Suh, T; Kim, S

    2014-06-01

    Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studies to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)

  1. 4D reconstruction of the past: the image retrieval and 3D model construction pipeline

    NASA Astrophysics Data System (ADS)

    Hadjiprocopis, Andreas; Ioannides, Marinos; Wenzel, Konrad; Rothermel, Mathias; Johnsons, Paul S.; Fritsch, Dieter; Doulamis, Anastasios; Protopapadakis, Eftychios; Kyriakaki, Georgia; Makantasis, Kostas; Weinlinger, Guenther; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro

    2014-08-01

    One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.

  2. Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution.

    PubMed

    Fernandez, Romain; Das, Pradeep; Mirabet, Vincent; Moscardi, Eric; Traas, Jan; Verdeil, Jean-Luc; Malandain, Grégoire; Godin, Christophe

    2010-07-01

    Quantitative information on growing organs is required to better understand morphogenesis in both plants and animals. However, detailed analyses of growth patterns at cellular resolution have remained elusive. We developed an approach, multiangle image acquisition, three-dimensional reconstruction and cell segmentation-automated lineage tracking (MARS-ALT), in which we imaged whole organs from multiple angles, computationally merged and segmented these images to provide accurate cell identification in three dimensions and automatically tracked cell lineages through multiple rounds of cell division during development. Using these methods, we quantitatively analyzed Arabidopsis thaliana flower development at cell resolution, which revealed differential growth patterns of key regions during early stages of floral morphogenesis. Lastly, using rice roots, we demonstrated that this approach is both generic and scalable.

  3. Imaging plant growth in 4D: robust tissue reconstruction and lineaging at cell resolution.

    PubMed

    Fernandez, Romain; Das, Pradeep; Mirabet, Vincent; Moscardi, Eric; Traas, Jan; Verdeil, Jean-Luc; Malandain, Grégoire; Godin, Christophe

    2010-07-01

    Quantitative information on growing organs is required to better understand morphogenesis in both plants and animals. However, detailed analyses of growth patterns at cellular resolution have remained elusive. We developed an approach, multiangle image acquisition, three-dimensional reconstruction and cell segmentation-automated lineage tracking (MARS-ALT), in which we imaged whole organs from multiple angles, computationally merged and segmented these images to provide accurate cell identification in three dimensions and automatically tracked cell lineages through multiple rounds of cell division during development. Using these methods, we quantitatively analyzed Arabidopsis thaliana flower development at cell resolution, which revealed differential growth patterns of key regions during early stages of floral morphogenesis. Lastly, using rice roots, we demonstrated that this approach is both generic and scalable. PMID:20543845

  4. Online 4d Reconstruction Using Multi-Images Available Under Open Access

    NASA Astrophysics Data System (ADS)

    Ioannides, M.; Hadjiprocopi, A.; Doulamis, N.; Doulamis, A.; Protopapadakis, E.; Makantasis, K.; Santos, P.; Fellner, D.; Stork, A.; Balet, O.; Julien, M.; Weinlinger, G.; Johnson, P. S.; Klein, M.; Fritsch, D.

    2013-07-01

    The advent of technology in digital cameras and their incorporation into virtually any smart mobile device has led to an explosion of the number of photographs taken every day. Today, the number of images stored online and available freely has reached unprecedented levels. It is estimated that in 2011, there were over 100 billion photographs stored in just one of the major social media sites. This number is growing exponentially. Moreover, advances in the fields of Photogrammetry and Computer Vision have led to significant breakthroughs such as the Structure from Motion algorithm which creates 3D models of objects using their twodimensional photographs. The existence of powerful and affordable computational machinery not only the reconstruction of complex structures but also entire cities. This paper illustrates an overview of our methodology for producing 3D models of Cultural Heritage structures such as monuments and artefacts from 2D data (pictures, video), available on Internet repositories, social media, Google Maps, Bing, etc. We also present new approaches to semantic enrichment of the end results and their subsequent export to Europeana, the European digital library, for integrated, interactive 3D visualisation within regular web browsers using WebGl and X3D. Our main goal is to enable historians, architects, archaeologists, urban planners and affiliated professionals to reconstruct views of historical structures from millions of images floating around the web and interact with them.

  5. Common-mask guided image reconstruction (c-MGIR) for enhanced 4D cone-beam computed tomography

    NASA Astrophysics Data System (ADS)

    Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Li, Jonathan G.; Liu, Chihray; Lu, Bo

    2015-12-01

    Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm ‘the common mask guided image reconstruction’ (c-MGIR). In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and ‘well’ solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the

  6. SU-E-J-153: Reconstructing 4D Cone Beam CT Images for Clinical QA of Lung SABR Treatments

    SciTech Connect

    Beaudry, J; Bergman, A; Cropp, R

    2015-06-15

    Purpose: To verify that the planned Primary Target Volume (PTV) and Internal Gross Tumor Volume (IGTV) fully enclose a moving lung tumor volume as visualized on a pre-SABR treatment verification 4D Cone Beam CT. Methods: Daily 3DCBCT image sets were acquired immediately prior to treatment for 10 SABR lung patients using the on-board imaging system integrated into a Varian TrueBeam (v1.6: no 4DCBCT module available). Respiratory information was acquired during the scan using the Varian RPM system. The CBCT projections were sorted into 8 bins offline, both by breathing phase and amplitude, using in-house software. An iterative algorithm based on total variation minimization, implemented in the open source reconstruction toolkit (RTK), was used to reconstruct the binned projections into 4DCBCT images. The relative tumor motion was quantified by tracking the centroid of the tumor volume from each 4DCBCT image. Following CT-CBCT registration, the planning CT volumes were compared to the location of the CBCT tumor volume as it moves along its breathing trajectory. An overlap metric quantified the ability of the planned PTV and IGTV to contain the tumor volume at treatment. Results: The 4DCBCT reconstructed images visibly show the tumor motion. The mean overlap between the planned PTV (IGTV) and the 4DCBCT tumor volumes was 100% (94%), with an uncertainty of 5% from the 4DCBCT tumor volume contours. Examination of the tumor motion and overlap metric verify that the IGTV drawn at the planning stage is a good representation of the tumor location at treatment. Conclusion: It is difficult to compare GTV volumes from a 4DCBCT and a planning CT due to image quality differences. However, it was possible to conclude the GTV remained within the PTV 100% of the time thus giving the treatment staff confidence that SABR lung treatements are being delivered accurately.

  7. Advances in 4D radiation therapy for managing respiration: part I - 4D imaging.

    PubMed

    Hugo, Geoffrey D; Rosu, Mihaela

    2012-12-01

    Techniques for managing respiration during imaging and planning of radiation therapy are reviewed, concentrating on free-breathing (4D) approaches. First, we focus on detailing the historical development and basic operational principles of currently-available "first generation" 4D imaging modalities: 4D computed tomography, 4D cone beam computed tomography, 4D magnetic resonance imaging, and 4D positron emission tomography. Features and limitations of these first generation systems are described, including necessity of breathing surrogates for 4D image reconstruction, assumptions made in acquisition and reconstruction about the breathing pattern, and commonly-observed artifacts. Both established and developmental methods to deal with these limitations are detailed. Finally, strategies to construct 4D targets and images and, alternatively, to compress 4D information into static targets and images for radiation therapy planning are described.

  8. Advances in 4D Radiation Therapy for Managing Respiration: Part I – 4D Imaging

    PubMed Central

    Hugo, Geoffrey D.; Rosu, Mihaela

    2014-01-01

    Techniques for managing respiration during imaging and planning of radiation therapy are reviewed, concentrating on free-breathing (4D) approaches. First, we focus on detailing the historical development and basic operational principles of currently-available “first generation” 4D imaging modalities: 4D computed tomography, 4D cone beam computed tomography, 4D magnetic resonance imaging, and 4D positron emission tomography. Features and limitations of these first generation systems are described, including necessity of breathing surrogates for 4D image reconstruction, assumptions made in acquisition and reconstruction about the breathing pattern, and commonly-observed artifacts. Both established and developmental methods to deal with these limitations are detailed. Finally, strategies to construct 4D targets and images and, alternatively, to compress 4D information into static targets and images for radiation therapy planning are described. PMID:22784929

  9. 4-D reconstruction for dynamic fluorescence diffuse optical tomography.

    PubMed

    Liu, Xin; Zhang, Bin; Luo, Jianwen; Bai, Jing

    2012-11-01

    Dynamic fluorescence diffuse optical tomography (FDOT) is important for the research of drug delivery, medical diagnosis and treatment. Conventionally, dynamic tomographic images are reconstructed frame by frame, independently. This approach fails to account for the temporal correlations in measurement data. Ideally, the entire image sequence should be considered as a whole and a four-dimensional (4-D) reconstruction should be performed. However, the fully 4-D reconstruction is computationally intensive. In this paper, we propose a new 4-D reconstruction approach for dynamic FDOT, which is achieved by applying a temporal Karhunen-Loève (KL) transformation to the imaging equation. By taking advantage of the decorrelation and compression properties of the KL transformation, the complex 4-D optical reconstruction problem is greatly simplified. To evaluate the performance of the method, simulation, phantom, and in vivo experiments (N=7) are performed on a hybrid FDOT/x-ray computed tomography imaging system. The experimental results indicate that the reconstruction images obtained by the KL method provide good reconstruction quality. Additionally, by discarding high-order KL components, the computation time involved with fully 4-D reconstruction can be greatly reduced in contrast to the conventional frame-by-frame reconstruction.

  10. Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

    SciTech Connect

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

    2014-04-15

    Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

  11. Impact of scanning parameters and breathing patterns on image quality and accuracy of tumor motion reconstruction in 4D CBCT: a phantom study.

    PubMed

    Lee, Soyoung; Yan, Guanghua; Lu, Bo; Kahler, Darren; Li, Jonathan G; Sanjiv, Samat S

    2015-01-01

    Four-dimensional, cone-beam CT (4D CBCT) substantially reduces respiration-induced motion blurring artifacts in three-dimension (3D) CBCT. However, the image quality of 4D CBCT is significantly degraded which may affect its accuracy in localizing a mobile tumor for high-precision, image-guided radiation therapy (IGRT). The purpose of this study was to investigate the impact of scanning parameters hereinafter collectively referred to as scanning sequence) and breathing patterns on the image quality and the accuracy of computed tumor trajectory for a commercial 4D CBCT system, in preparation for its clinical implementation. We simulated a series of periodic and aperiodic sinusoidal breathing patterns with a respiratory motion phantom. The aperiodic pattern was created by varying the period or amplitude of individual sinusoidal breathing cycles. 4D CBCT scans of the phantom were acquired with a manufacturer-supplied scanning sequence (4D-S-slow) and two in-house modified scanning sequences (4D-M-slow and 4D-M-fast). While 4D-S-slow used small field of view (FOV), partial rotation (200°), and no imaging filter, 4D-M-slow and 4D-M-fast used medium FOV, full rotation, and the F1 filter. The scanning speed was doubled in 4D-M-fast (100°/min gantry rotation). The image quality of the 4D CBCT scans was evaluated using contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and motion blurring ratio (MBR). The trajectory of the moving target was reconstructed by registering each phase of the 4D CBCT with a reference CT. The root-mean-squared-error (RMSE) analysis was used to quantify its accuracy. Significant decrease in CNR and SNR from 3D CBCT to 4D CBCT was observed. The 4D-S-slow and 4D-M-fast scans had comparable image quality, while the 4D-M-slow scans had better performance due to doubled projections. Both CNR and SNR decreased slightly as the breathing period increased, while no dependence on the amplitude was observed. The difference of both CNR and SNR

  12. Task-based evaluation of a 4D MAP-RBI-EM image reconstruction method for gated myocardial perfusion SPECT using a human observer study

    NASA Astrophysics Data System (ADS)

    Lee, Taek-Soo; Higuchi, Takahiro; Lautamäki, Riikka; Bengel, Frank M.; Tsui, Benjamin M. W.

    2015-09-01

    We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion

  13. Task-based evaluation of a 4D MAP-RBI-EM image reconstruction method for gated myocardial perfusion SPECT using a human observer study.

    PubMed

    Lee, Taek-Soo; Higuchi, Takahiro; Lautamäki, Riikka; Bengel, Frank M; Tsui, Benjamin M W

    2015-09-01

    We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion

  14. Task-Based Evaluation of a 4D MAP-RBI-EM Image Reconstruction Method for Gated Myocardial Perfusion SPECT using a Human Observer Study

    PubMed Central

    Lee, Taek-Soo; Higuchi, Takahiro; Lautamäki, Riikka; Bengel, Frank M.; Tsui, Benjamin M. W.

    2015-01-01

    We evaluated the performance of a new 4D image reconstruction method for improved 4D gated myocardial perfusion (MP) SPECT using a task-based human observer study. We used a realistic 4D NURBS-based Cardiac-Torso (NCAT) phantom that models cardiac beating motion. Half of the population was normal; the other half had a regional hypokinetic wall motion abnormality. Noise-free and noisy projection data with 16 gates/cardiac cycle were generated using an analytical projector that included the effects of attenuation, collimator-detector response, and scatter (ADS), and were reconstructed using the 3D FBP without and 3D OS-EM with ADS corrections followed by different cut-off frequencies of a 4D linear post-filter. A 4D iterative maximum a posteriori rescaled-block (MAP-RBI)-EM image reconstruction method with ADS corrections was also used to reconstruct the projection data using various values of the weighting factor for its prior. The trade-offs between bias and noise were represented by the normalized mean squared error (NMSE) and averaged normalized standard deviation (NSDav), respectively. They were used to select reasonable ranges of the reconstructed images for use in a human observer study. The observers were trained with the simulated cine images and were instructed to rate their confidence on the absence or presence of a motion defect on a continuous scale. We then applied receiver operating characteristic (ROC) analysis and used the area under the ROC curve (AUC) index. The results showed that significant differences in detection performance among the different NMSE-NSDav combinations were found and the optimal trade-off from optimized reconstruction parameters corresponded to a maximum AUC value. The 4D MAP-RBI-EM with ADS correction, which had the best trade-off among the tested reconstruction methods, also had the highest AUC value, resulting in significantly better human observer detection performance when detecting regional myocardial wall motion

  15. Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data.

    PubMed

    Kotasidis, F A; Mehranian, A; Zaidi, H

    2016-05-01

    Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image

  16. Impact of time-of-flight on indirect 3D and direct 4D parametric image reconstruction in the presence of inconsistent dynamic PET data

    NASA Astrophysics Data System (ADS)

    Kotasidis, F. A.; Mehranian, A.; Zaidi, H.

    2016-05-01

    Kinetic parameter estimation in dynamic PET suffers from reduced accuracy and precision when parametric maps are estimated using kinetic modelling following image reconstruction of the dynamic data. Direct approaches to parameter estimation attempt to directly estimate the kinetic parameters from the measured dynamic data within a unified framework. Such image reconstruction methods have been shown to generate parametric maps of improved precision and accuracy in dynamic PET. However, due to the interleaving between the tomographic and kinetic modelling steps, any tomographic or kinetic modelling errors in certain regions or frames, tend to spatially or temporally propagate. This results in biased kinetic parameters and thus limits the benefits of such direct methods. Kinetic modelling errors originate from the inability to construct a common single kinetic model for the entire field-of-view, and such errors in erroneously modelled regions could spatially propagate. Adaptive models have been used within 4D image reconstruction to mitigate the problem, though they are complex and difficult to optimize. Tomographic errors in dynamic imaging on the other hand, can originate from involuntary patient motion between dynamic frames, as well as from emission/transmission mismatch. Motion correction schemes can be used, however, if residual errors exist or motion correction is not included in the study protocol, errors in the affected dynamic frames could potentially propagate either temporally, to other frames during the kinetic modelling step or spatially, during the tomographic step. In this work, we demonstrate a new strategy to minimize such error propagation in direct 4D image reconstruction, focusing on the tomographic step rather than the kinetic modelling step, by incorporating time-of-flight (TOF) within a direct 4D reconstruction framework. Using ever improving TOF resolutions (580 ps, 440 ps, 300 ps and 160 ps), we demonstrate that direct 4D TOF image

  17. SU-E-J-74: Impact of Respiration-Correlated Image Quality On Tumor Motion Reconstruction in 4D-CBCT: A Phantom Study

    SciTech Connect

    Lee, S; Lu, B; Samant, S

    2014-06-01

    Purpose: To investigate the effects of scanning parameters and respiratory patterns on the image quality for 4-dimensional cone-beam computed tomography(4D-CBCT) imaging, and assess the accuracy of computed tumor trajectory for lung imaging using registration of phased 4D-CBCT imaging with treatment planning-CT. Methods: We simulated a periodic and non-sinusoidal respirations with various breathing periods and amplitudes using a respiratory phantom(Quasar, Modus Medical Devices Inc) to acquire respiration-correlated 4D-CBCT images. 4D-CBCT scans(Elekta Oncology Systems Ltd) were performed with different scanning parameters for collimation size(e.g., small and medium field-of-views) and scanning speed(e.g., slow 50°·min{sup −1}, fast 100°·min{sup −1}). Using a standard CBCT-QA phantom(Catphan500, The Phantom Laboratory), the image qualities of all phases in 4D-CBCT were evaluated with contrast-to-noise ratio(CNR) for lung tissue and uniformity in each module. Using a respiratory phantom, the target imaging in 4D-CBCT was compared to 3D-CBCT target image. The target trajectory from 10-respiratory phases in 4D-CBCT was extracted using an automatic image registration and subsequently assessed the accuracy by comparing with actual motion of the target. Results: Image analysis indicated that a short respiration with a small amplitude resulted in superior CNR and uniformity. Smaller variation of CNR and uniformity was present amongst different respiratory phases. The small field-of-view with a partial scan using slow scan can improve CNR, but degraded uniformity. Large amplitude of respiration can degrade image quality. RMS of voxel densities in tumor area of 4D-CBCT images between sinusoidal and non-sinusoidal motion exhibited no significant difference. The maximum displacement errors of motion trajectories were less than 1.0 mm and 13.5 mm, for sinusoidal and non-sinusoidal breathings, respectively. The accuracy of motion reconstruction showed good overall

  18. Non-rigid dual respiratory and cardiac motion correction methods after, during, and before image reconstruction for 4D cardiac PET

    NASA Astrophysics Data System (ADS)

    Feng, Tao; Wang, Jizhe; Fung, George; Tsui, Benjamin

    2016-01-01

    Respiratory motion (RM) and cardiac motion (CM) degrade the quality and resolution in cardiac PET scans. We have developed non-rigid motion estimation methods to estimate both RM and CM based on 4D cardiac gated PET data alone, and compensate the dual respiratory and cardiac (R&C) motions after (MCAR), during (MCDR), and before (MCBR) image reconstruction. In all three R&C motion correction methods, attenuation-activity mismatch effect was modeled by using transformed attenuation maps using the estimated RM. The difference of using activity preserving and non-activity preserving models in R&C correction was also studied. Realistic Monte Carlo simulated 4D cardiac PET data using the 4D XCAT phantom and accurate models of the scanner design parameters and performance characteristics at different noise levels were employed as the known truth and for method development and evaluation. Results from the simulation study suggested that all three dual R&C motion correction methods provide substantial improvement in the quality of 4D cardiac gated PET images as compared with no motion correction. Specifically, the MCDR method yields the best performance for all different noise levels compared with the MCAR and MCBR methods. While MCBR reduces computational time dramatically but the resultant 4D cardiac gated PET images has overall inferior image quality when compared to that from the MCAR and MCDR approaches in the ‘almost’ noise free case. Also, the MCBR method has better noise handling properties when compared with MCAR and provides better quantitative results in high noise cases. When the goal is to reduce scan time or patient radiation dose, MCDR and MCBR provide a good compromise between image quality and computational times.

  19. Non-rigid dual respiratory and cardiac motion correction methods after, during, and before image reconstruction for 4D cardiac PET.

    PubMed

    Feng, Tao; Wang, Jizhe; Fung, George; Tsui, Benjamin

    2016-01-01

    Respiratory motion (RM) and cardiac motion (CM) degrade the quality and resolution in cardiac PET scans. We have developed non-rigid motion estimation methods to estimate both RM and CM based on 4D cardiac gated PET data alone, and compensate the dual respiratory and cardiac (R&C) motions after (MCAR), during (MCDR), and before (MCBR) image reconstruction. In all three R&C motion correction methods, attenuation-activity mismatch effect was modeled by using transformed attenuation maps using the estimated RM. The difference of using activity preserving and non-activity preserving models in R&C correction was also studied. Realistic Monte Carlo simulated 4D cardiac PET data using the 4D XCAT phantom and accurate models of the scanner design parameters and performance characteristics at different noise levels were employed as the known truth and for method development and evaluation. Results from the simulation study suggested that all three dual R&C motion correction methods provide substantial improvement in the quality of 4D cardiac gated PET images as compared with no motion correction. Specifically, the MCDR method yields the best performance for all different noise levels compared with the MCAR and MCBR methods. While MCBR reduces computational time dramatically but the resultant 4D cardiac gated PET images has overall inferior image quality when compared to that from the MCAR and MCDR approaches in the 'almost' noise free case. Also, the MCBR method has better noise handling properties when compared with MCAR and provides better quantitative results in high noise cases. When the goal is to reduce scan time or patient radiation dose, MCDR and MCBR provide a good compromise between image quality and computational times.

  20. Direct 4D PET MLEM reconstruction of parametric images using the simplified reference tissue model with the basis function method for [¹¹C]raclopride.

    PubMed

    Gravel, Paul; Reader, Andrew J

    2015-06-01

    This work assesses the one-step late maximum likelihood expectation maximization (OSL-MLEM) 4D PET reconstruction algorithm for direct estimation of parametric images from raw PET data when using the simplified reference tissue model with the basis function method (SRTM-BFM) for the kinetic analysis. To date, the OSL-MLEM method has been evaluated using kinetic models based on two-tissue compartments with an irreversible component. We extend the evaluation of this method for two-tissue compartments with a reversible component, using SRTM-BFM on simulated 3D + time data sets (with use of [(11)C]raclopride time-activity curves from real data) and on real data sets acquired with the high resolution research tomograph. The performance of the proposed method is evaluated by comparing voxel-level binding potential (BPND) estimates with those obtained from conventional post-reconstruction kinetic parameter estimation. For the commonly chosen number of iterations used in practice, our results show that for the 3D + time simulation, the direct method delivers results with lower (%)RMSE at the normal count level (decreases of 9-10 percentage points, corresponding to a 38-44% reduction), and also at low count levels (decreases of 17-21 percentage points, corresponding to a 26-36% reduction). As for the real 3D data set, the results obtained follow a similar trend, with the direct reconstruction method offering a 21% decrease in (%)CV compared to the post reconstruction method at low count levels. Thus, based on the results presented herein, using the SRTM-BFM kinetic model in conjunction with the OSL-MLEM direct 4D PET MLEM reconstruction method offers an improvement in performance when compared to conventional post reconstruction methods. PMID:25992999

  1. 4D reconstruction of the past

    NASA Astrophysics Data System (ADS)

    Doulamis, Anastasios; Ioannides, Marinos; Doulamis, Nikolaos; Hadjiprocopis, Andreas; Fritsch, Dieter; Balet, Olivier; Julien, Martine; Protopapadakis, Eftychios; Makantasis, Kostas; Weinlinger, Guenther; Johnsons, Paul S.; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro

    2013-08-01

    One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Search engines can search text for keywords using algorithms of varied intelligence and with limited success. Searching images is a much more complex and computationally intensive task but some initial steps have already been made in this direction, mainly in face recognition. This paper aims to describe our proposed pipeline for integrating data available on Internet repositories and social media, such as photographs, animation and text to produce 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EUROPEANA. Our main goal is to enable historians, architects, archaeologists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web.

  2. Cardiac 4D Ultrasound Imaging

    NASA Astrophysics Data System (ADS)

    D'hooge, Jan

    Volumetric cardiac ultrasound imaging has steadily evolved over the last 20 years from an electrocardiography (ECC) gated imaging technique to a true real-time imaging modality. Although the clinical use of echocardiography is still to a large extent based on conventional 2D ultrasound imaging it can be anticipated that the further developments in image quality, data visualization and interaction and image quantification of three-dimensional cardiac ultrasound will gradually make volumetric ultrasound the modality of choice. In this chapter, an overview is given of the technological developments that allow for volumetric imaging of the beating heart by ultrasound.

  3. 4-D ultrafast shear-wave imaging.

    PubMed

    Gennisson, Jean-Luc; Provost, Jean; Deffieux, Thomas; Papadacci, Clément; Imbault, Marion; Pernot, Mathieu; Tanter, Mickael

    2015-06-01

    Over the last ten years, shear wave elastography (SWE) has seen considerable development and is now routinely used in clinics to provide mechanical characterization of tissues to improve diagnosis. The most advanced technique relies on the use of an ultrafast scanner to generate and image shear waves in real time in a 2-D plane at several thousands of frames per second. We have recently introduced 3-D ultrafast ultrasound imaging to acquire with matrix probes the 3-D propagation of shear waves generated by a dedicated radiation pressure transducer in a single acquisition. In this study, we demonstrate 3-D SWE based on ultrafast volumetric imaging in a clinically applicable configuration. A 32 × 32 matrix phased array driven by a customized, programmable, 1024-channel ultrasound system was designed to perform 4-D shear-wave imaging. A matrix phased array was used to generate and control in 3-D the shear waves inside the medium using the acoustic radiation force. The same matrix array was used with 3-D coherent plane wave compounding to perform high-quality ultrafast imaging of the shear wave propagation. Volumetric ultrafast acquisitions were then beamformed in 3-D using a delay-and-sum algorithm. 3-D volumetric maps of the shear modulus were reconstructed using a time-of-flight algorithm based on local multiscale cross-correlation of shear wave profiles in the three main directions using directional filters. Results are first presented in an isotropic homogeneous and elastic breast phantom. Then, a full 3-D stiffness reconstruction of the breast was performed in vivo on healthy volunteers. This new full 3-D ultrafast ultrasound system paves the way toward real-time 3-D SWE. PMID:26067040

  4. A sinogram warping strategy for pre-reconstruction 4D PET optimization.

    PubMed

    Gianoli, Chiara; Riboldi, Marco; Fontana, Giulia; Kurz, Christopher; Parodi, Katia; Baroni, Guido

    2016-03-01

    A novel strategy for 4D PET optimization in the sinogram domain is proposed, aiming at motion model application before image reconstruction ("sinogram warping" strategy). Compared to state-of-the-art 4D-MLEM reconstruction, the proposed strategy is able to optimize the image SNR, avoiding iterative direct and inverse warping procedures, which are typical of the 4D-MLEM algorithm. A full-count statistics sinogram of the motion-compensated 4D PET reference phase is generated by warping the sinograms corresponding to the different PET phases. This is achieved relying on a motion model expressed in the sinogram domain. The strategy was tested on the anthropomorphic 4D PET-CT NCAT phantom in comparison with the 4D-MLEM algorithm, with particular reference to robustness to PET-CT co-registrations artefacts. The MLEM reconstruction of the warped sinogram according to the proposed strategy exhibited better accuracy (up to +40.90 % with respect to the ideal value), whereas images reconstructed according to the 4D-MLEM reconstruction resulted in less noisy (down to -26.90 % with respect to the ideal value) but more blurred. The sinogram warping strategy demonstrates advantages with respect to 4D-MLEM algorithm. These advantages are paid back by introducing approximation of the deformation field, and further efforts are required to mitigate the impact of such an approximation in clinical 4D PET reconstruction.

  5. Fully 4D list-mode reconstruction applied to respiratory-gated PET scans

    NASA Astrophysics Data System (ADS)

    Grotus, N; Reader, A J; Stute, S; Rosenwald, J C; Giraud, P; Buvat, I

    2009-03-01

    18F-fluoro-deoxy-glucose (18F-FDG) positron emission tomography (PET) is one of the most sensitive and specific imaging modalities for the diagnosis of non-small cell lung cancer. A drawback of PET is that it requires several minutes of acquisition per bed position, which results in images being affected by respiratory blur. Respiratory gating techniques have been developed to deal with respiratory motion in the PET images. However, these techniques considerably increase the level of noise in the reconstructed images unless the acquisition time is increased. The aim of this paper is to evaluate a four-dimensional (4D) image reconstruction algorithm that combines the acquired events in all the gates whilst preserving the motion deblurring. This algorithm was compared to classic ordered subset expectation maximization (OSEM) reconstruction of gated and non-gated images, and to temporal filtering of gated images reconstructed with OSEM. Two datasets were used for comparing the different reconstruction approaches: one involving the NEMA IEC/2001 body phantom in motion, the other obtained using Monte-Carlo simulations of the NCAT breathing phantom. Results show that 4D reconstruction reaches a similar performance in terms of the signal-to-noise ratio (SNR) as non-gated reconstruction whilst preserving the motion deblurring. In particular, 4D reconstruction improves the SNR compared to respiratory-gated images reconstructed with the OSEM algorithm. Temporal filtering of the OSEM-reconstructed images helps improve the SNR, but does not achieve the same performance as 4D reconstruction. 4D reconstruction of respiratory-gated images thus appears as a promising tool to reach the same performance in terms of the SNR as non-gated acquisitions while reducing the motion blur, without increasing the acquisition time.

  6. 4D flow imaging with MRI

    PubMed Central

    Stankovic, Zoran; Allen, Bradley D.; Garcia, Julio; Jarvis, Kelly B.

    2014-01-01

    Magnetic resonance imaging (MRI) has become an important tool for the clinical evaluation of patients with cardiovascular disease. Since its introduction in the late 1980s, 2-dimensional phase contrast MRI (2D PC-MRI) has become a routine part of standard-of-care cardiac MRI for the assessment of regional blood flow in the heart and great vessels. More recently, time-resolved PC-MRI with velocity encoding along all three flow directions and three-dimensional (3D) anatomic coverage (also termed ‘4D flow MRI’) has been developed and applied for the evaluation of cardiovascular hemodynamics in multiple regions of the human body. 4D flow MRI allows for the comprehensive evaluation of complex blood flow patterns by 3D blood flow visualization and flexible retrospective quantification of flow parameters. Recent technical developments, including the utilization of advanced parallel imaging techniques such as k-t GRAPPA, have resulted in reasonable overall scan times, e.g., 8-12 minutes for 4D flow MRI of the aorta and 10-20 minutes for whole heart coverage. As a result, the application of 4D flow MRI in a clinical setting has become more feasible, as documented by an increased number of recent reports on the utility of the technique for the assessment of cardiac and vascular hemodynamics in patient studies. A number of studies have demonstrated the potential of 4D flow MRI to provide an improved assessment of hemodynamics which might aid in the diagnosis and therapeutic management of cardiovascular diseases. The purpose of this review is to describe the methods used for 4D flow MRI acquisition, post-processing and data analysis. In addition, the article provides an overview of the clinical applications of 4D flow MRI and includes a review of applications in the heart, thoracic aorta and hepatic system. PMID:24834414

  7. 4D Confocal Imaging of Yeast Organelles.

    PubMed

    Day, Kasey J; Papanikou, Effrosyni; Glick, Benjamin S

    2016-01-01

    Yeast cells are well suited to visualizing organelles by 4D confocal microscopy. Typically, one or more cellular compartments are labeled with a fluorescent protein or dye, and a stack of confocal sections spanning the entire cell volume is captured every few seconds. Under appropriate conditions, organelle dynamics can be observed for many minutes with only limited photobleaching. Images are captured at a relatively low signal-to-noise ratio and are subsequently processed to generate movies that can be analyzed and quantified. Here, we describe methods for acquiring and processing 4D data using conventional scanning confocal microscopy. PMID:27631997

  8. Evaluation of a 4D cone-beam CT reconstruction approach using a simulation framework.

    PubMed

    Hartl, Alexander; Yaniv, Ziv

    2009-01-01

    Current image-guided navigation systems for thoracic abdominal interventions utilize three dimensional (3D) images acquired at breath-hold. As a result they can only provide guidance at a specific point in the respiratory cycle. The intervention is thus performed in a gated manner, with the physician advancing only when the patient is at the same respiratory cycle in which the 3D image was acquired. To enable a more continuous workflow we propose to use 4D image data. We describe an approach to constructing a set of 4D images from a diagnostic CT acquired at breath-hold and a set of intraoperative cone-beam CT (CBCT) projection images acquired while the patient is freely breathing. Our approach is based on an initial reconstruction of a gated 4D CBCT data set. The 3D CBCT images for each respiratory phase are then non-rigidly registered to the diagnostic CT data. Finally the diagnostic CT is deformed based on the registration results, providing a 4D data set with sufficient quality for navigation purposes. In this work we evaluate the proposed reconstruction approach using a simulation framework. A 3D CBCT dataset of an anthropomorphic phantom is deformed using internal motion data acquired from an animal model to create a ground truth 4D CBCT image. Simulated projection images are then created from the 4D image and the known CBCT scan parameters. Finally, the original 3D CBCT and the simulated X-ray images are used as input to our reconstruction method. The resulting 4D data set is then compared to the known ground truth by normalized cross correlation(NCC). We show that the deformed diagnostic CTs are of better quality than the gated reconstructions with a mean NCC value of 0.94 versus a mean 0.81 for the reconstructions. PMID:19964143

  9. 4D Clinical Imaging for Dynamic CAD

    PubMed Central

    McIntyre, Frederick

    2013-01-01

    A basic 4D imaging system to capture the jaw motion has been developed that produces high resolution 3D surface data. Fluorescent microspheres are brushed onto the areas of the upper and the lower arches to be imaged, producing a high-contrast random optical pattern. A hand-held imaging device operated at about 10 cm from the mouth captures time-based perspective images of the fluorescent areas. Each set of images, containing both upper and the lower arch data, is converted to a 3d point mesh using photogrammetry, thereby providing an instantaneous relative jaw position. Eight 3d positions per second are captured. Using one of the 3d frames as a reference, incremental transforms are derived to express the free body motion of the mandible. Conventional 3d models of the dentition are directly registered to the reference frame, allowing them to be animated using the derived transforms. PMID:24082882

  10. Respiratory triggered 4D cone-beam computed tomography: A novel method to reduce imaging dose

    PubMed Central

    Cooper, Benjamin J.; O’Brien, Ricky T.; Balik, Salim; Hugo, Geoffrey D.; Keall, Paul J.

    2013-01-01

    Purpose: A novel method called respiratory triggered 4D cone-beam computed tomography (RT 4D CBCT) is described whereby imaging dose can be reduced without degrading image quality. RT 4D CBCT utilizes a respiratory signal to trigger projections such that only a single projection is assigned to a given respiratory bin for each breathing cycle. In contrast, commercial 4D CBCT does not actively use the respiratory signal to minimize image dose. Methods: To compare RT 4D CBCT with conventional 4D CBCT, 3600 CBCT projections of a thorax phantom were gathered and reconstructed to generate a ground truth CBCT dataset. Simulation pairs of conventional 4D CBCT acquisitions and RT 4D CBCT acquisitions were developed assuming a sinusoidal respiratory signal which governs the selection of projections from the pool of 3600 original projections. The RT 4D CBCT acquisition triggers a single projection when the respiratory signal enters a desired acquisition bin; the conventional acquisition does not use a respiratory trigger and projections are acquired at a constant frequency. Acquisition parameters studied were breathing period, acquisition time, and imager frequency. The performance of RT 4D CBCT using phase based and displacement based sorting was also studied. Image quality was quantified by calculating difference images of the test dataset from the ground truth dataset. Imaging dose was calculated by counting projections. Results: Using phase based sorting RT 4D CBCT results in 47% less imaging dose on average compared to conventional 4D CBCT. Image quality differences were less than 4% at worst. Using displacement based sorting RT 4D CBCT results in 57% less imaging dose on average, than conventional 4D CBCT methods; however, image quality was 26% worse with RT 4D CBCT. Conclusions: Simulation studies have shown that RT 4D CBCT reduces imaging dose while maintaining comparable image quality for phase based 4D CBCT; image quality is degraded for displacement based RT 4D

  11. 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.

  12. Registration based super-resolution reconstruction for lung 4D-CT.

    PubMed

    Wu, Xiuxiu; Xiao, Shan; Zhang, Yu

    2014-01-01

    Lung 4D-CT plays an important role in lung cancer radiotherapy for tumor localization and treatment planning. In lung 4D-CT data, the resolution in the slice direction is often much lower than the in-plane resolution. For multi-plane display, isotropic resolution is necessary, but the commonly used interpolation operation will blur the images. In this paper, we present a registration based method for super resolution enhancement of the 4D-CT multi-plane images. Our working premise is that the low-resolution images of different phases at the corresponding position can be regarded as input "frames" to reconstruct high resolution images. First, we employ the Demons registration algorithm to estimate the motion field between different "frames". Then, the projections onto convex sets (POCS) approach is employed to reconstruction high-resolution lung images. We show that our method can get clearer lung images and enhance image structure, compared with the cubic spline interpolation and back projection method. PMID:25570484

  13. Registration based super-resolution reconstruction for lung 4D-CT.

    PubMed

    Wu, Xiuxiu; Xiao, Shan; Zhang, Yu

    2014-01-01

    Lung 4D-CT plays an important role in lung cancer radiotherapy for tumor localization and treatment planning. In lung 4D-CT data, the resolution in the slice direction is often much lower than the in-plane resolution. For multi-plane display, isotropic resolution is necessary, but the commonly used interpolation operation will blur the images. In this paper, we present a registration based method for super resolution enhancement of the 4D-CT multi-plane images. Our working premise is that the low-resolution images of different phases at the corresponding position can be regarded as input "frames" to reconstruct high resolution images. First, we employ the Demons registration algorithm to estimate the motion field between different "frames". Then, the projections onto convex sets (POCS) approach is employed to reconstruction high-resolution lung images. We show that our method can get clearer lung images and enhance image structure, compared with the cubic spline interpolation and back projection method.

  14. Motion-compensated fully 4D reconstruction of gated cardiac sequences

    NASA Astrophysics Data System (ADS)

    Gravier, Erwan; Yang, Yongyi

    2005-03-01

    In this paper we investigate the benefits of a spatio-temporal approach for reconstruction of cardiac image sequences. We introduce a temporal prior based on motion-compensation to enforce temporal correlations along the curved trajectories that follow the cardiac motion. The image frames in a sequence are reconstructed simultaneously through maximum a posteriori (MAP) estimation. We evaluated the performance of our algorithm using the 4D gated mathematical cardiac-torso (gMCAT) D1.01 phantom to simulate gated SPECT perfusion imaging with Tc-99m-sestamibi. Our experimental results show that the proposed approach could significantly improve the accuracy of reconstructed images without causing cross-frame blurring that may arise form the cardiac motion.

  15. 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.

  16. 4D cone-beam CT reconstruction using multi-organ meshes for sliding motion modeling.

    PubMed

    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.

  17. 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.

  18. 4-D display of satellite cloud images

    NASA Technical Reports Server (NTRS)

    Hibbard, William L.

    1987-01-01

    A technique has been developed to display GOES satellite cloud images in perspective over a topographical map. Cloud heights are estimated using temperatures from an infrared (IR) satellite image, surface temperature observations, and a climatological model of vertical temperature profiles. Cloud levels are discriminated from each other and from the ground using a pattern recognition algorithm based on the brightness variance technique of Coakley and Bretherton. The cloud regions found by the pattern recognizer are rendered in three-dimensional perspective over a topographical map by an efficient remap of the visible image. The visible shades are mixed with an artificial shade based on the geometry of the cloud-top surface, in order to enhance the texture of the cloud top.

  19. A novel method for 4D cone-beam computer-tomography reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Hao; Park, Justin C.; Chen, Yunmei; Lan, Guanghui; Lu, Bo

    2015-03-01

    Image quality of Four Dimensional Cone-Beam Computer-Tomography (4DCBCT) is severely impaired by highly insufficient amount of projection data available for each phase. Therefore, making good use of limited projection data is crucial to solve this problem. Noticing that usually only a portion of the images is affected by motion, we separate the moving part (different between phases) of the images from the static part (identical among all phases) with the help of prior image reconstructed using all projection data. Then we update the moving part and the static part of images alternatively through solving minimization problems based on a global (use full projection data) and several local (use projection data for respective phase) linear systems. In the other word, we rebuild a large over-determined linear system for static part from the original under-determined systems and we reduce the number of unknowns in the original system for each phase as well. As a result, image quality for both static part and moving part are greatly improved and reliable 4D CBCT images are then reconstructed.

  20. Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

    NASA Astrophysics Data System (ADS)

    Rodrigues, Pedro L.; Rodrigues, Nuno F.; Fonseca, Jaime C.; Vilaça, João. L.

    2015-03-01

    An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.

  1. 4D MR imaging using robust internal respiratory signal

    NASA Astrophysics Data System (ADS)

    Hui, CheukKai; Wen, Zhifei; Stemkens, Bjorn; Tijssen, R. H. N.; van den Berg, C. A. T.; Hwang, Ken-Pin; Beddar, Sam

    2016-05-01

    The purpose of this study is to investigate the feasibility of using internal respiratory (IR) surrogates to sort four-dimensional (4D) magnetic resonance (MR) images. The 4D MR images were constructed by acquiring fast 2D cine MR images sequentially, with each slice scanned for more than one breathing cycle. The 4D volume was then sorted retrospectively using the IR signal. In this study, we propose to use multiple low-frequency components in the Fourier space as well as the anterior body boundary as potential IR surrogates. From these potential IR surrogates, we used a clustering algorithm to identify those that best represented the respiratory pattern to derive the IR signal. A study with healthy volunteers was performed to assess the feasibility of the proposed IR signal. We compared this proposed IR signal with the respiratory signal obtained using respiratory bellows. Overall, 99% of the IR signals matched the bellows signals. The average difference between the end inspiration times in the IR signal and bellows signal was 0.18 s in this cohort of matching signals. For the acquired images corresponding to the other 1% of non-matching signal pairs, the respiratory motion shown in the images was coherent with the respiratory phases determined by the IR signal, but not the bellows signal. This suggested that the IR signal determined by the proposed method could potentially correct the faulty bellows signal. The sorted 4D images showed minimal mismatched artefacts and potential clinical applicability. The proposed IR signal therefore provides a feasible alternative to effectively sort MR images in 4D.

  2. Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction

    PubMed Central

    Kazantsev, Daniil; Guo, Enyu; Kaestner, Anders; Lionheart, William R. B.; Bent, Julian; Withers, Philip J.; Lee, Peter D.

    2016-01-01

    X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding. PMID:27002902

  3. Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction.

    PubMed

    Kazantsev, Daniil; Guo, Enyu; Kaestner, Anders; Lionheart, William R B; Bent, Julian; Withers, Philip J; Lee, Peter D

    2016-01-01

    X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding.

  4. Temporal sparsity exploiting nonlocal regularization for 4D computed tomography reconstruction.

    PubMed

    Kazantsev, Daniil; Guo, Enyu; Kaestner, Anders; Lionheart, William R B; Bent, Julian; Withers, Philip J; Lee, Peter D

    2016-01-01

    X-ray imaging applications in medical and material sciences are frequently limited by the number of tomographic projections collected. The inversion of the limited projection data is an ill-posed problem and needs regularization. Traditional spatial regularization is not well adapted to the dynamic nature of time-lapse tomography since it discards the redundancy of the temporal information. In this paper, we propose a novel iterative reconstruction algorithm with a nonlocal regularization term to account for time-evolving datasets. The aim of the proposed nonlocal penalty is to collect the maximum relevant information in the spatial and temporal domains. With the proposed sparsity seeking approach in the temporal space, the computational complexity of the classical nonlocal regularizer is substantially reduced (at least by one order of magnitude). The presented reconstruction method can be directly applied to various big data 4D (x, y, z+time) tomographic experiments in many fields. We apply the proposed technique to modelled data and to real dynamic X-ray microtomography (XMT) data of high resolution. Compared to the classical spatio-temporal nonlocal regularization approach, the proposed method delivers reconstructed images of improved resolution and higher contrast while remaining significantly less computationally demanding. PMID:27002902

  5. Adaptive patch-based POCS approach for super resolution reconstruction of 4D-CT lung data.

    PubMed

    Wang, Tingting; Cao, Lei; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

    2015-08-01

    Image enhancement of lung four-dimensional computed tomography (4D-CT) data is highly important because image resolution remains a crucial point in lung cancer radiotherapy. In this paper, we proposed a method for lung 4D-CT super resolution (SR) by using an adaptive-patch-based projection onto convex sets (POCS) approach, which is in contrast with the global POCS SR algorithm, to recover fine details with lesser artifacts in images. The main contribution of this patch-based approach is that the interfering local structure from other phases can be rejected by employing a similar patch adaptive selection strategy. The effectiveness of our approach is demonstrated through experiments on simulated images and real lung 4D-CT datasets. A comparison with previously published SR reconstruction methods highlights the favorable characteristics of the proposed method.

  6. Adaptive patch-based POCS approach for super resolution reconstruction of 4D-CT lung data

    NASA Astrophysics Data System (ADS)

    Wang, Tingting; Cao, Lei; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

    2015-08-01

    Image enhancement of lung four-dimensional computed tomography (4D-CT) data is highly important because image resolution remains a crucial point in lung cancer radiotherapy. In this paper, we proposed a method for lung 4D-CT super resolution (SR) by using an adaptive-patch-based projection onto convex sets (POCS) approach, which is in contrast with the global POCS SR algorithm, to recover fine details with lesser artifacts in images. The main contribution of this patch-based approach is that the interfering local structure from other phases can be rejected by employing a similar patch adaptive selection strategy. The effectiveness of our approach is demonstrated through experiments on simulated images and real lung 4D-CT datasets. A comparison with previously published SR reconstruction methods highlights the favorable characteristics of the proposed method.

  7. Reconstruction of a 4D Particle Distribution Using UnderdeterminedPhase-Space Data

    SciTech Connect

    Rostamizadeh, Afshin

    2005-08-10

    A well defined 4D distribution that describes the transverse spatial coordinates (x,y) and momenta (x',y') of the particles that make up an intense ion beam is of great value to theorists in the field of particle beam physics. If such a distribution truthfully captures the characteristic of the actual beam, it can be used to initialize an extensive simulation, and can yield insight into the processes that affect beam quality. Creating a proper representative distribution of particles is a challenge because the problem is, in general, quite underdetermined. Data is collected through a pair of ''optical slit'' diagnostics which provide two 3D distributions, f(x,y,x') and f(x,y,y'); the challenge is to coalesce these into a full 4D distribution f(x,y,x',y'). Further difficulties are introduced because the data is collected at different longitudinal planes and must be ''remapped'' to a common plane, taking into account the convergence or divergence of the beam as well as any off-centering. This challenge was met by developing a suitable algorithm and implementing it as a ''plug-in'' for the popular scientific image analysis program ImageJ, written entirely in the Java programming language. The algorithm accomplishes the desired remapping and synthesizes a 4D particle distribution, using Monte-Carlo techniques. Preliminary results show that this reconstructed distribution is consistent with actual data that was gathered from the same experiment using a different diagnostic. Also, ''forward'' particle-in-cell (PIC) simulations, that use the reconstructed distribution, match actual data gathered downstream in the experiment. Both these results give us some indication that the reconstruction is being done correctly. In addition to the multi-particle synthesis, the plug-in allows for the easy loading of digital data and the output of various plots that are useful to both experimenters and theorists. It also provides a framework by which its applicability can be extended to

  8. Phase and amplitude binning for 4D-CT imaging

    NASA Astrophysics Data System (ADS)

    Abdelnour, A. F.; Nehmeh, S. A.; Pan, T.; Humm, J. L.; Vernon, P.; Schöder, H.; Rosenzweig, K. E.; Mageras, G. S.; Yorke, E.; Larson, S. M.; Erdi, Y. E.

    2007-07-01

    We compare the consistency and accuracy of two image binning approaches used in 4D-CT imaging. One approach, phase binning (PB), assigns each breathing cycle 2π rad, within which the images are grouped. In amplitude binning (AB), the images are assigned bins according to the breathing signal's full amplitude. To quantitate both approaches we used a NEMA NU2-2001 IEC phantom oscillating in the axial direction and at random frequencies and amplitudes, approximately simulating a patient's breathing. 4D-CT images were obtained using a four-slice GE Lightspeed CT scanner operating in cine mode. We define consistency error as a measure of ability to correctly bin over repeated cycles in the same field of view. Average consistency error μe ± σe in PB ranged from 18% ± 20% to 30% ± 35%, while in AB the error ranged from 11% ± 14% to 20% ± 24%. In PB nearly all bins contained sphere slices. AB was more accurate, revealing empty bins where no sphere slices existed. As a proof of principle, we present examples of two non-small cell lung carcinoma patients' 4D-CT lung images binned by both approaches. While AB can lead to gaps in the coronal images, depending on the patient's breathing pattern, PB exhibits no gaps but suffers visible artifacts due to misbinning, yielding images that cover a relatively large amplitude range. AB was more consistent, though often resulted in gaps when no data existed due to patients' breathing pattern. We conclude AB is more accurate than PB. This has important consequences to treatment planning and diagnosis.

  9. Myocardial motion and function assessment using 4D images

    NASA Astrophysics Data System (ADS)

    Shi, Peng-Cheng; Robinson, Glynn P.; Duncan, James S.

    1994-09-01

    This paper describes efforts aimed at more objectively and accurately quantifying the local, regional and global function of the left ventricle (LV) of the heart from 4D image data. Using our shape-based image analysis methods, point-wise myocardial motion vector fields between successive image frames through the entire cardiac cycle will be computed. Quantitative LV motion, thickening, and strain measurements will then be established from the point correspondence maps. In the paper, we will also briefly describe an in vivo experimental model which uses implanted imaging-opaque markers to validate the results of our image analysis methods. Finally, initial experimental results using image sequences from two different modalities will be presented.

  10. Super-resolution reconstruction for 4D computed tomography of the lung via the projections onto convex sets approach

    SciTech Connect

    Zhang, Yu E-mail: qianjinfeng08@gmail.com; Wu, Xiuxiu; Yang, Wei; Feng, Qianjin E-mail: qianjinfeng08@gmail.com; Chen, Wufan

    2014-11-01

    Purpose: The use of 4D computed tomography (4D-CT) of the lung is important in lung cancer radiotherapy for tumor localization and treatment planning. Sometimes, dense sampling is not acquired along the superior–inferior direction. This disadvantage results in an interslice thickness that is much greater than in-plane voxel resolutions. Isotropic resolution is necessary for multiplanar display, but the commonly used interpolation operation blurs images. This paper presents a super-resolution (SR) reconstruction method to enhance 4D-CT resolution. Methods: The authors assume that the low-resolution images of different phases at the same position can be regarded as input “frames” to reconstruct high-resolution images. The SR technique is used to recover high-resolution images. Specifically, the Demons deformable registration algorithm is used to estimate the motion field between different “frames.” Then, the projection onto convex sets approach is implemented to reconstruct high-resolution lung images. Results: The performance of the SR algorithm is evaluated using both simulated and real datasets. Their method can generate clearer lung images and enhance image structure compared with cubic spline interpolation and back projection (BP) method. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 40.8% relative to cubic spline interpolation and 10.2% versus BP. Conclusions: A new algorithm has been developed to improve the resolution of 4D-CT. The algorithm outperforms the cubic spline interpolation and BP approaches by producing images with markedly improved structural clarity and greatly reduced artifacts.

  11. 4D Light Field Imaging System Using Programmable Aperture

    NASA Technical Reports Server (NTRS)

    Bae, Youngsam

    2012-01-01

    Complete depth information can be extracted from analyzing all angles of light rays emanated from a source. However, this angular information is lost in a typical 2D imaging system. In order to record this information, a standard stereo imaging system uses two cameras to obtain information from two view angles. Sometimes, more cameras are used to obtain information from more angles. However, a 4D light field imaging technique can achieve this multiple-camera effect through a single-lens camera. Two methods are available for this: one using a microlens array, and the other using a moving aperture. The moving-aperture method can obtain more complete stereo information. The existing literature suggests a modified liquid crystal panel [LC (liquid crystal) panel, similar to ones commonly used in the display industry] to achieve a moving aperture. However, LC panels cannot withstand harsh environments and are not qualified for spaceflight. In this regard, different hardware is proposed for the moving aperture. A digital micromirror device (DMD) will replace the liquid crystal. This will be qualified for harsh environments for the 4D light field imaging. This will enable an imager to record near-complete stereo information. The approach to building a proof-ofconcept is using existing, or slightly modified, off-the-shelf components. An SLR (single-lens reflex) lens system, which typically has a large aperture for fast imaging, will be modified. The lens system will be arranged so that DMD can be integrated. The shape of aperture will be programmed for single-viewpoint imaging, multiple-viewpoint imaging, and coded aperture imaging. The novelty lies in using a DMD instead of a LC panel to move the apertures for 4D light field imaging. The DMD uses reflecting mirrors, so any light transmission lost (which would be expected from the LC panel) will be minimal. Also, the MEMS-based DMD can withstand higher temperature and pressure fluctuation than a LC panel can. Robotics need

  12. 4D XCAT phantom for multimodality imaging research

    SciTech Connect

    Segars, W. P.; Sturgeon, G.; Mendonca, S.; Grimes, Jason; Tsui, B. M. W.

    2010-09-15

    Purpose: The authors develop the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. Methods: Highly detailed whole-body anatomies for the adult male and female were defined in the XCAT using nonuniform rational B-spline (NURBS) and subdivision surfaces based on segmentation of the Visible Male and Female anatomical datasets from the National Library of Medicine as well as patient datasets. Using the flexibility of these surfaces, the Visible Human anatomies were transformed to match body measurements and organ volumes for a 50th percentile (height and weight) male and female. The desired body measurements for the models were obtained using the PEOPLESIZE program that contains anthropometric dimensions categorized from 1st to the 99th percentile for US adults. The desired organ volumes were determined from ICRP Publication 89 [ICRP, ''Basic anatomical and physiological data for use in radiological protection: reference values,'' ICRP Publication 89 (International Commission on Radiological Protection, New York, NY, 2002)]. The male and female anatomies serve as standard templates upon which anatomical variations may be modeled in the XCAT through user-defined parameters. Parametrized models for the cardiac and respiratory motions were also incorporated into the XCAT based on high-resolution cardiac- and respiratory-gated multislice CT data. To demonstrate the usefulness of the phantom, the authors show example simulation studies in PET, SPECT, and CT using publicly available simulation packages. Results: As demonstrated in the pilot studies, the 4D XCAT (which includes thousands of anatomical structures) can produce realistic imaging data when combined with accurate models of the imaging process. With the flexibility of the NURBS surface primitives, any number of different anatomies, cardiac or respiratory motions or patterns, and spatial resolutions can be simulated to perform imaging research. Conclusions: With the ability to produce

  13. 4D XCAT phantom for multimodality imaging research

    PubMed Central

    Segars, W. P.; Sturgeon, G.; Mendonca, S.; Grimes, Jason; Tsui, B. M. W.

    2010-01-01

    Purpose: The authors develop the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. Methods: Highly detailed whole-body anatomies for the adult male and female were defined in the XCAT using nonuniform rational B-spline (NURBS) and subdivision surfaces based on segmentation of the Visible Male and Female anatomical datasets from the National Library of Medicine as well as patient datasets. Using the flexibility of these surfaces, the Visible Human anatomies were transformed to match body measurements and organ volumes for a 50th percentile (height and weight) male and female. The desired body measurements for the models were obtained using the PEOPLESIZE program that contains anthropometric dimensions categorized from 1st to the 99th percentile for US adults. The desired organ volumes were determined from ICRP Publication 89 [ICRP, ‘‘Basic anatomical and physiological data for use in radiological protection: reference values,” ICRP Publication 89 (International Commission on Radiological Protection, New York, NY, 2002)]. The male and female anatomies serve as standard templates upon which anatomical variations may be modeled in the XCAT through user-defined parameters. Parametrized models for the cardiac and respiratory motions were also incorporated into the XCAT based on high-resolution cardiac- and respiratory-gated multislice CT data. To demonstrate the usefulness of the phantom, the authors show example simulation studies in PET, SPECT, and CT using publicly available simulation packages. Results: As demonstrated in the pilot studies, the 4D XCAT (which includes thousands of anatomical structures) can produce realistic imaging data when combined with accurate models of the imaging process. With the flexibility of the NURBS surface primitives, any number of different anatomies, cardiac or respiratory motions or patterns, and spatial resolutions can be simulated to perform imaging research. Conclusions: With the ability to produce

  14. 4D rotational x-ray imaging of wrist joint dynamic motion

    SciTech Connect

    Carelsen, Bart; Bakker, Niels H.; Strackee, Simon D.; Boon, Sjirk N.; Maas, Mario; Sabczynski, Joerg; Grimbergen, Cornelis A.; Streekstra, Geert J.

    2005-09-15

    Current methods for imaging joint motion are limited to either two-dimensional (2D) video fluoroscopy, or to animated motions from a series of static three-dimensional (3D) images. 3D movement patterns can be detected from biplane fluoroscopy images matched with computed tomography images. This involves several x-ray modalities and sophisticated 2D to 3D matching for the complex wrist joint. We present a method for the acquisition of dynamic 3D images of a moving joint. In our method a 3D-rotational x-ray (3D-RX) system is used to image a cyclically moving joint. The cyclic motion is synchronized to the x-ray acquisition to yield multiple sets of projection images, which are reconstructed to a series of time resolved 3D images, i.e., four-dimensional rotational x ray (4D-RX). To investigate the obtained image quality parameters the full width at half maximum (FWHM) of the point spread function (PSF) via the edge spread function and the contrast to noise ratio between air and phantom were determined on reconstructions of a bullet and rod phantom, using 4D-RX as well as stationary 3D-RX images. The CNR in volume reconstructions based on 251 projection images in the static situation and on 41 and 34 projection images of a moving phantom were 6.9, 3.0, and 2.9, respectively. The average FWHM of the PSF of these same images was, respectively, 1.1, 1.7, and 2.2 mm orthogonal to the motion and parallel to direction of motion 0.6, 0.7, and 1.0 mm. The main deterioration of 4D-RX images compared to 3D-RX images is due to the low number of projection images used and not to the motion of the object. Using 41 projection images seems the best setting for the current system. Experiments on a postmortem wrist show the feasibility of the method for imaging 3D dynamic joint motion. We expect that 4D-RX will pave the way to improved assessment of joint disorders by detection of 3D dynamic motion patterns in joints.

  15. 4D micro-CT-based perfusion imaging in small animals

    NASA Astrophysics Data System (ADS)

    Badea, C. T.; Johnston, S. M.; Lin, M.; Hedlund, L. W.; Johnson, G. A.

    2009-02-01

    Quantitative in-vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in rodents. We have recently developed a dual tube/detector micro-CT scanner that is well suited to capture first-pass kinetics of a bolus of contrast agent used to compute perfusion information. Our approach is based on the paradigm that the same time density curves can be reproduced in a number of consecutive, small (i.e. 50μL) injections of iodinated contrast agent at a series of different angles. This reproducibility is ensured by the high-level integration of the imaging components of our system, with a micro-injector, a mechanical ventilator, and monitoring applications. Sampling is controlled through a biological pulse sequence implemented in LabVIEW. Image reconstruction is based on a simultaneous algebraic reconstruction technique implemented on a GPU. The capabilities of 4D micro-CT imaging are demonstrated in studies on lung perfusion in rats. We report 4D micro-CT imaging in the rat lung with a heartbeat temporal resolution of 140 ms and reconstructed voxels of 88 μm. The approach can be readily extended to a wide range of important preclinical models, such as tumor perfusion and angiogenesis, and renal function.

  16. Graph-based retrospective 4D image construction from free-breathing MRI slice acquisitions

    NASA Astrophysics Data System (ADS)

    Tong, Yubing; Udupa, Jayaram K.; Ciesielski, Krzysztof C.; McDonough, Joseph M.; Mong, Andrew; Campbell, Robert M.

    2014-03-01

    4D or dynamic imaging of the thorax has many potential applications [1, 2]. CT and MRI offer sufficient speed to acquire motion information via 4D imaging. However they have different constraints and requirements. For both modalities both prospective and retrospective respiratory gating and tracking techniques have been developed [3, 4]. For pediatric imaging, x-ray radiation becomes a primary concern and MRI remains as the de facto choice. The pediatric subjects we deal with often suffer from extreme malformations of their chest wall, diaphragm, and/or spine, as such patient cooperation needed by some of the gating and tracking techniques are difficult to realize without causing patient discomfort. Moreover, we are interested in the mechanical function of their thorax in its natural form in tidal breathing. Therefore free-breathing MRI acquisition is the ideal modality of imaging for these patients. In our set up, for each coronal (or sagittal) slice position, slice images are acquired at a rate of about 200-300 ms/slice over several natural breathing cycles. This produces typically several thousands of slices which contain both the anatomic and dynamic information. However, it is not trivial to form a consistent and well defined 4D volume from these data. In this paper, we present a novel graph-based combinatorial optimization solution for constructing the best possible 4D scene from such data entirely in the digital domain. Our proposed method is purely image-based and does not need breath holding or any external surrogates or instruments to record respiratory motion or tidal volume. Both adult and children patients' data are used to illustrate the performance of the proposed method. Experimental results show that the reconstructed 4D scenes are smooth and consistent spatially and temporally, agreeing with known shape and motion of the lungs.

  17. TU-C-BRD-01: Image Guided SBRT I: Multi-Modality 4D Imaging

    SciTech Connect

    Cai, J; Mageras, G; Pan, T

    2014-06-15

    Motion management is one of the critical technical challenges for radiation therapy. 4D imaging has been rapidly adopted as essential tool to assess organ motion associated with respiratory breathing. A variety of 4D imaging techniques have been developed and are currently under development based on different imaging modalities such as CT, MRI, PET, and CBCT. Each modality provides specific and complementary information about organ and tumor respiratory motion. Effective use of each different technique or combined use of different techniques can introduce a comprehensive management of tumor motion. Specifically, these techniques have afforded tremendous opportunities to better define and delineate tumor volumes, more accurately perform patient positioning, and effectively apply highly conformal therapy techniques such as IMRT and SBRT. Successful implementation requires good understanding of not only each technique, including unique features, limitations, artifacts, imaging acquisition and process, but also how to systematically apply the information obtained from different imaging modalities using proper tools such as deformable image registration. Furthermore, it is important to understand the differences in the effects of breathing variation between different imaging modalities. A comprehensive motion management strategy using multi-modality 4D imaging has shown promise in improving patient care, but at the same time faces significant challenges. This session will focuses on the current status and advances in imaging respiration-induced organ motion with different imaging modalities: 4D-CT, 4D-MRI, 4D-PET, and 4D-CBCT/DTS. Learning Objectives: Understand the need and role of multimodality 4D imaging in radiation therapy. Understand the underlying physics behind each 4D imaging technique. Recognize the advantages and limitations of each 4D imaging technique.

  18. Automated 4D lung computed tomography reconstruction during free breathing for conformal radiation therapy

    NASA Astrophysics Data System (ADS)

    El Naqa, Issam M.; Low, Daniel A.; Christensen, Gary E.; Parikh, Parag J.; Song, Joo Hyun; Nystrom, Michelle M.; Lu, Wei; Deasy, Joseph O.; Hubenschmidt, James P.; Wahab, Sasha H.; Mutic, Sasa; Singh, Anurag K.; Bradley, Jeffrey D.

    2004-04-01

    We are developing 4D-CT to provide breathing motion information (trajectories) for radiation therapy treatment planning of lung cancer. Potential applications include optimization of intensity-modulated beams in the presence of breathing motion and intra-fraction target volume margin determination for conformal therapy. The images are acquired using a multi-slice CT scanner while the patient undergoes simultaneous quantitative spirometry. At each couch position, the CT scanner is operated in ciné mode and acquires up to 15 scans of 12 slices each. Each CT scan is associated with the measured tidal volume for retrospective reconstruction of 3D CT scans at arbitrary tidal volumes. The specific tasks of this project involves the development of automated registration of internal organ motion (trajectories) during breathing. A modified least-squares based optical flow algorithm tracks specific features of interest by modifying the eigenvalues of gradient matrix (gradient structural tensor). Good correlations between the measured motion and spirometry-based tidal volume are observed and evidence of internal hysteresis is also detected.

  19. 4D STEM: High efficiency phase contrast imaging using a fast pixelated detector

    NASA Astrophysics Data System (ADS)

    Yang, H.; Jones, L.; Ryll, H.; Simson, M.; Soltau, H.; Kondo, Y.; Sagawa, R.; Banba, H.; MacLaren, I.; Nellist, P. D.

    2015-10-01

    Phase contrast imaging is widely used for imaging beam sensitive and weak phase objects in electron microscopy. In this work we demonstrate the achievement of high efficient phase contrast imaging in STEM using the pnCCD, a fast direct electron pixelated detector, which records the diffraction patterns at every probe position with a speed of 1000 to 4000 frames per second, forming a 4D STEM dataset simultaneously with the incoherent Z-contrast imaging. Ptychographic phase reconstruction has been applied and the obtained complex transmission function reveals the phase of the specimen. The results using GaN and Ti, Nd- doped BiFeO3 show that this imaging mode is especially powerful for imaging light elements in the presence of much heavier elements.

  20. 3D and 4D magnetic susceptibility tomography based on complex MR images

    DOEpatents

    Chen, Zikuan; Calhoun, Vince D

    2014-11-11

    Magnetic susceptibility is the physical property for T2*-weighted magnetic resonance imaging (T2*MRI). The invention relates to methods for reconstructing an internal distribution (3D map) of magnetic susceptibility values, .chi. (x,y,z), of an object, from 3D T2*MRI phase images, by using Computed Inverse Magnetic Resonance Imaging (CIMRI) tomography. The CIMRI technique solves the inverse problem of the 3D convolution by executing a 3D Total Variation (TV) regularized iterative convolution scheme, using a split Bregman iteration algorithm. The reconstruction of .chi. (x,y,z) can be designed for low-pass, band-pass, and high-pass features by using a convolution kernel that is modified from the standard dipole kernel. Multiple reconstructions can be implemented in parallel, and averaging the reconstructions can suppress noise. 4D dynamic magnetic susceptibility tomography can be implemented by reconstructing a 3D susceptibility volume from a 3D phase volume by performing 3D CIMRI magnetic susceptibility tomography at each snapshot time.

  1. SU-E-J-246: A Deformation-Field Map Based Liver 4D CBCT Reconstruction Method Using Gold Nanoparticles as Constraints

    SciTech Connect

    Harris, W; Zhang, Y; Ren, L; Yin, F

    2014-06-01

    Purpose: To investigate the feasibility of using nanoparticle markers to validate liver tumor motion together with a deformation field map-based four dimensional (4D) cone-beam computed tomography (CBCT) reconstruction method. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In this method, each phase of the 4D-CBCT is considered as a deformation of a prior CT volume. The DFM is solved by a motion modeling and free-form deformation (MM-FD) technique, using a data fidelity constraint and the deformation energy minimization. For liver imaging, there is low contrast of a liver tumor in on-board projections. A validation of liver tumor motion using implanted gold nanoparticles, along with the MM-FD deformation technique is implemented to reconstruct onboard 4D CBCT liver radiotherapy images. These nanoparticles were placed around the liver tumor to reflect the tumor positions in both CT simulation and on-board image acquisition. When reconstructing each phase of the 4D-CBCT, the migrations of the gold nanoparticles act as a constraint to regularize the deformation field, along with the data fidelity and the energy minimization constraints. In this study, multiple tumor diameters and positions were simulated within the liver for on-board 4D-CBCT imaging. The on-board 4D-CBCT reconstructed by the proposed method was compared with the “ground truth” image. Results: The preliminary data, which uses reconstruction for lung radiotherapy suggests that the advanced reconstruction algorithm including the gold nanoparticle constraint will Resultin volume percentage differences (VPD) between lesions in reconstructed images by MM-FD and “ground truth” on-board images of 11.5% (± 9.4%) and a center of mass shift of 1.3 mm (± 1.3 mm) for liver radiotherapy. Conclusion: The advanced MM-FD technique enforcing the additional constraints from gold nanoparticles, results in improved accuracy

  2. The study of integration about measurable image and 4D production

    NASA Astrophysics Data System (ADS)

    Zhang, Chunsen; Hu, Pingbo; Niu, Weiyun

    2008-12-01

    In this paper, we create the geospatial data of three-dimensional (3D) modeling by the combination of digital photogrammetry and digital close-range photogrammetry. For large-scale geographical background, we make the establishment of DEM and DOM combination of three-dimensional landscape model based on the digital photogrammetry which uses aerial image data to make "4D" (DOM: Digital Orthophoto Map, DEM: Digital Elevation Model, DLG: Digital Line Graphic and DRG: Digital Raster Graphic) production. For the range of building and other artificial features which the users are interested in, we realize that the real features of the three-dimensional reconstruction adopting the method of the digital close-range photogrammetry can come true on the basis of following steps : non-metric cameras for data collection, the camera calibration, feature extraction, image matching, and other steps. At last, we combine three-dimensional background and local measurements real images of these large geographic data and realize the integration of measurable real image and the 4D production.The article discussed the way of the whole flow and technology, achieved the three-dimensional reconstruction and the integration of the large-scale threedimensional landscape and the metric building.

  3. VMAT QA: Measurement-guided 4D dose reconstruction on a patient

    SciTech Connect

    Nelms, Benjamin E.; Opp, Daniel; Robinson, Joshua; Wolf, Theresa K.; Zhang, Geoffrey; Moros, Eduardo; Feygelman, Vladimir

    2012-07-15

    Purpose: To develop and validate a volume-modulated arc therapy (VMAT) quality assurance (QA) tool that takes as input a time-resolved, low-density ({approx}10 mm) cylindrical surface dose map from a commercial helical diode array, and outputs a high density, volumetric, time-resolved dose matrix on an arbitrary patient dataset. This first validation study is limited to a homogeneous 'patient.'Methods: A VMAT treatment is delivered to a diode array phantom (ARCCHECK, Sun Nuclear Corp., Melbourne, FL). 3DVH software (Sun Nuclear) derives the high-density volumetric dose using measurement-guided dose reconstruction (MGDR). MGDR cylindrical phantom results are then used to perturb the three-dimensional (3D) treatment planning dose on the patient dataset, producing a semiempirical volumetric dose grid. Four-dimensional (4D) dose reconstruction on the patient is also possible by morphing individual sub-beam doses instead of the composite. For conventional (3D) dose comparison two methods were developed, using the four plans (Multi-Target, C-shape, Mock Prostate, and Head and Neck), including their structures and objectives, from the AAPM TG-119 report. First, 3DVH and treatment planning system (TPS) cumulative point doses were compared to ion chamber in a cube water-equivalent phantom ('patient'). The shape of the phantom is different from the ARCCHECK and furthermore the targets were placed asymmetrically. Second, coronal and sagittal absolute film dose distributions in the cube were compared with 3DVH and TPS. For time-resolved (4D) comparisons, three tests were performed. First, volumetric dose differences were calculated between the 3D MGDR and cumulative time-resolved patient (4D MGDR) dose at the end of delivery, where they ideally should be identical. Second, time-resolved (10 Hz sampling rate) ion chamber doses were compared to cumulative point dose vs time curves from 4D MGDR. Finally, accelerator output was varied to assess the linearity of the 4D MGDR with

  4. 4D imaging of protein aggregation in live cells.

    PubMed

    Spokoini, Rachel; Shamir, Maya; Keness, Alma; Kaganovich, Daniel

    2013-01-01

    ubiquitinated are diverted to the IPOD, where they are actively aggregated in a protective compartment. Up until this point, the methodological paradigm of live-cell fluorescence microscopy has largely been to label proteins and track their locations in the cell at specific time-points and usually in two dimensions. As new technologies have begun to grant experimenters unprecedented access to the submicron scale in living cells, the dynamic architecture of the cytosol has come into view as a challenging new frontier for experimental characterization. We present a method for rapidly monitoring the 3D spatial distributions of multiple fluorescently labeled proteins in the yeast cytosol over time. 3D timelapse (4D imaging) is not merely a technical challenge; rather, it also facilitates a dramatic shift in the conceptual framework used to analyze cellular structure. We utilize a cytosolic folding sensor protein in live yeast to visualize distinct fates for misfolded proteins in cellular aggregation quality control, using rapid 4D fluorescent imaging. The temperature sensitive mutant of the Ubc9 protein (Ubc9(ts)) is extremely effective both as a sensor of cellular proteostasis, and a physiological model for tracking aggregation quality control. As with most ts proteins, Ubc9(ts) is fully folded and functional at permissive temperatures due to active cellular chaperones. Above 30 ° C, or when the cell faces misfolding stress, Ubc9(ts) misfolds and follows the fate of a native globular protein that has been misfolded due to mutation, heat denaturation, or oxidative damage. By fusing it to GFP or other fluorophores, it can be tracked in 3D as it forms Stress Foci, or is directed to JUNQ or IPOD. PMID:23608881

  5. Three-channel dynamic photometric stereo: a new method for 4D surface reconstruction and volume recovery

    NASA Astrophysics Data System (ADS)

    Schroeder, Walter; Schulze, Wolfram; Wetter, Thomas; Chen, Chi-Hsien

    2008-08-01

    Three-dimensional (3D) body surface reconstruction is an important field in health care. A popular method for this purpose is laser scanning. However, using Photometric Stereo (PS) to record lumbar lordosis and the surface contour of the back poses a viable alternative due to its lower costs and higher flexibility compared to laser techniques and other methods of three-dimensional body surface reconstruction. In this work, we extended the traditional PS method and proposed a new method for obtaining surface and volume data of a moving object. The principle of traditional Photometric Stereo uses at least three images of a static object taken under different light sources to obtain 3D information of the object. Instead of using normal light, the light sources in the proposed method consist of the RGB-Color-Model's three colors: red, green and blue. A series of pictures taken with a video camera can now be separated into the different color channels. Each set of the three images can then be used to calculate the surface normals as a traditional PS. This method waives the requirement that the object imaged must be kept still as in almost all the other body surface reconstruction methods. By putting two cameras opposite to a moving object and lighting the object with the colored light, the time-varying surface (4D) data can easily be calculated. The obtained information can be used in many medical fields such as rehabilitation, diabetes screening or orthopedics.

  6. Learning distance function for regression-based 4D pulmonary trunk model reconstruction estimated from sparse MRI data

    NASA Astrophysics Data System (ADS)

    Vitanovski, Dime; Tsymbal, Alexey; Ionasec, Razvan; Georgescu, Bogdan; Zhou, Shaohua K.; Hornegger, Joachim; Comaniciu, Dorin

    2011-03-01

    Congenital heart defect (CHD) is the most common birth defect and a frequent cause of death for children. Tetralogy of Fallot (ToF) is the most often occurring CHD which affects in particular the pulmonary valve and trunk. Emerging interventional methods enable percutaneous pulmonary valve implantation, which constitute an alternative to open heart surgery. While minimal invasive methods become common practice, imaging and non-invasive assessment tools become crucial components in the clinical setting. Cardiac computed tomography (CT) and cardiac magnetic resonance imaging (cMRI) are techniques with complementary properties and ability to acquire multiple non-invasive and accurate scans required for advance evaluation and therapy planning. In contrary to CT which covers the full 4D information over the cardiac cycle, cMRI often acquires partial information, for example only one 3D scan of the whole heart in the end-diastolic phase and two 2D planes (long and short axes) over the whole cardiac cycle. The data acquired in this way is called sparse cMRI. In this paper, we propose a regression-based approach for the reconstruction of the full 4D pulmonary trunk model from sparse MRI. The reconstruction approach is based on learning a distance function between the sparse MRI which needs to be completed and the 4D CT data with the full information used as the training set. The distance is based on the intrinsic Random Forest similarity which is learnt for the corresponding regression problem of predicting coordinates of unseen mesh points. Extensive experiments performed on 80 cardiac CT and MR sequences demonstrated the average speed of 10 seconds and accuracy of 0.1053mm mean absolute error for the proposed approach. Using the case retrieval workflow and local nearest neighbour regression with the learnt distance function appears to be competitive with respect to "black box" regression with immediate prediction of coordinates, while providing transparency to the

  7. SU-D-17A-03: 5D Respiratory Motion Model Based Iterative Reconstruction Method for 4D Cone-Beam CT

    SciTech Connect

    Gao, Y; Thomas, D; Low, D; Gao, H

    2014-06-01

    Purpose: The purpose of this work is to develop a new iterative reconstruction method for 4D cone-beam CT (CBCT) based on a published time-independent 5D respiratory motion model. The proposed method will offer a single high-resolution image at a user-selected breathing phase and the 5D motion model parameters, which could be used to generate the breathing pattern during the CT acquisition. Methods: 5D respiratory motion model was proposed for accurately modeling the motion of lung and lung tumor tissues. 4D images are then parameterized by a reference image, measured breathing amplitude, breathing rate, two time-independent vector fields that describe the 5D model parameters, and a scalar field that describes the change in HU as a function of breathing amplitude. In contrast with the traditional method of reconstructing multiple temporal image phases to reduce respiratory artifact, 5D model based method simplify the problem into the reconstruction of a single reference image and the 5D motion model parameters. The reconstruction formulation of the reference image and scalar and vector fields is a nonlinear least-square optimization problem that consists of solving the reference image and fields alternately, in which the reference image is regularized with the total variation sparsity transform and the vector fields are solved through linearizations regularized by the H1 norm. 2D lung simulations were performed in this proof-of-concept study. Results: The breathing amplitude, its rate, and the corresponding scalar and vector fields were generated from a patient case. Compared with filtered backprojection method and sparsity regularized iterative method for the phase-by-phase reconstruction, the proposed 5D motion model based method yielded improved image quality. Conclusion: Based on 5D respiratory motion model, we have developed a new iterative reconstruction method for 4D CBCT that has the potential for improving image quality while providing needed on

  8. SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

    SciTech Connect

    Cui, Y; Bowsher, J; Yan, S; Cai, J; Das, S; Yin, F

    2014-06-01

    Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with {sup 18}F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medical Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.

  9. Sparse-CAPR: Highly-Accelerated 4D CE-MRA with Parallel Imaging and Nonconvex Compressive Sensing

    PubMed Central

    Trzasko, Joshua D.; Haider, Clifton R.; Borisch, Eric A.; Campeau, Norbert G.; Glockner, James F.; Riederer, Stephen J.; Manduca, Armando

    2012-01-01

    CAPR is a SENSE-type parallel 3DFT acquisition paradigm for 4D contrast-enhanced magnetic resonance angiography (CE-MRA) that has been demonstrated capable of providing high spatial and temporal resolution, diagnostic-quality images at very high acceleration rates. However, CAPR images are typically reconstructed online using Tikhonov regularization and partial Fourier methods, which are prone to exhibit noise amplification and undersampling artifacts when operating at very high acceleration rates. In this work, a sparsity-driven offline reconstruction framework for CAPR is developed and demonstrated to consistently provide improvements over the currently-employed reconstruction strategy against these ill-effects. Moreover, the proposed reconstruction strategy requires no changes to the existing CAPR acquisition protocol, and an efficient numerical optimization and hardware system are described that allow for a 256×160×80 volume CE-MRA volume to be reconstructed from an 8-channel data set in less than two minutes. PMID:21608028

  10. Overview of Image Reconstruction

    SciTech Connect

    Marr, R. B.

    1980-04-01

    Image reconstruction (or computerized tomography, etc.) is any process whereby a function, f, on Rn is estimated from empirical data pertaining to its integrals, ∫f(x) dx, for some collection of hyperplanes of dimension k < n. The paper begins with background information on how image reconstruction problems have arisen in practice, and describes some of the application areas of past or current interest; these include radioastronomy, optics, radiology and nuclear medicine, electron microscopy, acoustical imaging, geophysical tomography, nondestructive testing, and NMR zeugmatography. Then the various reconstruction algorithms are discussed in five classes: summation, or simple back-projection; convolution, or filtered back-projection; Fourier and other functional transforms; orthogonal function series expansion; and iterative methods. Certain more technical mathematical aspects of image reconstruction are considered from the standpoint of uniqueness, consistency, and stability of solution. The paper concludes by presenting certain open problems. 73 references. (RWR)

  11. SU-D-17A-01: Geometric and Dosimetric Evaluation of a 4D-CBCT Reconstruction Technique Using Prior Knowledge

    SciTech Connect

    Zhang, Y; Yin, F; Ren, L

    2014-06-01

    Purpose: To evaluate a 4D-CBCT reconstruction technique both geometrically and dosimetrically Methods: A prior-knowledge guided 4DC-BCT reconstruction method named the motion-modeling and free-form deformation (MM-FD) has been developed. MM-FD views each phase of the 4D-CBCT as a deformation of a prior CT volume. The deformation field is first solved by principal component analysis based motion modeling, followed by constrained free-form deformation.The 4D digital extended-cardiac- torso (XCAT) phantom was used for comprehensive evaluation. Based on a simulated 4D planning CT of a lung patient, 8 different scenarios were simulated to cover the typical on-board anatomical and respiratory variations: (1) synchronized and (2) unsynchronized motion amplitude change for body and tumor; tumor (3) shrinkage and (4) expansion; tumor average position shift in (5) superior-inferior (SI) direction, (6) anterior-posterior (AP) direction and (7) SI, AP and lateral directions altogether; and (8) tumor phase shift relative to the respiratory cycle of the body. Orthogonal-view 30° projections were simulated based on the eight patient scenarios to reconstruct on-board 4D-CBCTs. For geometric evaluation, the volume-percentage-difference (VPD) was calculated to assess the volumetric differences between the reconstructed and the ground-truth tumor.For dosimetric evaluation, a gated treatment plan was designed for the prior 4D-CT. The dose distributions were calculated on the reconstructed 4D-CBCTs and the ground-truth images for comparison. The MM-FD technique was compared with MM-only and FD-only techniques. Results: The average (±s.d.) VPD values of reconstructed tumors for MM-only, FDonly and MM-FD methods were 59.16%(± 26.66%), 75.98%(± 27.21%) and 5.22%(± 2.12%), respectively. The average min/max/mean dose (normalized to prescription) of the reconstructed tumors by MM-only, FD-only, MM-FD methods and ground-truth tumors were 78.0%/122.2%/108.2%, 13%/117.7%/86%, 58

  12. 4D RECONSTRUCTIONS FROM LOW-COUNT SPECT DATA USING DEFORMABLE MODELS WITH SMOOTH INTERIOR INTENSITY VARIATIONS

    SciTech Connect

    G. S. CUNNINGHAM; A. LEHOVICH

    2000-01-01

    The Bayes Inference Engine (BIE) has been used to perform a 4D reconstruction of a first-pass radiotracer bolus distribution inside a CardioWest Total Artificial Heart, imaged with the University of Arizona's FastSPECT system. The BIE estimates parameter values that define the 3D model of the radiotracer distribution at each of 41 times spanning about two seconds. The 3D models have two components: a closed surface, composed of hi-quadratic Bezier triangular surface patches, that defines the interface between the part of the blood pool that contains radiotracer and the part that contains no radiotracer, and smooth voxel-to-voxel variations in intensity within the closed surface. Ideally, the surface estimates the ventricular wall location where the bolus is infused throughout the part of the blood pool contained by the right ventricle. The voxel-to-voxel variations are needed to model an inhomogeneously-mixed bolus. Maximum a posterior (MAP) estimates of the Bezier control points and voxel values are obtained for each time frame. We show new reconstructions using the Bezier surface models, and discuss estimates of ventricular volume as a function of time, ejection fraction, and wall motion. The computation time for our reconstruction process, which directly estimates complex 3D model parameters from the raw data, is performed in a time that is competitive with more traditional voxel-based methods (ML-EM, e.g.).

  13. 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.

  14. Development of a dynamic 4D anthropomorphic breast phantom for contrast-based breast imaging

    NASA Astrophysics Data System (ADS)

    Kiarashi, Nooshin; Lin, Yuan; Segars, William P.; Ghate, Sujata V.; Ikejimba, Lynda; Chen, Baiyu; Lo, Joseph Y.; Dobbins, James T., III; Nolte, Loren W.; Samei, Ehsan

    2012-03-01

    Mammography is currently the most widely accepted tool for detection and diagnosis of breast cancer. However, the sensitivity of mammography is reduced in women with dense breast tissue due to tissue overlap, which may obscure lesions. Digital breast tomosynthesis with contrast enhancement reduces tissue overlap and provides additional functional information about lesions (i.e. morphology and kinetics), which in turn may improve lesion characterization. The performance of such techniques is highly dependent on the structural composition of the breast, which varies significantly across patients. Therefore, optimization of breast imaging systems should be done with respect to this patient versatility. Furthermore, imaging techniques that employ contrast require the inclusion of a temporally varying breast composition with respect to the contrast agent kinetics to enable the optimization of the system. To these ends, we have developed a dynamic 4D anthropomorphic breast phantom, which can be used for optimizing a breast imaging system by incorporating material characteristics. The presented dynamic phantom is based on two recently developed anthropomorphic breast phantoms, which can be representative of a whole population through their randomized anatomical feature generation and various compression levels. The 4D dynamic phantom is incorporated with the kinetics of contrast agent uptake in different tissues and can realistically model benign and malignant lesions. To demonstrate the utility of the proposed dynamic phantom, contrast-enhanced digital mammography and breast tomosynthesis were simulated where a ray-tracing algorithm emulated the projections, a filtered back projection algorithm was used for reconstruction, and dual-energy and temporal subtractions were performed and compared.

  15. Augmented Likelihood Image Reconstruction.

    PubMed

    Stille, Maik; Kleine, Matthias; Hägele, Julian; Barkhausen, Jörg; Buzug, Thorsten M

    2016-01-01

    The presence of high-density objects remains an open problem in medical CT imaging. Data of projections passing through objects of high density, such as metal implants, are dominated by noise and are highly affected by beam hardening and scatter. Reconstructed images become less diagnostically conclusive because of pronounced artifacts that manifest as dark and bright streaks. A new reconstruction algorithm is proposed with the aim to reduce these artifacts by incorporating information about shape and known attenuation coefficients of a metal implant. Image reconstruction is considered as a variational optimization problem. The afore-mentioned prior knowledge is introduced in terms of equality constraints. An augmented Lagrangian approach is adapted in order to minimize the associated log-likelihood function for transmission CT. During iterations, temporally appearing artifacts are reduced with a bilateral filter and new projection values are calculated, which are used later on for the reconstruction. A detailed evaluation in cooperation with radiologists is performed on software and hardware phantoms, as well as on clinically relevant patient data of subjects with various metal implants. Results show that the proposed reconstruction algorithm is able to outperform contemporary metal artifact reduction methods such as normalized metal artifact reduction.

  16. Neutral wind estimation from 4-D ionospheric electron density images

    NASA Astrophysics Data System (ADS)

    Datta-Barua, S.; Bust, G. S.; Crowley, G.; Curtis, N.

    2009-06-01

    We develop a new inversion algorithm for Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). The EMPIRE method uses four-dimensional images of global electron density to estimate the field-aligned neutral wind ionospheric driver when direct measurement is not available. We begin with a model of the electron continuity equation that includes production and loss rate estimates, as well as E × B drift, gravity, and diffusion effects. We use ion, electron, and neutral species temperatures and neutral densities from the Thermosphere Ionosphere Mesosphere Electrodynamics General Circulation Model (TIMEGCM-ASPEN) for estimating the magnitude of these effects. We then model the neutral wind as a power series at a given longitude for a range of latitudes and altitudes. As a test of our algorithm, we have input TIMEGCM electron densities to our algorithm. The model of the neutral wind is computed at hourly intervals and validated by comparing to the “true” TIMEGCM neutral wind fields. We show results for a storm day: 10 November 2004. The agreement between the winds derived from EMPIRE versus the TIMEGCM “true” winds appears to be time-dependent for the day under consideration. This may indicate that the diurnal variation in certain driving processes impacts the accuracy of our neutral wind model. Despite the potential temporal and spatial limits on accuracy, estimating neutral wind speed from measured electron density fields via our algorithm shows great promise as a complement to the more sparse radar and satellite measurements.

  17. Toward time resolved 4D cardiac CT imaging with patient dose reduction: estimating the global heart motion

    NASA Astrophysics Data System (ADS)

    Taguchi, Katsuyuki; Segars, W. Paul; Fung, George S. K.; Tsui, Benjamin M. W.

    2006-03-01

    Coronary artery imaging with multi-slice helical computed tomography is a promising noninvasive imaging technique. The current major issues include the insufficient temporal resolution and large patient dose. We propose an image reconstruction method which provides a solution to both of the problems. The method uses an iterative approach repeating the following four steps until the difference between the two projection data sets falls below a certain criteria in step-4: 1) estimating or updating the cardiac motion vectors, 2) reconstructing the time-resolved 4D dynamic volume images using the motion vectors, 3) calculating the projection data from the current 4D images, 4) comparing them with the measured ones. In this study, we obtain the first estimate of the motion vector. We use the 4D NCAT phantom, a realistic computer model for the human anatomy and cardiac motions, to generate the dynamic fan-beam projection data sets as well to provide a known truth for the motion. Then, the halfscan reconstruction with the sliding time-window technique is used to generate cine images: f(t, r r). Here, we use one heart beat for each position r so that the time information is retained. Next, the magnitude of the first derivative of f(t, r r) with respect to time, i.e., |df/dt|, is calculated and summed over a region-of-interest (ROI), which is called the mean-absolute difference (MAD). The initial estimation of the vector field are obtained using MAD for each ROI. Results of the preliminary study are presented.

  18. Impact of 4D image quality on the accuracy of target definition.

    PubMed

    Nielsen, Tine Bjørn; Hansen, Christian Rønn; Westberg, Jonas; Hansen, Olfred; Brink, Carsten

    2016-03-01

    Delineation accuracy of target shape and position depends on the image quality. This study investigates whether the image quality on standard 4D systems has an influence comparable to the overall delineation uncertainty. A moving lung target was imaged using a dynamic thorax phantom on three different 4D computed tomography (CT) systems and a 4D cone beam CT (CBCT) system using pre-defined clinical scanning protocols. Peak-to-peak motion and target volume were registered using rigid registration and automatic delineation, respectively. A spatial distribution of the imaging uncertainty was calculated as the distance deviation between the imaged target and the true target shape. The measured motions were smaller than actual motions. There were volume differences of the imaged target between respiration phases. Imaging uncertainties of >0.4 cm were measured in the motion direction which showed that there was a large distortion of the imaged target shape. Imaging uncertainties of standard 4D systems are of similar size as typical GTV-CTV expansions (0.5-1 cm) and contribute considerably to the target definition uncertainty. Optimising and validating 4D systems is recommended in order to obtain the most optimal imaged target shape.

  19. 4D cone beam CT phase sorting using high frequency optical surface measurement during image guided radiotherapy

    NASA Astrophysics Data System (ADS)

    Price, G. J.; Marchant, T. E.; Parkhurst, J. M.; Sharrock, P. J.; Whitfield, G. A.; Moore, C. J.

    2011-03-01

    In image guided radiotherapy (IGRT) two of the most promising recent developments are four dimensional cone beam CT (4D CBCT) and dynamic optical metrology of patient surfaces. 4D CBCT is now becoming commercially available and finds use in treatment planning and verification, and whilst optical monitoring is a young technology, its ability to measure during treatment delivery without dose consequences has led to its uptake in many institutes. In this paper, we demonstrate the use of dynamic patient surfaces, simultaneously captured during CBCT acquisition using an optical sensor, to phase sort projection images for 4D CBCT volume reconstruction. The dual modality approach we describe means that in addition to 4D volumetric data, the system provides correlated wide field measurements of the patient's skin surface with high spatial and temporal resolution. As well as the value of such complementary data in verification and motion analysis studies, it introduces flexibility into the acquisition of the signal required for phase sorting. The specific technique used may be varied according to individual patient circumstances and the imaging target. We give details of three different methods of obtaining a suitable signal from the optical surfaces: simply following the motion of triangulation spots used to calibrate the surfaces' absolute height; monitoring the surface height in a single, arbitrarily selected, camera pixel; and tracking, in three dimensions, the movement of a surface feature. In addition to describing the system and methodology, we present initial results from a case study oesophageal cancer patient.

  20. LOFAR sparse image reconstruction

    NASA Astrophysics Data System (ADS)

    Garsden, H.; Girard, J. N.; Starck, J. L.; Corbel, S.; Tasse, C.; Woiselle, A.; McKean, J. P.; van Amesfoort, A. S.; Anderson, J.; Avruch, I. M.; Beck, R.; Bentum, M. J.; Best, P.; Breitling, F.; Broderick, J.; Brüggen, M.; Butcher, H. R.; Ciardi, B.; de Gasperin, F.; de Geus, E.; de Vos, M.; Duscha, S.; Eislöffel, J.; Engels, D.; Falcke, H.; Fallows, R. A.; Fender, R.; Ferrari, C.; Frieswijk, W.; Garrett, M. A.; Grießmeier, J.; Gunst, A. W.; Hassall, T. E.; Heald, G.; Hoeft, M.; Hörandel, J.; van der Horst, A.; Juette, E.; Karastergiou, A.; Kondratiev, V. I.; Kramer, M.; Kuniyoshi, M.; Kuper, G.; Mann, G.; Markoff, S.; McFadden, R.; McKay-Bukowski, D.; Mulcahy, D. D.; Munk, H.; Norden, M. J.; Orru, E.; Paas, H.; Pandey-Pommier, M.; Pandey, V. N.; Pietka, G.; Pizzo, R.; Polatidis, A. G.; Renting, A.; Röttgering, H.; Rowlinson, A.; Schwarz, D.; Sluman, J.; Smirnov, O.; Stappers, B. W.; Steinmetz, M.; Stewart, A.; Swinbank, J.; Tagger, M.; Tang, Y.; Tasse, C.; Thoudam, S.; Toribio, C.; Vermeulen, R.; Vocks, C.; van Weeren, R. J.; Wijnholds, S. J.; Wise, M. W.; Wucknitz, O.; Yatawatta, S.; Zarka, P.; Zensus, A.

    2015-03-01

    Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various deconvolution and minimization methods. Aims: Recent papers have established a clear link between the discrete nature of radio interferometry measurement and the "compressed sensing" (CS) theory, which supports sparse reconstruction methods to form an image from the measured visibilities. Empowered by proximal theory, CS offers a sound framework for efficient global minimization and sparse data representation using fast algorithms. Combined with instrumental direction-dependent effects (DDE) in the scope of a real instrument, we developed and validated a new method based on this framework. Methods: We implemented a sparse reconstruction method in the standard LOFAR imaging tool and compared the photometric and resolution performance of this new imager with that of CLEAN-based methods (CLEAN and MS-CLEAN) with simulated and real LOFAR data. Results: We show that i) sparse reconstruction performs as well as CLEAN in recovering the flux of point sources; ii) performs much better on extended objects (the root mean square error is reduced by a factor of up to 10); and iii) provides a solution with an effective angular resolution 2-3 times better than the CLEAN images. Conclusions: Sparse recovery gives a correct photometry on high dynamic and wide-field images and improved realistic structures of extended sources (of simulated and real LOFAR datasets). This sparse reconstruction method is compatible with modern interferometric imagers that handle DDE corrections (A- and W-projections) required for current and future instruments such as LOFAR and SKA.

  1. The Use of Gated and 4D CT Imaging in Planning for Stereotactic Body Radiation Therapy

    SciTech Connect

    D'Souza, Warren D. . E-mail: wdsou001@umaryland.edu; Nazareth, Daryl P.; Zhang Bin; Deyoung, Chad; Suntharalingam, Mohan; Kwok, Young; Yu, Cedric X.; Regine, William F.

    2007-07-01

    The localization of treatment targets is of utmost importance for patients receiving stereotactic body radiation therapy (SBRT), where the dose per fraction is large. While both setup or respiration-induced motion components affect the localization of the treatment volume, the purpose of this work is to describe our management of the intrafraction localization uncertainty induced by normal respiration. At our institution, we have implemented gated computed tomography (CT) acquisition with an active breathing control system (ABC), and 4-dimensional (4D) CT using a skin-based marker and retrospective respiration phase-based image sorting. During gated simulation, 3D CT images were acquired corresponding to end-inhalation and end-exhalation. For 4D CT imaging, 3D CT images were acquired corresponding to 8 phases of the respiratory cycle. In addition to gated or 4D CT images, we acquired a conventional free-breathing CT (FB). For both gated and 4D CT images, the target contours were registered to the FB scan in the planning system. These contours were then combined in the FB image set to form the internal target volume (ITV). Dynamic conformal arc treatment plans were generated for the ITV using the FB scan and the gated or 4D scans with an additional 7-mm margin for patient setup uncertainty. We have described our results for a pancreas and a lung tumor case. Plans were normalized so that the PTV received 95% of the prescription dose. The dose distribution for all the critical structures in the pancreas and lung tumor cases resulted in increased sparing when the ITV was defined using gated or 4D CT images than when the FB scan was used. Our results show that patient-specific target definition using gated or 4D CT scans lead to improved normal tissue sparing.

  2. SU-E-J-157: Improving the Quality of T2-Weighted 4D Magnetic Resonance Imaging for Clinical Evaluation

    SciTech Connect

    Du, D; Mutic, S; Hu, Y; Caruthers, S; Glide-Hurst, C; Low, D

    2014-06-01

    Purpose: To develop an imaging technique that enables us to acquire T2- weighted 4D Magnetic Resonance Imaging (4DMRI) with sufficient spatial coverage, temporal resolution and spatial resolution for clinical evaluation. Methods: T2-weighed 4DMRI images were acquired from a healthy volunteer using a respiratory amplitude triggered T2-weighted Turbo Spin Echo sequence. 10 respiratory states were used to equally sample the respiratory range based on amplitude (0%, 20%i, 40%i, 60%i, 80%i, 100%, 80%e, 60%e, 40%e and 20%e). To avoid frequent scanning halts, a methodology was devised that split 10 respiratory states into two packages in an interleaved manner and packages were acquired separately. Sixty 3mm sagittal slices at 1.5mm in-plane spatial resolution were acquired to offer good spatial coverage and reasonable spatial resolution. The in-plane field of view was 375mm × 260mm with nominal scan time of 3 minutes 42 seconds. Acquired 2D images at the same respiratory state were combined to form the 3D image set corresponding to that respiratory state and reconstructed in the coronal view to evaluate whether all slices were at the same respiratory state. 3D image sets of 10 respiratory states represented a complete 4D MRI image set. Results: T2-weighted 4DMRI image were acquired in 10 minutes which was within clinical acceptable range. Qualitatively, the acquired MRI images had good image quality for delineation purposes. There were no abrupt position changes in reconstructed coronal images which confirmed that all sagittal slices were in the same respiratory state. Conclusion: We demonstrated it was feasible to acquire T2-weighted 4DMRI image set within a practical amount of time (10 minutes) that had good temporal resolution (10 respiratory states), spatial resolution (1.5mm × 1.5mm × 3.0mm) and spatial coverage (60 slices) for future clinical evaluation.

  3. SU-D-17A-04: The Impact of Audiovisual Biofeedback On Image Quality During 4D Functional and Anatomic Imaging: Results of a Prospective Clinical Trial

    SciTech Connect

    Keall, P; Pollock, S; Yang, J; Diehn, M; Berger, J; Graves, E; Loo, B; Yamamoto, T

    2014-06-01

    comprehension and capability. Supported by NIH/NCI R01 CA 093626, Stanford BioX Interdisciplinary Initiatives Program, NHMRC Australia Fellowship, and Kwanjeong Educational Foundation. GE Healthcare provided the Respiratory Gating Toolbox for 4D-PET image reconstruction. Stanford University owns US patent #E7955270 which is unlicensed to any commercial entity.

  4. Four-dimensional (4D) PET/CT imaging of the thorax

    SciTech Connect

    Nehmeh, S.A.; Erdi, Y.E.; Pan, T.

    2004-12-01

    We have reported in our previous studies on the methodology, and feasibility of 4D-PET (Gated PET) acquisition, to reduce respiratory motion artifact in PET imaging of the thorax. In this study, we expand our investigation to address the problem of respiration motion in PET/CT imaging. The respiratory motion of four lung cancer patients were monitored by tracking external markers placed on the thorax. A 4D-CT acquisition was performed using a 'step-and-shoot' technique, in which computed tomography (CT) projection data were acquired over a complete respiratory cycle at each couch position. The period of each CT acquisition segment was time stamped with an 'x-ray ON' signal, which was recorded by the tracking system. 4D-CT data were then sorted into 10 groups, according to their corresponding phase of the breathing cycle. 4D-PET data were acquired in the gated mode, where each breathing cycle was divided into ten 0.5 s bins. For both CT and PET acquisitions, patients received audio prompting to regularize breathing. The 4D-CT and 4D-PET data were then correlated according to respiratory phase. The effect of 4D acquisition on improving the co-registration of PET and CT images, reducing motion smearing, and consequently increase the quantitation of the SUV, were investigated. Also, quantitation of the tumor motions in PET, and CT, were studied and compared. 4D-PET with matching phase 4D-CTAC showed an improved accuracy in PET-CT image co-registration of up to 41%, compared to measurements from 4D-PET with clinical-CTAC. Gating PET data in correlation with respiratory motion reduced motion-induced smearing, thereby decreasing the observed tumor volume, by as much as 43%. 4D-PET lesions volumes showed a maximum deviation of 19% between clinical CT and phase- matched 4D-CT attenuation corrected PET images. In CT, 4D acquisition resulted in increasing the tumor volume in two patients by up to 79%, and decreasing it in the other two by up to 35%. Consequently, these

  5. Reconstruction of landslide movements by inversion of 4-D electrical resistivity tomography monitoring data

    NASA Astrophysics Data System (ADS)

    Wilkinson, Paul; Chambers, Jonathan; Uhlemann, Sebastian; Meldrum, Philip; Smith, Alister; Dixon, Neil; Loke, Meng Heng

    2016-02-01

    Reliable tomographic inversion of geoelectrical monitoring data from unstable slopes relies critically on knowing the electrode positions, which may move over time. We develop and present an innovative inverse method to recover movements in both surface directions from geoelectrical measurements made on a grid of monitoring electrodes. For the first time, we demonstrate this method using field data from an active landslide to recover sequences of movement over timescales of days to years. Comparison with GPS measurements demonstrated an accuracy of within 10% of the electrode spacing, sufficient to correct the majority of artifacts that would occur in subsequent image reconstructions if incorrect positions are used. Over short timescales where the corresponding subsurface resistivity changes were smaller, the constraints could be relaxed and an order-of-magnitude better accuracy was achievable. This enabled the onset and acceleration of landslide activity to be detected with a temporal resolution of a few days.

  6. Improvement of the cine-CT based 4D-CT imaging

    SciTech Connect

    Pan Tinsu; Sun Xiaojun; Luo Dershan

    2007-11-15

    An improved 4D-CT utility has been developed on the GE LightSpeed multislice CT (MSCT) and Discovery PET/CT scanners, which have the cine CT scan capability. Two new features have been added in this 4D-CT over the commercial Advantage 4D-CT from GE. One feature was a new tool for disabling parts of the respiratory signal with irregular respiration and improving the accuracy of phase determination for the respiratory signal from the Varian real-time positioning and monitoring (RPM) system before sorting of the cine CT images into the 4D-CT images. The second feature was to allow generation of the maximum-intensity-projection (MIP), average (AVG) and minimum-intensity-projection (mip) CT images from the cine CT images without a respiratory signal. The implementation enables the assessment of tumor motion in treatment planning with the MIP, AVG, and mip CT images on the GE MSCT and PET/CT scanners without the RPM and the Advantage 4D-CT with a GE Advantage windows workstation. Several clinical examples are included to illustrate this new application.

  7. PET Image Reconstruction Using Kernel Method

    PubMed Central

    Wang, Guobao; Qi, Jinyi

    2014-01-01

    Image reconstruction from low-count PET projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality. Inspired by the kernel methods in machine learning, this paper proposes a kernel based method that models PET image intensity in each pixel as a function of a set of features obtained from prior information. The kernel-based image model is incorporated into the forward model of PET projection data and the coefficients can be readily estimated by the maximum likelihood (ML) or penalized likelihood image reconstruction. A kernelized expectation-maximization (EM) algorithm is presented to obtain the ML estimate. Computer simulations show that the proposed approach can achieve better bias versus variance trade-off and higher contrast recovery for dynamic PET image reconstruction than the conventional maximum likelihood method with and without post-reconstruction denoising. Compared with other regularization-based methods, the kernel method is easier to implement and provides better image quality for low-count data. Application of the proposed kernel method to a 4D dynamic PET patient dataset showed promising results. PMID:25095249

  8. Exercises in PET Image Reconstruction

    NASA Astrophysics Data System (ADS)

    Nix, Oliver

    These exercises are complementary to the theoretical lectures about positron emission tomography (PET) image reconstruction. They aim at providing some hands on experience in PET image reconstruction and focus on demonstrating the different data preprocessing steps and reconstruction algorithms needed to obtain high quality PET images. Normalisation, geometric-, attenuation- and scatter correction are introduced. To explain the necessity of those some basics about PET scanner hardware, data acquisition and organisation are reviewed. During the course the students use a software application based on the STIR (software for tomographic image reconstruction) library 1,2 which allows them to dynamically select or deselect corrections and reconstruction methods as well as to modify their most important parameters. Following the guided tutorial, the students get an impression on the effect the individual data precorrections have on image quality and what happens if they are forgotten. Several data sets in sinogram format are provided, such as line source data, Jaszczak phantom data sets with high and low statistics and NEMA whole body phantom data. The two most frequently used reconstruction algorithms in PET image reconstruction, filtered back projection (FBP) and the iterative OSEM (ordered subset expectation maximation) approach are used to reconstruct images. The exercise should help the students gaining an understanding what the reasons for inferior image quality and artefacts are and how to improve quality by a clever choice of reconstruction parameters.

  9. Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization

    SciTech Connect

    Segars, W. P.; Bond, Jason; Frush, Jack; Hon, Sylvia; Eckersley, Chris; Samei, E.; Williams, Cameron H.; Frush, D.; Feng Jianqiao; Tward, Daniel J.; Ratnanather, J. T.; Miller, M. I.

    2013-04-15

    Purpose: The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms. Methods: The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models. Results: Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve

  10. A Workstation for Interactive Display and Quantitative Analysis of 3-D and 4-D Biomedical Images

    PubMed Central

    Robb, R.A.; Heffeman, P.B.; Camp, J.J.; Hanson, D.P.

    1986-01-01

    The capability to extract objective and quantitatively accurate information from 3-D radiographic biomedical images has not kept pace with the capabilities to produce the images themselves. This is rather an ironic paradox, since on the one hand the new 3-D and 4-D imaging capabilities promise significant potential for providing greater specificity and sensitivity (i.e., precise objective discrimination and accurate quantitative measurement of body tissue characteristics and function) in clinical diagnostic and basic investigative imaging procedures than ever possible before, but on the other hand, the momentous advances in computer and associated electronic imaging technology which have made these 3-D imaging capabilities possible have not been concomitantly developed for full exploitation of these capabilities. Therefore, we have developed a powerful new microcomputer-based system which permits detailed investigations and evaluation of 3-D and 4-D (dynamic 3-D) biomedical images. The system comprises a special workstation to which all the information in a large 3-D image data base is accessible for rapid display, manipulation, and measurement. The system provides important capabilities for simultaneously representing and analyzing both structural and functional data and their relationships in various organs of the body. This paper provides a detailed description of this system, as well as some of the rationale, background, theoretical concepts, and practical considerations related to system implementation. ImagesFigure 5Figure 7Figure 8Figure 9Figure 10Figure 11Figure 12Figure 13Figure 14Figure 15Figure 16

  11. TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients

    SciTech Connect

    Yang, F; Nyflot, M; Bowen, S; Kinahan, P; Sandison, G

    2014-06-15

    Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4D PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5% to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.

  12. First Steps Toward Ultrasound-Based Motion Compensation for Imaging and Therapy: Calibration with an Optical System and 4D PET Imaging.

    PubMed

    Schwaab, Julia; Kurz, Christopher; Sarti, Cristina; Bongers, André; Schoenahl, Frédéric; Bert, Christoph; Debus, Jürgen; Parodi, Katia; Jenne, Jürgen Walter

    2015-01-01

    Target motion, particularly in the abdomen, due to respiration or patient movement is still a challenge in many diagnostic and therapeutic processes. Hence, methods to detect and compensate this motion are required. Diagnostic ultrasound (US) represents a non-invasive and dose-free alternative to fluoroscopy, providing more information about internal target motion than respiration belt or optical tracking. The goal of this project is to develop an US-based motion tracking for real-time motion correction in radiation therapy and diagnostic imaging, notably in 4D positron emission tomography (PET). In this work, a workflow is established to enable the transformation of US tracking data to the coordinates of the treatment delivery or imaging system - even if the US probe is moving due to respiration. It is shown that the US tracking signal is equally adequate for 4D PET image reconstruction as the clinically used respiration belt and provides additional opportunities in this concern. Furthermore, it is demonstrated that the US probe being within the PET field of view generally has no relevant influence on the image quality. The accuracy and precision of all the steps in the calibration workflow for US tracking-based 4D PET imaging are found to be in an acceptable range for clinical implementation. Eventually, we show in vitro that an US-based motion tracking in absolute room coordinates with a moving US transducer is feasible. PMID:26649277

  13. First Steps Toward Ultrasound-Based Motion Compensation for Imaging and Therapy: Calibration with an Optical System and 4D PET Imaging

    PubMed Central

    Schwaab, Julia; Kurz, Christopher; Sarti, Cristina; Bongers, André; Schoenahl, Frédéric; Bert, Christoph; Debus, Jürgen; Parodi, Katia; Jenne, Jürgen Walter

    2015-01-01

    Target motion, particularly in the abdomen, due to respiration or patient movement is still a challenge in many diagnostic and therapeutic processes. Hence, methods to detect and compensate this motion are required. Diagnostic ultrasound (US) represents a non-invasive and dose-free alternative to fluoroscopy, providing more information about internal target motion than respiration belt or optical tracking. The goal of this project is to develop an US-based motion tracking for real-time motion correction in radiation therapy and diagnostic imaging, notably in 4D positron emission tomography (PET). In this work, a workflow is established to enable the transformation of US tracking data to the coordinates of the treatment delivery or imaging system – even if the US probe is moving due to respiration. It is shown that the US tracking signal is equally adequate for 4D PET image reconstruction as the clinically used respiration belt and provides additional opportunities in this concern. Furthermore, it is demonstrated that the US probe being within the PET field of view generally has no relevant influence on the image quality. The accuracy and precision of all the steps in the calibration workflow for US tracking-based 4D PET imaging are found to be in an acceptable range for clinical implementation. Eventually, we show in vitro that an US-based motion tracking in absolute room coordinates with a moving US transducer is feasible. PMID:26649277

  14. Robust segmentation of 4D cardiac MRI-tagged images via spatio-temporal propagation

    NASA Astrophysics Data System (ADS)

    Qian, Zhen; Huang, Xiaolei; Metaxas, Dimitris N.; Axel, Leon

    2005-04-01

    In this paper we present a robust method for segmenting and tracking cardiac contours and tags in 4D cardiac MRI tagged images via spatio-temporal propagation. Our method is based on two main techniques: the Metamorphs Segmentation for robust boundary estimation, and the tunable Gabor filter bank for tagging lines enhancement, removal and myocardium tracking. We have developed a prototype system based on the integration of these two techniques, and achieved efficient, robust segmentation and tracking with minimal human interaction.

  15. Four-dimensional magnetic resonance imaging (4D-MRI) using image-based respiratory surrogate: A feasibility study

    PubMed Central

    Cai, Jing; Chang, Zheng; Wang, Zhiheng; Paul Segars, William; Yin, Fang-Fang

    2011-01-01

    Purpose: Four-dimensional computed tomography (4D-CT) has been widely used in radiation therapy to assess patient-specific breathing motion for determining individual safety margins. However, it has two major drawbacks: low soft-tissue contrast and an excessive imaging dose to the patient. This research aimed to develop a clinically feasible four-dimensional magnetic resonance imaging (4D-MRI) technique to overcome these limitations. Methods: The proposed 4D-MRI technique was achieved by continuously acquiring axial images throughout the breathing cycle using fast 2D cine-MR imaging, and then retrospectively sorting the images by respiratory phase. The key component of the technique was the use of body area (BA) of the axial MR images as an internal respiratory surrogate to extract the breathing signal. The validation of the BA surrogate was performed using 4D-CT images of 12 cancer patients by comparing the respiratory phases determined using the BA method to those determined clinically using the Real-time position management (RPM) system. The feasibility of the 4D-MRI technique was tested on a dynamic motion phantom, the 4D extended Cardiac Torso (XCAT) digital phantom, and two healthy human subjects. Results: Respiratory phases determined from the BA matched closely to those determined from the RPM: mean (±SD) difference in phase: −3.9% (±6.4%); mean (±SD) absolute difference in phase: 10.40% (±3.3%); mean (±SD) correlation coefficient: 0.93 (±0.04). In the motion phantom study, 4D-MRI clearly showed the sinusoidal motion of the phantom; image artifacts observed were minimal to none. Motion trajectories measured from 4D-MRI and 2D cine-MRI (used as a reference) matched excellently: the mean (±SD) absolute difference in motion amplitude: −0.3 (±0.5) mm. In the 4D-XCAT phantom study, the simulated “4D-MRI” images showed good consistency with the original 4D-XCAT phantom images. The motion trajectory of the hypothesized “tumor” matched

  16. 4D dynamic imaging of the eye using ultrahigh speed SS-OCT

    NASA Astrophysics Data System (ADS)

    Liu, Jonathan J.; Grulkowski, Ireneusz; Potsaid, Benjamin; Jayaraman, Vijaysekhar; Cable, Alex E.; Kraus, Martin F.; Hornegger, Joachim; Duker, Jay S.; Fujimoto, James G.

    2013-03-01

    Recent advances in swept-source / Fourier domain optical coherence tomography (SS-OCT) technology enable in vivo ultrahigh speed imaging, offering a promising technique for four-dimensional (4-D) imaging of the eye. Using an ultrahigh speed tunable vertical cavity surface emitting laser (VCSEL) light source based SS-OCT prototype system, we performed imaging of human eye dynamics in four different imaging modes: 1) Pupillary reaction to light at 200,000 axial scans per second and 9 μm resolution in tissue. 2) Anterior eye focusing dynamics at 100,000 axial scans per second and 9 μm resolution in tissue. 3) Tear film break up at 50,000 axial scans per second and 19 μm resolution in tissue. 4) Retinal blood flow at 800,000 axial scans per second and 12 μm resolution in tissue. The combination of tunable ultrahigh speeds and long coherence length of the VCSEL along with the outstanding roll-off performance of SS-OCT makes this technology an ideal tool for time-resolved volumetric imaging of the eye. Visualization and quantitative analysis of 4-D OCT data can potentially provide insight to functional and structural changes in the eye during disease progression. Ultrahigh speed imaging using SS-OCT promises to enable novel 4-D visualization of realtime dynamic processes of the human eye. Furthermore, this non-invasive imaging technology is a promising tool for research to characterize and understand a variety of visual functions.

  17. Real-time volume rendering of 4D image using 3D texture mapping

    NASA Astrophysics Data System (ADS)

    Hwang, Jinwoo; Kim, June-Sic; Kim, Jae Seok; Kim, In Young; Kim, Sun Il

    2001-05-01

    Four dimensional image is 3D volume data that varies with time. It is used to express deforming or moving object in virtual surgery of 4D ultrasound. It is difficult to render 4D image by conventional ray-casting or shear-warp factorization methods because of their time-consuming rendering time or pre-processing stage whenever the volume data are changed. Even 3D texture mapping is used, repeated volume loading is also time-consuming in 4D image rendering. In this study, we propose a method to reduce data loading time using coherence between currently loaded volume and previously loaded volume in order to achieve real time rendering based on 3D texture mapping. Volume data are divided into small bricks and each brick being loaded is tested for similarity to one which was already loaded in memory. If the brick passed the test, it is defined as 3D texture by OpenGL functions. Later, the texture slices of the brick are mapped into polygons and blended by OpenGL blending functions. All bricks undergo this test. Continuously deforming fifty volumes are rendered in interactive time with SGI ONYX. Real-time volume rendering based on 3D texture mapping is currently available on PC.

  18. Crystallographic image reconstruction problem

    NASA Astrophysics Data System (ADS)

    ten Eyck, Lynn F.

    1993-11-01

    The crystallographic X-ray diffraction experiment gives the amplitudes of the Fourier series expansion of the electron density distribution within the crystal. The 'phase problem' in crystallography is the determination of the phase angles of the Fourier coefficients required to calculate the Fourier synthesis and reveal the molecular structure. The magnitude of this task varies enormously as the size of the structures ranges from a few atoms to thousands of atoms, and the number of Fourier coefficients ranges from hundreds to hundreds of thousands. The issue is further complicated for large structures by limited resolution. This problem is solved for 'small' molecules (up to 200 atoms and a few thousand Fourier coefficients) by methods based on probabilistic models which depend on atomic resolution. These methods generally fail for larger structures such as proteins. The phase problem for protein molecules is generally solved either by laborious experimental methods or by exploiting known similarities to solved structures. Various direct methods have been attempted for very large structures over the past 15 years, with gradually improving results -- but so far no complete success. This paper reviews the features of the crystallographic image reconstruction problem which render it recalcitrant, and describes recent encouraging progress in the application of maximum entropy methods to this problem.

  19. Impact of CT attenuation correction method on quantitative respiratory-correlated (4D) PET/CT imaging

    SciTech Connect

    Nyflot, Matthew J.; Lee, Tzu-Cheng; Alessio, Adam M.; Kinahan, Paul E.; Wollenweber, Scott D.; Stearns, Charles W.; Bowen, Stephen R.

    2015-01-15

    Purpose: Respiratory-correlated positron emission tomography (PET/CT) 4D PET/CT is used to mitigate errors from respiratory motion; however, the optimal CT attenuation correction (CTAC) method for 4D PET/CT is unknown. The authors performed a phantom study to evaluate the quantitative performance of CTAC methods for 4D PET/CT in the ground truth setting. Methods: A programmable respiratory motion phantom with a custom movable insert designed to emulate a lung lesion and lung tissue was used for this study. The insert was driven by one of five waveforms: two sinusoidal waveforms or three patient-specific respiratory waveforms. 3DPET and 4DPET images of the phantom under motion were acquired and reconstructed with six CTAC methods: helical breath-hold (3DHEL), helical free-breathing (3DMOT), 4D phase-averaged (4DAVG), 4D maximum intensity projection (4DMIP), 4D phase-matched (4DMATCH), and 4D end-exhale (4DEXH) CTAC. Recovery of SUV{sub max}, SUV{sub mean}, SUV{sub peak}, and segmented tumor volume was evaluated as RC{sub max}, RC{sub mean}, RC{sub peak}, and RC{sub vol}, representing percent difference relative to the static ground truth case. Paired Wilcoxon tests and Kruskal–Wallis ANOVA were used to test for significant differences. Results: For 4DPET imaging, the maximum intensity projection CTAC produced significantly more accurate recovery coefficients than all other CTAC methods (p < 0.0001 over all metrics). Over all motion waveforms, ratios of 4DMIP CTAC recovery were 0.2 ± 5.4, −1.8 ± 6.5, −3.2 ± 5.0, and 3.0 ± 5.9 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. In comparison, recovery coefficients for phase-matched CTAC were −8.4 ± 5.3, −10.5 ± 6.2, −7.6 ± 5.0, and −13.0 ± 7.7 for RC{sub max}, RC{sub peak}, RC{sub mean}, and RC{sub vol}. When testing differences between phases over all CTAC methods and waveforms, end-exhale phases were significantly more accurate (p = 0.005). However, these differences were driven by

  20. Automated Lung Segmentation and Image Quality Assessment for Clinical 3-D/4-D-Computed Tomography

    PubMed Central

    Li, Guang

    2014-01-01

    4-D-computed tomography (4DCT) provides not only a new dimension of patient-specific information for radiation therapy planning and treatment, but also a challenging scale of data volume to process and analyze. Manual analysis using existing 3-D tools is unable to keep up with vastly increased 4-D data volume, automated processing and analysis are thus needed to process 4DCT data effectively and efficiently. In this paper, we applied ideas and algorithms from image/signal processing, computer vision, and machine learning to 4DCT lung data so that lungs can be reliably segmented in a fully automated manner, lung features can be visualized and measured on the fly via user interactions, and data quality classifications can be computed in a robust manner. Comparisons of our results with an established treatment planning system and calculation by experts demonstrated negligible discrepancies (within ±2%) for volume assessment but one to two orders of magnitude performance enhancement. An empirical Fourier-analysis-based quality measure-delivered performances closely emulating human experts. Three machine learners are inspected to justify the viability of machine learning techniques used to robustly identify data quality of 4DCT images in the scalable manner. The resultant system provides a toolkit that speeds up 4-D tasks in the clinic and facilitates clinical research to improve current clinical practice. PMID:25621194

  1. Four-dimensional cardiac reconstruction from rotational x-ray sequences: first results for 4D coronary angiography

    NASA Astrophysics Data System (ADS)

    Hansis, Eberhard; Schomberg, Hermann; Erhard, Klaus; Dössel, Olaf; Grass, Michael

    2009-02-01

    The tomographic reconstruction of the beating heart requires dedicated methods. One possibility is gated reconstruction, where only data corresponding to a certain motion state are incorporated. Another one is motioncompensated reconstruction with a pre-computed motion vector field, which requires a preceding estimation of the motion. Here, results of a new approach are presented: simultaneous reconstruction of a three-dimensional object and its motion over time, yielding a fully four-dimensional representation. The object motion is modeled by a time-dependent elastic transformation. The reconstruction is carried out with an iterative gradient-descent algorithm which simultaneously optimizes the three-dimensional image and the motion parameters. The method was tested on a simulated rotational X-ray acquisition of a dynamic coronary artery phantom, acquired on a C-arm system with a slowly rotating C-arm. Accurate reconstruction of both absorption coefficient and motion could be achieved. First results from experiments on clinical rotational X-ray coronary angiography data are shown. The resulting reconstructions enable the analysis of both static properties, such as vessel geometry and cross-sectional areas, and dynamic properties, like magnitude, speed, and synchrony of motion during the cardiac cycle.

  2. Joint surface reconstruction and 4D deformation estimation from sparse data and prior knowledge for marker-less Respiratory motion tracking

    SciTech Connect

    Berkels, Benjamin; Rumpf, Martin; Bauer, Sebastian; Ettl, Svenja; Arold, Oliver; Hornegger, Joachim

    2013-09-15

    Purpose: The intraprocedural tracking of respiratory motion has the potential to substantially improve image-guided diagnosis and interventions. The authors have developed a sparse-to-dense registration approach that is capable of recovering the patient's external 3D body surface and estimating a 4D (3D + time) surface motion field from sparse sampling data and patient-specific prior shape knowledge.Methods: The system utilizes an emerging marker-less and laser-based active triangulation (AT) sensor that delivers sparse but highly accurate 3D measurements in real-time. These sparse position measurements are registered with a dense reference surface extracted from planning data. Thereby a dense displacement field is recovered, which describes the spatio-temporal 4D deformation of the complete patient body surface, depending on the type and state of respiration. It yields both a reconstruction of the instantaneous patient shape and a high-dimensional respiratory surrogate for respiratory motion tracking. The method is validated on a 4D CT respiration phantom and evaluated on both real data from an AT prototype and synthetic data sampled from dense surface scans acquired with a structured-light scanner.Results: In the experiments, the authors estimated surface motion fields with the proposed algorithm on 256 datasets from 16 subjects and in different respiration states, achieving a mean surface reconstruction accuracy of ±0.23 mm with respect to ground truth data—down from a mean initial surface mismatch of 5.66 mm. The 95th percentile of the local residual mesh-to-mesh distance after registration did not exceed 1.17 mm for any subject. On average, the total runtime of our proof of concept CPU implementation is 2.3 s per frame, outperforming related work substantially.Conclusions: In external beam radiation therapy, the approach holds potential for patient monitoring during treatment using the reconstructed surface, and for motion-compensated dose delivery using

  3. Dosimetric quality assurance of highly conformal external beam treatments: from 2D phantom comparisons to 4D patient dose reconstruction

    NASA Astrophysics Data System (ADS)

    Feygelman, V.; Nelms, B.

    2013-06-01

    As IMRT technology continues to evolve, so do the dosimetric QA methods. A historical review of those is presented, starting with longstanding techniques such as film and ion chamber in a phantom and progressing towards 3D and 4D dose reconstruction in the patient. Regarding patient-specific QA, we envision that the currently prevalent limited comparison of dose distributions in the phantom by γ-analysis will be eventually replaced by clinically meaningful patient dose analyses with improved sensitivity and specificity. In a larger sense, we envision a future of QA built upon lessons from the rich history of "quality" as a science and philosophy. This future will aim to improve quality (and ultimately reduce cost) via advanced commissioning processes that succeed in detecting and rooting out systematic errors upstream of patient treatment, thus reducing our reliance on, and the resource burden associated with, per-beam/per-plan inspection.

  4. ANALYZING IMAGING BIOMARKERS FOR TRAUMATIC BRAIN INJURY USING 4D MODELING OF LONGITUDINAL MRI

    PubMed Central

    Wang, Bo; Prastawa, Marcel; Irimia, Andrei; Chambers, Micah C.; Sadeghi, Neda; Vespa, Paul M.; van Horn, John D.; Gerig, Guido

    2013-01-01

    Quantitative imaging biomarkers are important for assessment of impact, recovery and treatment efficacy in patients with traumatic brain injury (TBI). To our knowledge, the identification of such biomarkers characterizing disease progress and recovery has been insufficiently explored in TBI due to difficulties in registration of baseline and follow-up data and automatic segmentation of tissue and lesions from multimodal, longitudinal MR image data. We propose a new methodology for computing imaging biomarkers in TBI by extending a recently proposed spatiotemporal 4D modeling approach in order to compute quantitative features of tissue change. The proposed method computes surface-based and voxel-based measurements such as cortical thickness, volume changes, and geometric deformation. We analyze the potential for clinical use of these biomarkers by correlating them with TBI-specific patient scores at the level of the whole brain and of individual regions. Our preliminary results indicate that the proposed voxel-based biomarkers are correlated with clinical outcomes. PMID:24443697

  5. 4D-CT imaging of a volume influenced by respiratory motion on multi-slice CT.

    PubMed

    Pan, Tinsu; Lee, Ting-Yim; Rietzel, Eike; Chen, George T Y

    2004-02-01

    We propose a new scanning protocol for generating 4D-CT image data sets influenced by respiratory motion. A cine scanning protocol is used during data acquisition, and two registration methods are used to sort images into temporal phases. A volume is imaged in multiple acquisitions of 1 or 2 cm length along the cranial-caudal direction. In each acquisition, the scans are continuously acquired for a time interval greater than or equal to the average respiratory cycle plus the duration of the data for an image reconstruction. The x ray is turned off during CT table translation and the acquisition is repeated until the prescribed volume is completely scanned. The scanning for 20 cm coverage takes about 1 min with an eight-slice CT or 2 mins with a four-slice CT. After data acquisition, the CT data are registered into respiratory phases based on either an internal anatomical match or an external respiratory signal. The internal approach registers the data according to correlation of anatomy in the CT images between two adjacent locations in consecutive respiratory cycles. We have demonstrated the technique with ROIs placed in the region of diaphragm. The external approach registers the image data according to an externally recorded respiratory signal generated by the Real-Time Position Management (RPM) Respiratory Gating System (Varian Medical Systems, Palo Alto, CA). Compared with previously reported prospective or retrospective imaging of the respiratory motion with a single-slice or multi-slice CT, the 4D-CT method proposed here provides (1) a shorter scan time of three to six times faster than the single-slice CT with prospective gating; (2) a shorter scan time of two to four times improvement over a previously reported multi-slice CT implementation, and (3) images over all phases of a breathing cycle. We have applied the scanning and registration methods on phantom, animal and patients, and initial results suggest the applicability of both the scanning and the

  6. Segmentation of brain tumors in 4D MR images using the hidden Markov model.

    PubMed

    Solomon, Jeffrey; Butman, John A; Sood, Arun

    2006-12-01

    Tumor size is an objective measure that is used to evaluate the effectiveness of anticancer agents. Responses to therapy are categorized as complete response, partial response, stable disease and progressive disease. Implicit in this scheme is the change in the tumor over time; however, most tumor segmentation algorithms do not use temporal information. Here we introduce an automated method using probabilistic reasoning over both space and time to segment brain tumors from 4D spatio-temporal MRI data. The 3D expectation-maximization method is extended using the hidden Markov model to infer tumor classification based on previous and subsequent segmentation results. Spatial coherence via a Markov Random Field was included in the 3D spatial model. Simulated images as well as patient images from three independent sources were used to validate this method. The sensitivity and specificity of tumor segmentation using this spatio-temporal model is improved over commonly used spatial or temporal models alone. PMID:17050032

  7. Performance evaluation and optimization of BM4D-AV denoising algorithm for cone-beam CT images

    NASA Astrophysics Data System (ADS)

    Huang, Kuidong; Tian, Xiaofei; Zhang, Dinghua; Zhang, Hua

    2015-12-01

    The broadening application of cone-beam Computed Tomography (CBCT) in medical diagnostics and nondestructive testing, necessitates advanced denoising algorithms for its 3D images. The block-matching and four dimensional filtering algorithm with adaptive variance (BM4D-AV) is applied to the 3D image denoising in this research. To optimize it, the key filtering parameters of the BM4D-AV algorithm are assessed firstly based on the simulated CBCT images and a table of optimized filtering parameters is obtained. Then, considering the complexity of the noise in realistic CBCT images, possible noise standard deviations in BM4D-AV are evaluated to attain the chosen principle for the realistic denoising. The results of corresponding experiments demonstrate that the BM4D-AV algorithm with optimized parameters presents excellent denosing effect on the realistic 3D CBCT images.

  8. Using 4D Cardiovascular Magnetic Resonance Imaging to Validate Computational Fluid Dynamics: A Case Study

    PubMed Central

    Biglino, Giovanni; Cosentino, Daria; Steeden, Jennifer A.; De Nova, Lorenzo; Castelli, Matteo; Ntsinjana, Hopewell; Pennati, Giancarlo; Taylor, Andrew M.; Schievano, Silvia

    2015-01-01

    Computational fluid dynamics (CFD) can have a complementary predictive role alongside the exquisite visualization capabilities of 4D cardiovascular magnetic resonance (CMR) imaging. In order to exploit these capabilities (e.g., for decision-making), it is necessary to validate computational models against real world data. In this study, we sought to acquire 4D CMR flow data in a controllable, experimental setup and use these data to validate a corresponding computational model. We applied this paradigm to a case of congenital heart disease, namely, transposition of the great arteries (TGA) repaired with arterial switch operation. For this purpose, a mock circulatory loop compatible with the CMR environment was constructed and two detailed aortic 3D models (i.e., one TGA case and one normal aortic anatomy) were tested under realistic hemodynamic conditions, acquiring 4D CMR flow. The same 3D domains were used for multi-scale CFD simulations, whereby the remainder of the mock circulatory system was appropriately summarized with a lumped parameter network. Boundary conditions of the simulations mirrored those measured in vitro. Results showed a very good quantitative agreement between experimental and computational models in terms of pressure (overall maximum % error = 4.4% aortic pressure in the control anatomy) and flow distribution data (overall maximum % error = 3.6% at the subclavian artery outlet of the TGA model). Very good qualitative agreement could also be appreciated in terms of streamlines, throughout the cardiac cycle. Additionally, velocity vectors in the ascending aorta revealed less symmetrical flow in the TGA model, which also exhibited higher wall shear stress in the anterior ascending aorta. PMID:26697416

  9. The development of a population of 4D pediatric XCAT phantoms for CT imaging research and optimization

    NASA Astrophysics Data System (ADS)

    Norris, Hannah; Zhang, Yakun; Frush, Jack; Sturgeon, Gregory M.; Minhas, Anum; Tward, Daniel J.; Ratnanather, J. Tilak; Miller, M. I.; Frush, Donald; Samei, Ehsan; Segars, W. Paul

    2014-03-01

    With the increased use of CT examinations, the associated radiation dose has become a large concern, especially for pediatrics. Much research has focused on reducing radiation dose through new scanning and reconstruction methods. Computational phantoms provide an effective and efficient means for evaluating image quality, patient-specific dose, and organ-specific dose in CT. We previously developed a set of highly-detailed 4D reference pediatric XCAT phantoms at ages of newborn, 1, 5, 10, and 15 years with organ and tissues masses matched to ICRP Publication 89 values. We now extend this reference set to a series of 64 pediatric phantoms of a variety of ages and height and weight percentiles, representative of the public at large. High resolution PET-CT data was reviewed by a practicing experienced radiologist for anatomic regularity and was then segmented with manual and semi-automatic methods to form a target model. A Multi-Channel Large Deformation Diffeomorphic Metric Mapping (MC-LDDMM) algorithm was used to calculate the transform from the best age matching pediatric reference phantom to the patient target. The transform was used to complete the target, filling in the non-segmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. 3D CT data was simulated from the phantoms to demonstrate their ability to generate realistic, patient quality imaging data. The population of pediatric phantoms developed in this work provides a vital tool to investigate dose reduction techniques in 3D and 4D pediatric CT.

  10. Enhancing a diffusion algorithm for 4D image segmentation using local information

    NASA Astrophysics Data System (ADS)

    Lösel, Philipp; Heuveline, Vincent

    2016-03-01

    Inspired by the diffusion of a particle, we present a novel approach for performing a semiautomatic segmentation of tomographic images in 3D, 4D or higher dimensions to meet the requirements of high-throughput measurements in a synchrotron X-ray microtomograph. Given a small number of 2D-slices with at least two manually labeled segments, one can either analytically determine the probability that an intelligently weighted random walk starting at one labeled pixel will be at a certain time at a specific position in the dataset or determine the probability approximately by performing several random walks. While the weights of a random walk take into account local information at the starting point, the random walk itself can be in any dimension. Starting a great number of random walks in each labeled pixel, a voxel in the dataset will be hit by several random walks over time. Hence, the image can be segmented by assigning each voxel to the label where the random walks most likely started from. Due to the high scalability of random walks, this approach is suitable for high throughput measurements. Additionally, we describe an interactively adjusted active contours slice by slice method considering local information, where we start with one manually labeled slice and move forward in any direction. This approach is superior with respect to accuracy towards the diffusion algorithm but inferior in the amount of tedious manual processing steps. The methods were applied on 3D and 4D datasets and evaluated by means of manually labeled images obtained in a realistic scenario with biologists.

  11. Quantifying the impact of respiratory-gated 4D CT acquisition on thoracic image quality: A digital phantom study

    SciTech Connect

    Bernatowicz, K. Knopf, A.; Lomax, A.; Keall, P.; Kipritidis, J.; Mishra, P.

    2015-01-15

    Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CT can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results

  12. brainR: Interactive 3 and 4D Images of High Resolution Neuroimage Data

    PubMed Central

    Muschelli, John; Sweeney, Elizabeth; Crainiceanu, Ciprian

    2016-01-01

    We provide software tools for displaying and publishing interactive 3-dimensional (3D) and 4-dimensional (4D) figures to html webpages, with examples of high-resolution brain imaging. Our framework is based in the R statistical software using the rgl package, a 3D graphics library. We build on this package to allow manipulation of figures including rotation and translation, zooming, coloring of brain substructures, adjusting transparency levels, and addition/or removal of brain structures. The need for better visualization tools of ultra high dimensional data is ever present; we are providing a clean, simple, web-based option. We also provide a package (brainR) for users to readily implement these tools. PMID:27330829

  13. Metal-ceramic interfaces: Overlayer-induced reconstruction and magnetism of 4d transition-metal monolayers

    SciTech Connect

    Wu, R.; Freeman, A.J.

    1995-02-15

    Structural, electronic, and magnetic properties of metal-ceramic interfaces, M/MgO(001) (M=Pd, Rh, and Ru), have been investigated using the full potential linearized augmented-plane-wave method. Ru and Rh monolayers are found to be able to retain large spin magnetic moments on MgO(001) (1.95 {mu}{sub B} and 1.21 {mu}{sub B} for Ru and Ph; respectively) -- indicating, in principle, the potential application of MgO(001) as a benign substrate for 4d monolayer magnetism. Significantly, according to our atomic-force determinations, the metal overlayers induce a sizable buckling reconstruction in the interfacial MgO layer, which enhances the M-MgO binding energy by 0.1 eV. The weak M-0 interaction is mainly via tail effects; however, it affects the density of states at the Fermi level for Pd/Mg0(001) significantly and completely eliminates the small magnetic moment of the free Pd monolaver (0.34{mu}{sub B}).

  14. Sample Drift Correction Following 4D Confocal Time-lapse Imaging

    PubMed Central

    Parslow, Adam; Cardona, Albert; Bryson-Richardson, Robert J.

    2014-01-01

    The generation of four-dimensional (4D) confocal datasets; consisting of 3D image sequences over time; provides an excellent methodology to capture cellular behaviors involved in developmental processes.  The ability to track and follow cell movements is limited by sample movements that occur due to drift of the sample or, in some cases, growth during image acquisition. Tracking cells in datasets affected by drift and/or growth will incorporate these movements into any analysis of cell position. This may result in the apparent movement of static structures within the sample. Therefore prior to cell tracking, any sample drift should be corrected. Using the open source Fiji distribution 1  of ImageJ 2,3 and the incorporated LOCI tools 4, we developed the Correct 3D drift plug-in to remove erroneous sample movement in confocal datasets. This protocol effectively compensates for sample translation or alterations in focal position by utilizing phase correlation to register each time-point of a four-dimensional confocal datasets while maintaining the ability to visualize and measure cell movements over extended time-lapse experiments. PMID:24747942

  15. Super-resolution image reconstruction using diffuse source models.

    PubMed

    Ellis, Michael A; Viola, Francesco; Walker, William F

    2010-06-01

    Image reconstruction is central to many scientific fields, from medical ultrasound and sonar to computed tomography and computer vision. Although lenses play a critical reconstruction role in these fields, digital sensors enable more sophisticated computational approaches. A variety of computational methods have thus been developed, with the common goal of increasing contrast and resolution to extract the greatest possible information from raw data. This paper describes a new image reconstruction method named the Diffuse Time-domain Optimized Near-field Estimator (dTONE). dTONE represents each hypothetical target in the system model as a diffuse region of targets rather than a single discrete target, which more accurately represents the experimental data that arise from signal sources in continuous space, with no additional computational requirements at the time of image reconstruction. Simulation and experimental ultrasound images of animal tissues show that dTONE achieves image resolution and contrast far superior to those of conventional image reconstruction methods. We also demonstrate the increased robustness of the diffuse target model to major sources of image degradation through the addition of electronic noise, phase aberration and magnitude aberration to ultrasound simulations. Using experimental ultrasound data from a tissue-mimicking phantom containing a 3-mm-diameter anechoic cyst, the conventionally reconstructed image has a cystic contrast of -6.3 dB, whereas the dTONE image has a cystic contrast of -14.4 dB.

  16. Image processing and reconstruction

    SciTech Connect

    Chartrand, Rick

    2012-06-15

    This talk will examine some mathematical methods for image processing and the solution of underdetermined, linear inverse problems. The talk will have a tutorial flavor, mostly accessible to undergraduates, while still presenting research results. The primary approach is the use of optimization problems. We will find that relaxing the usual assumption of convexity will give us much better results.

  17. Dynamic real-time 4D cardiac MDCT image display using GPU-accelerated volume rendering.

    PubMed

    Zhang, Qi; Eagleson, Roy; Peters, Terry M

    2009-09-01

    Intraoperative cardiac monitoring, accurate preoperative diagnosis, and surgical planning are important components of minimally-invasive cardiac therapy. Retrospective, electrocardiographically (ECG) gated, multidetector computed tomographical (MDCT), four-dimensional (3D + time), real-time, cardiac image visualization is an important tool for the surgeon in such procedure, particularly if the dynamic volumetric image can be registered to, and fused with the actual patient anatomy. The addition of stereoscopic imaging provides a more intuitive environment by adding binocular vision and depth cues to structures within the beating heart. In this paper, we describe the design and implementation of a comprehensive stereoscopic 4D cardiac image visualization and manipulation platform, based on the opacity density radiation model, which exploits the power of modern graphics processing units (GPUs) in the rendering pipeline. In addition, we present a new algorithm to synchronize the phases of the dynamic heart to clinical ECG signals, and to calculate and compensate for latencies in the visualization pipeline. A dynamic multiresolution display is implemented to enable the interactive selection and emphasis of volume of interest (VOI) within the entire contextual cardiac volume and to enhance performance, and a novel color and opacity adjustment algorithm is designed to increase the uniformity of the rendered multiresolution image of heart. Our system provides a visualization environment superior to noninteractive software-based implementations, but with a rendering speed that is comparable to traditional, but inferior quality, volume rendering approaches based on texture mapping. This retrospective ECG-gated dynamic cardiac display system can provide real-time feedback regarding the suspected pathology, function, and structural defects, as well as anatomical information such as chamber volume and morphology.

  18. SU-E-J-28: Gantry Speed Significantly Affects Image Quality and Imaging Dose for 4D Cone-Beam Computed Tomography On the Varian Edge Platform

    SciTech Connect

    Santoso, A; Song, K; Gardner, S; Chetty, I; Wen, N

    2015-06-15

    Purpose: 4D-CBCT facilitates assessment of tumor motion at treatment position. We investigated the effect of gantry speed on 4D-CBCT image quality and dose using the Varian Edge On-Board Imager (OBI). Methods: A thoracic protocol was designed using a 125 kVp spectrum. Image quality parameters were obtained via 4D acquisition using a Catphan phantom with a gating system. A sinusoidal waveform was executed with a five second period and superior-inferior motion. 4D-CBCT scans were sorted into 4 and 10 phases. Image quality metrics included spatial resolution, contrast-to-noise ratio (CNR), uniformity index (UI), Hounsfield unit (HU) sensitivity, and RMS error (RMSE) of motion amplitude. Dosimetry was accomplished using Gafchromic XR-QA2 films within a CIRS Thorax phantom. This was placed on the gating phantom using the same motion waveform. Results: High contrast resolution decreased linearly from 5.93 to 4.18 lp/cm, 6.54 to 4.18 lp/cm, and 5.19 to 3.91 lp/cm for averaged, 4 phase, and 10 phase 4DCBCT volumes respectively as gantry speed increased from 1.0 to 6.0 degs/sec. CNRs decreased linearly from 4.80 to 1.82 as the gantry speed increased from 1.0 to 6.0 degs/sec, respectively. No significant variations in UIs, HU sensitivities, or RMSEs were observed with variable gantry speed. Ion chamber measurements compared to film yielded small percent differences in plastic water regions (0.1–9.6%), larger percent differences in lung equivalent regions (7.5–34.8%), and significantly larger percent differences in bone equivalent regions (119.1–137.3%). Ion chamber measurements decreased from 17.29 to 2.89 cGy with increasing gantry speed from 1.0 to 6.0 degs/sec. Conclusion: Maintaining technique factors while changing gantry speed changes the number of projections used for reconstruction. Increasing the number of projections by decreasing gantry speed decreases noise, however, dose is increased. The future of 4DCBCT’s clinical utility relies on further

  19. 4D optical coherence tomography of the embryonic heart using gated imaging

    NASA Astrophysics Data System (ADS)

    Jenkins, Michael W.; Rothenberg, Florence; Roy, Debashish; Nikolski, Vladimir P.; Wilson, David L.; Efimov, Igor R.; Rollins, Andrew M.

    2005-04-01

    Computed tomography (CT), ultrasound, and magnetic resonance imaging have been used to image and diagnose diseases of the human heart. By gating the acquisition of the images to the heart cycle (gated imaging), these modalities enable one to produce 3D images of the heart without significant motion artifact and to more accurately calculate various parameters such as ejection fractions [1-3]. Unfortunately, these imaging modalities give inadequate resolution when investigating embryonic development in animal models. Defects in developmental mechanisms during embryogenesis have long been thought to result in congenital cardiac anomalies. Our understanding of normal mechanisms of heart development and how abnormalities can lead to defects has been hampered by our inability to detect anatomic and physiologic changes in these small (<2mm) organs. Optical coherence tomography (OCT) has made it possible to visualize internal structures of the living embryonic heart with high-resolution in two- and threedimensions. OCT offers higher resolution than ultrasound (30 um axial, 90 um lateral) and magnetic resonance microscopy (25 um axial, 31 um lateral) [4, 5], with greater depth penetration over confocal microscopy (200 um). Optical coherence tomography (OCT) uses back reflected light from a sample to create an image with axial resolutions ranging from 2-15 um, while penetrating 1-2 mm in depth [6]. In the past, OCT groups estimated ejection fractions using 2D images in a Xenopus laevis [7], created 3D renderings of chick embryo hearts [8], and used a gated reconstruction technique to produce 2D Doppler OCT image of an in vivo Xenopus laevis heart [9]. In this paper we present a gated imaging system that allowed us to produce a 16-frame 3D movie of a beating chick embryo heart. The heart was excised from a day two (stage 13) chicken embryo and electrically paced at 1 Hz. We acquired 2D images (B-scans) in 62.5 ms, which provides enough temporal resolution to distinguish end

  20. A rapid compression technique for 4-D functional MRI images using data rearrangement and modified binary array techniques.

    PubMed

    Uma Vetri Selvi, G; Nadarajan, R

    2015-12-01

    Compression techniques are vital for efficient storage and fast transfer of medical image data. The existing compression techniques take significant amount of time for performing encoding and decoding and hence the purpose of compression is not fully satisfied. In this paper a rapid 4-D lossy compression method constructed using data rearrangement, wavelet-based contourlet transformation and a modified binary array technique has been proposed for functional magnetic resonance imaging (fMRI) images. In the proposed method, the image slices of fMRI data are rearranged so that the redundant slices form a sequence. The image sequence is then divided into slices and transformed using wavelet-based contourlet transform (WBCT). In WBCT, the high frequency sub-band obtained from wavelet transform is further decomposed into multiple directional sub-bands by directional filter bank to obtain more directional information. The relationship between the coefficients has been changed in WBCT as it has more directions. The differences in parent–child relationships are handled by a repositioning algorithm. The repositioned coefficients are then subjected to quantization. The quantized coefficients are further compressed by modified binary array technique where the most frequently occurring value of a sequence is coded only once. The proposed method has been experimented with fMRI images the results indicated that the processing time of the proposed method is less compared to existing wavelet-based set partitioning in hierarchical trees and set partitioning embedded block coder (SPECK) compression schemes [1]. The proposed method could also yield a better compression performance compared to wavelet-based SPECK coder. The objective results showed that the proposed method could gain good compression ratio in maintaining a peak signal noise ratio value of above 70 for all the experimented sequences. The SSIM value is equal to 1 and the value of CC is greater than 0.9 for all

  1. Modeling 4D Changes in Pathological Anatomy using Domain Adaptation: Analysis of TBI Imaging using a Tumor Database.

    PubMed

    Wang, Bo; Prastawa, Marcel; Saha, Avishek; Awate, Suyash P; Irimia, Andrei; Chambers, Micah C; Vespa, Paul M; Van Horn, John D; Pascucci, Valerio; Gerig, Guido

    2013-01-01

    Analysis of 4D medical images presenting pathology (i.e., lesions) is significantly challenging due to the presence of complex changes over time. Image analysis methods for 4D images with lesions need to account for changes in brain structures due to deformation, as well as the formation and deletion of new structures (e.g., edema, bleeding) due to the physiological processes associated with damage, intervention, and recovery. We propose a novel framework that models 4D changes in pathological anatomy across time, and provides explicit mapping from a healthy template to subjects with pathology. Moreover, our framework uses transfer learning to leverage rich information from a known source domain, where we have a collection of completely segmented images, to yield effective appearance models for the input target domain. The automatic 4D segmentation method uses a novel domain adaptation technique for generative kernel density models to transfer information between different domains, resulting in a fully automatic method that requires no user interaction. We demonstrate the effectiveness of our novel approach with the analysis of 4D images of traumatic brain injury (TBI), using a synthetic tumor database as the source domain. PMID:25346953

  2. Automatic landmark generation for deformable image registration evaluation for 4D CT images of lung

    NASA Astrophysics Data System (ADS)

    Vickress, J.; Battista, J.; Barnett, R.; Morgan, J.; Yartsev, S.

    2016-10-01

    Deformable image registration (DIR) has become a common tool in medical imaging across both diagnostic and treatment specialties, but the methods used offer varying levels of accuracy. Evaluation of DIR is commonly performed using manually selected landmarks, which is subjective, tedious and time consuming. We propose a semi-automated method that saves time and provides accuracy comparable to manual selection. Three landmarking methods including manual (with two independent observers), scale invariant feature transform (SIFT), and SIFT with manual editing (SIFT-M) were tested on 10 thoracic 4DCT image studies corresponding to the 0% and 50% phases of respiration. Results of each method were evaluated against a gold standard (GS) landmark set comparing both mean and proximal landmark displacements. The proximal method compares the local deformation magnitude between a test landmark pair and the closest GS pair. Statistical analysis was done using an intra class correlation (ICC) between test and GS displacement values. The creation time per landmark pair was 22, 34, 2.3, and 4.3 s for observers 1 and 2, SIFT, and SIFT-M methods respectively. Across 20 lungs from the 10 CT studies, the ICC values between the GS and observer 1 and 2, SIFT, and SIFT-M methods were 0.85, 0.85, 0.84, and 0.82 for mean lung deformation, and 0.97, 0.98, 0.91, and 0.96 for proximal landmark deformation, respectively. SIFT and SIFT-M methods have an accuracy that is comparable to manual methods when tested against a GS landmark set while saving 90% of the time. The number and distribution of landmarks significantly affected the analysis as manifested by the different results for mean deformation and proximal landmark deformation methods. Automatic landmark methods offer a promising alternative to manual landmarking, if the quantity, quality and distribution of landmarks can be optimized for the intended application.

  3. A deformable phantom for 4D radiotherapy verification: Design and image registration evaluation

    SciTech Connect

    Serban, Monica; Heath, Emily; Stroian, Gabriela; Collins, D. Louis; Seuntjens, Jan

    2008-03-15

    peak inhale. The SI displacement of the landmarks varied between 94% and 3% of the piston excursion for positions closer and farther away from the piston, respectively. The reproducibility of the phantom deformation was within the image resolution (0.7x0.7x1.25 mm{sup 3}). Vector average registration accuracy based on point landmarks was found to be 0.5 (0.4 SD) mm. The tumor and lung mean 3D DTA obtained from triangulated surfaces were 0.4 (0.1 SD) mm and 1.0 (0.8 SD) mm, respectively. This phantom is capable of reproducibly emulating the physically realistic lung features and deformations and has a wide range of potential applications, including four-dimensional (4D) imaging, evaluation of deformable registration accuracy, 4D planning and dose delivery.

  4. Application of 4D resistivity image profiling to detect DNAPLs plume.

    NASA Astrophysics Data System (ADS)

    Liu, H.; Yang, C.; Tsai, Y.

    2008-12-01

    In July 1993, the soil and groundwater of the factory of Taiwan , Miaoli was found to be contaminated by dichloroethane, chlorobenzene and other hazardous solvents. The contaminants were termed to be dense non-aqueous phase liquids (DNAPLs). The contaminated site was neglected for the following years until May 1998, the Environment Protection Agency of Miaoli ordered the company immediately take an action for treatment of the contaminated site. Excavating and exposing the contaminated soil was done at the previous waste DNAPL dumped area. In addition, more than 53 wells were drilled around the pool with a maximum depth of 12 m where a clayey layer was found. Continuous pumping the groundwater and monitoring the concentration of residual DNAPL contained in the well water samples have done in different stages of remediation. However, it is suspected that the DNAPL has existed for a long time, therefore the contaminants might dilute but remnants of a DNAPL plume that are toxic to humans still remain in the soil and migrate to deeper aquifers. A former contaminated site was investigated using the 2D, 3D and 4D resisitivity image technique, with aims of determining buried contaminant geometry. This paper emphasizes the use of resistivity image profiling (RIP) method to map the limit of this DNAPL waste disposal site where the records of operations are not variations. A significant change in resistivity values was detected between known polluted and non-polluted subsurface; a high resistivity value implies that the subsurface was contaminated by DNAPL plume. The results of the survey serve to provide insight into the sensitivity of RIP method for detecting DNAPL plumes within the shallow subsurface, and help to provide valuable information related to monitoring the possible migration path of DNAPL plume in the past. According to the formerly studies in this site, affiliation by excavates with pumps water remediation had very long time, Therefore this research was used

  5. Evaluation of Elekta 4D cone beam CT-based automatic image registration for radiation treatment of lung cancer

    PubMed Central

    Harrison, Amy; Yu, Yan; Xiao, Ying; Werner-Wasik, Maria; Lu, Bo

    2015-01-01

    Objective: The study was aimed to evaluate the precision of Elekta four-dimensional (4D) cone beam CT (CBCT)-based automatic dual-image registrations using different landmarks for clipbox for radiation treatment of lung cancer. Methods: 30 4D CBCT scans from 15 patients were studied. 4D CBCT images were registered with reference CT images using dual-image registration: a clipbox registration and a mask registration. The image registrations performed in clinic using a physician-defined clipbox, were reviewed by physicians, and were taken as the standard. Studies were conducted to evaluate the automatic dual registrations using three kinds of landmarks for clipbox: spine, spine plus internal target volume (ITV) and lung (including as much of the lung as possible). Translational table shifts calculated from the automatic registrations were compared with those of the standard. Results: The mean of the table shift differences in the lateral direction were 0.03, 0.03 and 0.03 cm, for clipboxes based on spine, spine plus ITV and lung, respectively. The mean of the shift differences in the longitudinal direction were 0.08, 0.08 and 0.08 cm, respectively. The mean of the shift differences in the vertical direction were 0.03, 0.03 and 0.03 cm, respectively. Conclusion: The automatic registrations using three different landmarks for clipbox showed similar results. One can use any of the three landmarks in 4D CBCT dual-image registration. Advance in knowledge: The study provides knowledge and recommendations for application of Elekta 4D CBCT image registration in radiation therapy of lung cancer. PMID:26183932

  6. Maximum entropy image reconstruction from projections

    NASA Astrophysics Data System (ADS)

    Bara, N.; Murata, K.

    1981-07-01

    The maximum entropy method is applied to image reconstruction from projections, of which angular view is restricted. The relaxation parameters are introduced to the maximum entropy reconstruction and after iteration the median filtering is implemented. These procedures improve the quality of the reconstructed image from noisy projections

  7. Four-dimensional (4D) Motion Detection to Correct Respiratory Effects in Treatment Response Assessment Using Molecular Imaging Biomarkers

    PubMed Central

    Schreibmann, Eduard; Crocker, Ian; Schuster, David M.; Curran, Walter J.; Fox, Tim

    2014-01-01

    Observing early metabolic changes in positron emission tomography (PET) is an essential tool to assess treatment efficiency in radiotherapy. However, for thoracic regions, the use of three-dimensional (3D) PET imaging is unfeasible because the radiotracer activity is smeared by the respiratory motion and averaged during the imaging acquisition process. This motion-induced degradation is similar in magnitude with the treatment-induced changes, and the two occurrences become indiscernible. We present a customized temporal-spatial deformable registration method for quantifying respiratory motion in a four-dimensional (4D) PET dataset. Once the motion is quantified, a motion-corrected (MC) dataset is created by tracking voxels to eliminate breathing-induced changes in the 4D imaging scan. The 4D voxel-tracking data is then summed to yield a 3D MC-PET scan containing only treatment-induced changes. This proof of concept is exemplified on both phantom and clinical data, where the proposed algorithm tracked the trajectories of individual points through the 4D datasets reducing motion to less than 4 mm in all phases. This correction approach using deformable registration can discern motion blurring from treatment-induced changes in treatment response assessment using PET imaging. PMID:24000982

  8. Reconstruction of coded aperture images

    NASA Technical Reports Server (NTRS)

    Bielefeld, Michael J.; Yin, Lo I.

    1987-01-01

    Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

  9. Quantifying the image quality and dose reduction of respiratory triggered 4D cone-beam computed tomography with patient-measured breathing

    NASA Astrophysics Data System (ADS)

    Cooper, Benjamin J.; O'Brien, Ricky T.; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J.

    2015-12-01

    Respiratory triggered four dimensional cone-beam computed tomography (RT 4D CBCT) is a novel technique that uses a patient’s respiratory signal to drive the image acquisition with the goal of imaging dose reduction without degrading image quality. This work investigates image quality and dose using patient-measured respiratory signals for RT 4D CBCT simulations. Studies were performed that simulate a 4D CBCT image acquisition using both the novel RT 4D CBCT technique and a conventional 4D CBCT technique. A set containing 111 free breathing lung cancer patient respiratory signal files was used to create 111 pairs of RT 4D CBCT and conventional 4D CBCT image sets from realistic simulations of a 4D CBCT system using a Rando phantom and the digital phantom, XCAT. Each of these image sets were compared to a ground truth dataset from which a mean absolute pixel difference (MAPD) metric was calculated to quantify the degradation of image quality. The number of projections used in each simulation was counted and was assumed as a surrogate for imaging dose. Based on 111 breathing traces, when comparing RT 4D CBCT with conventional 4D CBCT, the average image quality was reduced by 7.6% (Rando study) and 11.1% (XCAT study). However, the average imaging dose reduction was 53% based on needing fewer projections (617 on average) than conventional 4D CBCT (1320 projections). The simulation studies have demonstrated that the RT 4D CBCT method can potentially offer a 53% saving in imaging dose on average compared to conventional 4D CBCT in simulation studies using a wide range of patient-measured breathing traces with a minimal impact on image quality.

  10. SU-E-J-183: Quantifying the Image Quality and Dose Reduction of Respiratory Triggered 4D Cone-Beam Computed Tomography with Patient- Measured Breathing

    SciTech Connect

    Cooper, B; OBrien, R; Kipritidis, J; Keall, P

    2014-06-01

    Purpose: Respiratory triggered four dimensional cone-beam computed tomography (RT 4D CBCT) is a novel technique that uses a patient's respiratory signal to drive the image acquisition with the goal of imaging dose reduction without degrading image quality. This work investigates image quality and dose using patient-measured respiratory signals for RT 4D CBCT simulations instead of synthetic sinusoidal signals used in previous work. Methods: Studies were performed that simulate a 4D CBCT image acquisition using both the novel RT 4D CBCT technique and a conventional 4D CBCT technique from a database of oversampled Rando phantom CBCT projections. A database containing 111 free breathing lung cancer patient respiratory signal files was used to create 111 RT 4D CBCT and 111 conventional 4D CBCT image datasets from realistic simulations of a 4D RT CBCT system. Each of these image datasets were compared to a ground truth dataset from which a root mean square error (RMSE) metric was calculated to quantify the degradation of image quality. The number of projections used in each simulation is counted and was assumed as a surrogate for imaging dose. Results: Based on 111 breathing traces, when comparing RT 4D CBCT with conventional 4D CBCT the average image quality was reduced by 7.6%. However, the average imaging dose reduction was 53% based on needing fewer projections (617 on average) than conventional 4D CBCT (1320 projections). Conclusion: The simulation studies using a wide range of patient breathing traces have demonstrated that the RT 4D CBCT method can potentially offer a substantial saving of imaging dose of 53% on average compared to conventional 4D CBCT in simulation studies with a minimal impact on image quality. A patent application (PCT/US2012/048693) has been filed which is related to this work.

  11. 4D cone-beam CT imaging for guidance in radiation therapy: setup verification by use of implanted fiducial markers

    NASA Astrophysics Data System (ADS)

    Jin, Peng; van Wieringen, Niek; Hulshof, Maarten C. C. M.; Bel, Arjan; Alderliesten, Tanja

    2016-03-01

    The use of 4D cone-beam computed tomography (CBCT) and fiducial markers for guidance during radiation therapy of mobile tumors is challenging due to the trade-off between image quality, imaging dose, and scanning time. We aimed to investigate the visibility of markers and the feasibility of marker-based 4D registration and manual respiration-induced marker motion quantification for different CBCT acquisition settings. A dynamic thorax phantom and a patient with implanted gold markers were included. For both the phantom and patient, the peak-to-peak amplitude of marker motion in the cranial-caudal direction ranged from 5.3 to 14.0 mm, which did not affect the marker visibility and the associated marker-based registration feasibility. While using a medium field of view (FOV) and the same total imaging dose as is applied for 3D CBCT scanning in our clinic, it was feasible to attain an improved marker visibility by reducing the imaging dose per projection and increasing the number of projection images. For a small FOV with a shorter rotation arc but similar total imaging dose, streak artifacts were reduced due to using a smaller sampling angle. Additionally, the use of a small FOV allowed reducing total imaging dose and scanning time (~2.5 min) without losing the marker visibility. In conclusion, by using 4D CBCT with identical or lower imaging dose and a reduced gantry speed, it is feasible to attain sufficient marker visibility for marker-based 4D setup verification. Moreover, regardless of the settings, manual marker motion quantification can achieve a high accuracy with the error <1.2 mm.

  12. Analysis and dynamic 3D visualization of cerebral blood flow combining 3D and 4D MR image sequences

    NASA Astrophysics Data System (ADS)

    Forkert, Nils Daniel; Säring, Dennis; Fiehler, Jens; Illies, Till; Möller, Dietmar; Handels, Heinz

    2009-02-01

    In this paper we present a method for the dynamic visualization of cerebral blood flow. Spatio-temporal 4D magnetic resonance angiography (MRA) image datasets and 3D MRA datasets with high spatial resolution were acquired for the analysis of arteriovenous malformations (AVMs). One of the main tasks is the combination of the information of the 3D and 4D MRA image sequences. Initially, in the 3D MRA dataset the vessel system is segmented and a 3D surface model is generated. Then, temporal intensity curves are analyzed voxelwise in the 4D MRA image sequences. A curve fitting of the temporal intensity curves to a patient individual reference curve is used to extract the bolus arrival times in the 4D MRA sequences. After non-linear registration of both MRA datasets the extracted hemodynamic information is transferred to the surface model where the time points of inflow can be visualized color coded dynamically over time. The dynamic visualizations computed using the curve fitting method for the estimation of the bolus arrival times were rated superior compared to those computed using conventional approaches for bolus arrival time estimation. In summary the procedure suggested allows a dynamic visualization of the individual hemodynamic situation and better understanding during the visual evaluation of cerebral vascular diseases.

  13. TH-E-BRF-02: 4D-CT Ventilation Image-Based IMRT Plans Are Dosimetrically Comparable to SPECT Ventilation Image-Based Plans

    SciTech Connect

    Kida, S; Bal, M; Kabus, S; Loo, B; Keall, P; Yamamoto, T

    2014-06-15

    Purpose: An emerging lung ventilation imaging method based on 4D-CT can be used in radiotherapy to selectively avoid irradiating highly-functional lung regions, which may reduce pulmonary toxicity. Efforts to validate 4DCT ventilation imaging have been focused on comparison with other imaging modalities including SPECT and xenon CT. The purpose of this study was to compare 4D-CT ventilation image-based functional IMRT plans with SPECT ventilation image-based plans as reference. Methods: 4D-CT and SPECT ventilation scans were acquired for five thoracic cancer patients in an IRB-approved prospective clinical trial. The ventilation images were created by quantitative analysis of regional volume changes (a surrogate for ventilation) using deformable image registration of the 4D-CT images. A pair of 4D-CT ventilation and SPECT ventilation image-based IMRT plans was created for each patient. Regional ventilation information was incorporated into lung dose-volume objectives for IMRT optimization by assigning different weights on a voxel-by-voxel basis. The objectives and constraints of the other structures in the plan were kept identical. The differences in the dose-volume metrics have been evaluated and tested by a paired t-test. SPECT ventilation was used to calculate the lung functional dose-volume metrics (i.e., mean dose, V20 and effective dose) for both 4D-CT ventilation image-based and SPECT ventilation image-based plans. Results: Overall there were no statistically significant differences in any dose-volume metrics between the 4D-CT and SPECT ventilation imagebased plans. For example, the average functional mean lung dose of the 4D-CT plans was 26.1±9.15 (Gy), which was comparable to 25.2±8.60 (Gy) of the SPECT plans (p = 0.89). For other critical organs and PTV, nonsignificant differences were found as well. Conclusion: This study has demonstrated that 4D-CT ventilation image-based functional IMRT plans are dosimetrically comparable to SPECT ventilation image

  14. Method for position emission mammography image reconstruction

    DOEpatents

    Smith, Mark Frederick

    2004-10-12

    An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.

  15. Attempt of UAV oblique images and MLS point clouds for 4D modelling of roadside pole-like objects

    NASA Astrophysics Data System (ADS)

    Lin, Yi; West, Geoff

    2014-11-01

    The state-of-the-art remote sensing technologies, namely Unmanned Aerial Vehicle (UAV) based oblique imaging and Mobile Laser Scanning (MLS) show great potential for spatial information acquisition. This study investigated the combination of the two data sources for 4D modelling of roadside pole-like objects. The data for the analysis were collected by the Microdrone md4-200 UAV imaging system and the Sensei MLS system developed by the Finnish Geodetic Institute. Pole extraction, 3D structural parameter derivation and texture segmentation were deployed on the oblique images and point clouds, and their results were fused to yield the 4D models for one example of pole-like objects, namely lighting poles. The combination techniques proved promising.

  16. Evaluation of the reliability of the maximum entropy method for reconstructing 3D and 4D NOESY-type NMR spectra of proteins.

    PubMed

    Shigemitsu, Yoshiki; Ikeya, Teppei; Yamamoto, Akihiro; Tsuchie, Yuusuke; Mishima, Masaki; Smith, Brian O; Güntert, Peter; Ito, Yutaka

    2015-02-01

    Despite their advantages in analysis, 4D NMR experiments are still infrequently used as a routine tool in protein NMR projects due to the long duration of the measurement and limited digital resolution. Recently, new acquisition techniques for speeding up multidimensional NMR experiments, such as nonlinear sampling, in combination with non-Fourier transform data processing methods have been proposed to be beneficial for 4D NMR experiments. Maximum entropy (MaxEnt) methods have been utilised for reconstructing nonlinearly sampled multi-dimensional NMR data. However, the artefacts arising from MaxEnt processing, particularly, in NOESY spectra have not yet been clearly assessed in comparison with other methods, such as quantitative maximum entropy, multidimensional decomposition, and compressed sensing. We compared MaxEnt with other methods in reconstructing 3D NOESY data acquired with variously reduced sparse sampling schedules and found that MaxEnt is robust, quick and competitive with other methods. Next, nonlinear sampling and MaxEnt processing were applied to 4D NOESY experiments, and the effect of the artefacts of MaxEnt was evaluated by calculating 3D structures from the NOE-derived distance restraints. Our results demonstrated that sufficiently converged and accurate structures (RMSD of 0.91Å to the mean and 1.36Å to the reference structures) were obtained even with NOESY spectra reconstructed from 1.6% randomly selected sampling points for indirect dimensions. This suggests that 3D MaxEnt processing in combination with nonlinear sampling schedules is still a useful and advantageous option for rapid acquisition of high-resolution 4D NOESY spectra of proteins.

  17. Reconstructing HST Images of Asteroids

    NASA Astrophysics Data System (ADS)

    Storrs, A. D.; Bank, S.; Gerhardt, H.; Makhoul, K.

    2003-12-01

    We present reconstructions of images of 22 large main belt asteroids that were observed by Hubble Space Telescope with the Wide-Field/Planetary cameras. All images were restored with the MISTRAL program (Mugnier, Fusco, and Conan 2003) at enhanced spatial resolution. This is possible thanks to the well-studied and stable point spread function (PSF) on HST. We present some modeling of this process and determine that the Strehl ratio for WF/PC (aberrated) images can be improved to 130 ratio of 80 We will report sizes, shapes, and albedos for these objects, as well as any surface features. Images taken with the WFPC-2 instrument were made in a variety of filters so that it should be possible to investigate changes in mineralogy across the surface of the larger asteroids in a manner similar to that done on 4 Vesta by Binzel et al. (1997). Of particular interest are a possible water of hydration feature on 1 Ceres, and the non-observation of a constriction or gap between the components of 216 Kleopatra. Reduction of this data was aided by grant HST-GO-08583.08A from the Space Telescope Science Institute. References: Mugnier, L.M., T. Fusco, and J.-M. Conan, 2003. JOSA A (submitted) Binzel, R.P., Gaffey, M.J., Thomas, P.C., Zellner, B.H., Storrs, A.D., and Wells, E.N. 1997. Icarus 128 pp. 95-103

  18. A proposed framework for consensus-based lung tumour volume auto-segmentation in 4D computed tomography imaging

    NASA Astrophysics Data System (ADS)

    Martin, Spencer; Brophy, Mark; Palma, David; Louie, Alexander V.; Yu, Edward; Yaremko, Brian; Ahmad, Belal; Barron, John L.; Beauchemin, Steven S.; Rodrigues, George; Gaede, Stewart

    2015-02-01

    This work aims to propose and validate a framework for tumour volume auto-segmentation based on ground-truth estimates derived from multi-physician input contours to expedite 4D-CT based lung tumour volume delineation. 4D-CT datasets of ten non-small cell lung cancer (NSCLC) patients were manually segmented by 6 physicians. Multi-expert ground truth (GT) estimates were constructed using the STAPLE algorithm for the gross tumour volume (GTV) on all respiratory phases. Next, using a deformable model-based method, multi-expert GT on each individual phase of the 4D-CT dataset was propagated to all other phases providing auto-segmented GTVs and motion encompassing internal gross target volumes (IGTVs) based on GT estimates (STAPLE) from each respiratory phase of the 4D-CT dataset. Accuracy assessment of auto-segmentation employed graph cuts for 3D-shape reconstruction and point-set registration-based analysis yielding volumetric and distance-based measures. STAPLE-based auto-segmented GTV accuracy ranged from (81.51  ±  1.92) to (97.27  ±  0.28)% volumetric overlap of the estimated ground truth. IGTV auto-segmentation showed significantly improved accuracies with reduced variance for all patients ranging from 90.87 to 98.57% volumetric overlap of the ground truth volume. Additional metrics supported these observations with statistical significance. Accuracy of auto-segmentation was shown to be largely independent of selection of the initial propagation phase. IGTV construction based on auto-segmented GTVs within the 4D-CT dataset provided accurate and reliable target volumes compared to manual segmentation-based GT estimates. While inter-/intra-observer effects were largely mitigated, the proposed segmentation workflow is more complex than that of current clinical practice and requires further development.

  19. EarthScope imaging of 4D stress evolution of the San Andreas Fault System

    NASA Astrophysics Data System (ADS)

    Smith-Konter, B. R.; Del Pardo, C.

    2011-12-01

    EarthScope seismic and geodetic observations, combined with sophisticated computational models and powerful visualization tools, are now providing a critical ensemble of information about interseismic stressing rates along the San Andreas Fault System (SAFS). When combined with paleoseismic chronologies of earthquake ruptures spanning the last several hundreds of years, four-dimensional (4D) simulations of stress evolution spanning multiple earthquake cycles are now possible. To investigate stress variations at depth along the SAFS over multiple earthquake cycles, we use a 4D semi-analytic model that simulates interseismic strain accumulation, coseismic displacement, and post-seismic viscoelastic relaxation of the mantle. The model utilizes geologic estimates of fault locations and slip rates, as well as paleoseismic earthquake rupture histories, and is computed at a 500 m grid resolution to better resolve the sharp deformation gradients at creeping faults. Using EarthScope PBO and ALOS InSAR data, we tune the model locking depths and slip rates to compute the 4D stress accumulation within the seismogenic crust. 4D models show that stress accumulation and stress drop are a complex function of space and time. We use ParaView 3.10, an open-source multi-platform visualization package, for manipulation and visualization of 4D stress variations of fault segments at depth. We use ParaView to create a 3D meshed volume spanning a ~1000 x 1500 x 50 km region of the SAFS and present both volume and sliced views of stress from several viewpoints along the plate boundary. These models reveal pockets of stress concentrated at depth due to the interaction of neighboring fault segments and at fault segment branching junctions. We present several sensitivity tests that reveal the variation of stress at depth as a function of locking depth, slip rate, coefficient of friction, elastic plate thickness, and viscosity. These visualizations lay the groundwork for 4D time

  20. Image reconstruction via truncated lambda tomography

    NASA Astrophysics Data System (ADS)

    Yu, Hengyong; Ye, Yangbo; Wang, Ge

    2006-08-01

    This paper investigates the feasibility of reconstructing a Computed Tomography (CT) image from truncated Lambda Tomography (LT), a gradient-like image of it's original. An LT image can be regarded as a convolution of the object image and the point spread function (PSF) of the Calderon operator. The PSF's infinite support provides the LT image infinite support; even the original CT image is of compact support. When the support of a truncated LT image fully covers the compact support of the corresponding CT image, we develop an extrapolation method to recover the CT image more precisely. When the support of the CT image fully covers the support of the truncated LT image, we design a template-based scheme to compensate the cupping effects and reconstruct a satisfactory image. Our algorithms are evaluated in numerical simulations and the results demonstrate the feasibilities of our methods. Our approaches provide a new way to reconstruct high-quality CT images.

  1. Heuristic reconstructions of neutron penumbral images

    SciTech Connect

    Nozaki, Shinya; Chen Yenwei

    2004-10-01

    Penumbral imaging is a technique of coded aperture imaging proposed for imaging of highly penetrating radiations. To date, the penumbral imaging technique has been successfully applied to neutron imaging in laser fusion experiments. Since the reconstruction of penumbral images is based on linear deconvolution methods, such as inverse filter and Wiener filer, the point spread function of apertures should be space invariant; it is also sensitive to the noise contained in penumbral images. In this article, we propose a new heuristic reconstruction method for neutron penumbral imaging, which can be used for a space-variant imaging system and is also very tolerant to the noise.

  2. Structured image reconstruction for three-dimensional ghost imaging lidar.

    PubMed

    Yu, Hong; Li, Enrong; Gong, Wenlin; Han, Shensheng

    2015-06-01

    A structured image reconstruction method has been proposed to obtain high quality images in three-dimensional ghost imaging lidar. By considering the spatial structure relationship between recovered images of scene slices at different longitudinal distances, orthogonality constraint has been incorporated to reconstruct the three-dimensional scenes in remote sensing. Numerical simulations have been performed to demonstrate that scene slices with various sparse ratios can be recovered more accurately by applying orthogonality constraint, and the enhancement is significant especially for ghost imaging with less measurements. A simulated three-dimensional city scene has been successfully reconstructed by using structured image reconstruction in three-dimensional ghost imaging lidar. PMID:26072814

  3. Real-time dynamic display of registered 4D cardiac MR and ultrasound images using a GPU

    NASA Astrophysics Data System (ADS)

    Zhang, Q.; Huang, X.; Eagleson, R.; Guiraudon, G.; Peters, T. M.

    2007-03-01

    In minimally invasive image-guided surgical interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and real-time three-dimensional (3D) ultrasound (US), can provide complementary, multi-spectral image information. Multimodality dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac procedures, it would be valuable to register dynamic MRI or CT with intraoperative US. However, in practice, either the high computational cost prohibits such real-time visualization of volumetric multimodal images in a real-world medical environment, or else the resulting image quality is not satisfactory for accurate guidance during the intervention. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to begin to address this problem. In this work, we first outline our research on dynamic 3D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Then we describe image processing and optimization techniques for 4D (3D + time) cardiac image real-time rendering. We also present our multimodality 4D medical image visualization engine, which directly runs on a GPU in real-time by exploiting the advantages of the graphics hardware. In addition, techniques such as multiple transfer functions for different imaging modalities, dynamic texture binding, advanced texture sampling and multimodality image compositing are employed to facilitate the real-time display and manipulation of the registered dual-modality dynamic 3D MR and US cardiac datasets.

  4. High-resolution reconstruction for terahertz imaging.

    PubMed

    Xu, Li-Min; Fan, Wen-Hui; Liu, Jia

    2014-11-20

    We present a high-resolution (HR) reconstruction model and algorithms for terahertz imaging, taking advantage of super-resolution methodology and algorithms. The algorithms used include projection onto a convex sets approach, iterative backprojection approach, Lucy-Richardson iteration, and 2D wavelet decomposition reconstruction. Using the first two HR reconstruction methods, we successfully obtain HR terahertz images with improved definition and lower noise from four low-resolution (LR) 22×24 terahertz images taken from our homemade THz-TDS system at the same experimental conditions with 1.0 mm pixel. Using the last two HR reconstruction methods, we transform one relatively LR terahertz image to a HR terahertz image with decreased noise. This indicates potential application of HR reconstruction methods in terahertz imaging with pulsed and continuous wave terahertz sources.

  5. Studies on image compression and image reconstruction

    NASA Technical Reports Server (NTRS)

    Sayood, Khalid; Nori, Sekhar; Araj, A.

    1994-01-01

    During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

  6. 4-D Photoacoustic Tomography

    NASA Astrophysics Data System (ADS)

    Xiang, Liangzhong; Wang, Bo; Ji, Lijun; Jiang, Huabei

    2013-01-01

    Photoacoustic tomography (PAT) offers three-dimensional (3D) structural and functional imaging of living biological tissue with label-free, optical absorption contrast. These attributes lend PAT imaging to a wide variety of applications in clinical medicine and preclinical research. Despite advances in live animal imaging with PAT, there is still a need for 3D imaging at centimeter depths in real-time. We report the development of four dimensional (4D) PAT, which integrates time resolutions with 3D spatial resolution, obtained using spherical arrays of ultrasonic detectors. The 4D PAT technique generates motion pictures of imaged tissue, enabling real time tracking of dynamic physiological and pathological processes at hundred micrometer-millisecond resolutions. The 4D PAT technique is used here to image needle-based drug delivery and pharmacokinetics. We also use this technique to monitor 1) fast hemodynamic changes during inter-ictal epileptic seizures and 2) temperature variations during tumor thermal therapy.

  7. Optimal reconstruction of images from localized phase.

    PubMed

    Urieli, S; Porat, M; Cohen, N

    1998-01-01

    The importance of localized phase in signal representation is investigated. The convergence rate of the POCS algorithm (projection onto convex sets) used for image reconstruction from spectral phase is defined and analyzed, and the characteristics of images optimally reconstructed from phase-only information are presented. It is concluded that images of geometric form are most efficiently reconstructed from their spectral phase, whereas images of symmetric form have the poorest convergence characteristics. The transition between the two extremes is shown to be continuous. The results provide a new approach and analysis of the previously reported advantages of the localized phase representation over the global approach, and suggest possible compression schemes.

  8. Assessment of Left Ventricular Function in Cardiac MSCT Imaging by a 4D Hierarchical Surface-Volume Matching Process

    PubMed Central

    Simon, Antoine; Boulmier, Dominique; Coatrieux, Jean-Louis; Le Breton, Hervé

    2006-01-01

    Multislice computed tomography (MSCT) scanners offer new perspectives for cardiac kinetics evaluation with 4D dynamic sequences of high contrast and spatiotemporal resolutions. A new method is proposed for cardiac motion extraction in multislice CT. Based on a 4D hierarchical surface-volume matching process, it provides the detection of the heart left cavities along the acquired sequence and the estimation of their 3D surface velocity fields. A Markov random field model is defined to find, according to topological descriptors, the best correspondences between a 3D mesh describing the left endocardium at one time and the 3D acquired volume at the following time. The global optimization of the correspondences is realized with a multiresolution process. Results obtained on simulated and real data show the capabilities to extract clinically relevant global and local motion parameters and highlight new perspectives in cardiac computed tomography imaging. PMID:23165027

  9. Digital in-line holography: 4-D imaging and tracking of micro-structures and organisms in microfluidics and biology

    NASA Astrophysics Data System (ADS)

    Garcia-Sucerquia, J.; Xu, W.; Jericho, S. K.; Jericho, M. H.; Tamblyn, I.; Kreuzer, H. J.

    2006-01-01

    In recent years, in-line holography as originally proposed by Gabor, supplemented with numerical reconstruction, has been perfected to the point at which wavelength resolution both laterally and in depth is routinely achieved with light by using digital in-line holographic microscopy (DIHM). The advantages of DIHM are: (1) simplicity of the hardware (laser- pinhole-CCD camera), (2) magnification is obtained in the numerical reconstruction, (3) maximum information of the 3-D structure with a depth of field of millimeters, (4) changes in the specimen and the simultaneous motion of many species, can be followed in 4-D at the camera frame rate. We present results obtained with DIHM in biological and microfluidic applications. By taking advantage of the large depth of field and the plane-to-plane reconstruction capability of DIHM, we can produce 3D representations of the paths followed by micron-sized objects such as suspensions of microspheres and biological samples (cells, algae, protozoa, bacteria). Examples from biology include a study of the motion of bacteria in a diatom and the track of algae and paramecium. In microfluidic applications we observe micro-channel flow, motion of bubbles in water and evolution in electrolysis. The paper finishes with new results from an underwater version of DIHM.

  10. 3D-Reconstructions and Virtual 4D-Visualization to Study Metamorphic Brain Development in the Sphinx Moth Manduca Sexta.

    PubMed

    Huetteroth, Wolf; El Jundi, Basil; El Jundi, Sirri; Schachtner, Joachim

    2010-01-01

    DURING METAMORPHOSIS, THE TRANSITION FROM THE LARVA TO THE ADULT, THE INSECT BRAIN UNDERGOES CONSIDERABLE REMODELING: new neurons are integrated while larval neurons are remodeled or eliminated. One well acknowledged model to study metamorphic brain development is the sphinx moth Manduca sexta. To further understand mechanisms involved in the metamorphic transition of the brain we generated a 3D standard brain based on selected brain areas of adult females and 3D reconstructed the same areas during defined stages of pupal development. Selected brain areas include for example mushroom bodies, central complex, antennal- and optic lobes. With this approach we eventually want to quantify developmental changes in neuropilar architecture, but also quantify changes in the neuronal complement and monitor the development of selected neuronal populations. Furthermore, we used a modeling software (Cinema 4D) to create a virtual 4D brain, morphing through its developmental stages. Thus the didactical advantages of 3D visualization are expanded to better comprehend complex processes of neuropil formation and remodeling during development. To obtain datasets of the M. sexta brain areas, we stained whole brains with an antiserum against the synaptic vesicle protein synapsin. Such labeled brains were then scanned with a confocal laser scanning microscope and selected neuropils were reconstructed with the 3D software AMIRA 4.1.

  11. WE-G-BRF-09: Force- and Image-Adaptive Strategies for Robotised Placement of 4D Ultrasound Probes

    SciTech Connect

    Kuhlemann, I; Bruder, R; Ernst, F; Schweikard, A

    2014-06-15

    Purpose: To allow continuous acquisition of high quality 4D ultrasound images for non-invasive live tracking of tumours for IGRT, image- and force-adaptive strategies for robotised placement of 4D ultrasound probes are developed and evaluated. Methods: The developed robotised ultrasound system is based on a 6-axes industrial robot (adept Viper s850) carrying a 4D ultrasound transducer with a mounted force-torque sensor. The force-adaptive placement strategies include probe position control using artificial potential fields and contact pressure regulation by a PD controller strategy. The basis for live target tracking is a continuous minimum contact pressure to ensure good image quality and high patient comfort. This contact pressure can be significantly disturbed by respiratory movements and has to be compensated. All measurements were performed on human subjects under realistic conditions. When performing cardiac ultrasound, rib- and lung shadows are a common source of interference and can disrupt the tracking. To ensure continuous tracking, these artefacts had to be detected to automatically realign the probe. The detection is realised by multiple algorithms based on entropy calculations as well as a determination of the image quality. Results: Through active contact pressure regulation it was possible to reduce the variance of the contact pressure by 89.79% despite respiratory motion of the chest. The results regarding the image processing clearly demonstrate the feasibility to detect image artefacts like rib shadows in real-time. Conclusion: In all cases, it was possible to stabilise the image quality by active contact pressure control and automatically detected image artefacts. This fact enables the possibility to compensate for such interferences by realigning the probe and thus continuously optimising the ultrasound images. This is a huge step towards fully automated transducer positioning and opens the possibility for stable target tracking in

  12. Image Reconstruction Using Analysis Model Prior.

    PubMed

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  13. Image Reconstruction Using Analysis Model Prior

    PubMed Central

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  14. 4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging.

    PubMed

    Reilhac, Anthonin; Charil, Arnaud; Wimberley, Catriona; Angelis, Georgios; Hamze, Hasar; Callaghan, Paul; Garcia, Marie-Paule; Boisson, Frederic; Ryder, Will; Meikle, Steven R; Gregoire, Marie-Claude

    2015-09-01

    Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity. PMID:26080302

  15. Spectral image reconstruction through the PCA transform

    NASA Astrophysics Data System (ADS)

    Ma, Long; Qiu, Xuewei; Cong, Yangming

    2015-12-01

    Digital color image reproduction based on spectral information has become a field of much interest and practical importance in recent years. The representation of color in digital form with multi-band images is not very accurate, hence the use of spectral image is justified. Reconstructing high-dimensional spectral reflectance images from relatively low-dimensional camera signals is generally an ill-posed problem. The aim of this study is to use the Principal component analysis (PCA) transform in spectral reflectance images reconstruction. The performance is evaluated by the mean, median and standard deviation of color difference values. The values of mean, median and standard deviation of root mean square (GFC) errors between the reconstructed and the actual spectral image were also calculated. Simulation experiments conducted on a six-channel camera system and on spectral test images show the performance of the suggested method.

  16. A novel non-registration based segmentation approach of 4D dynamic upper airway MR images: minimally interactive fuzzy connectedness

    NASA Astrophysics Data System (ADS)

    Tong, Yubing; Udupa, Jayaram K.; Odhner, Dewey; Sin, Sanghun; Wagshul, Mark E.; Arens, Raanan

    2014-03-01

    There are several disease conditions that lead to upper airway restrictive disorders. In the study of these conditions, it is important to take into account the dynamic nature of the upper airway. Currently, dynamic MRI is the modality of choice for studying these diseases. Unfortunately, the contrast resolution obtainable in the images poses many challenges for an effective segmentation of the upper airway structures. No viable methods have been developed to date to solve this problem. In this paper, we demonstrate the adaptation of the iterative relative fuzzy connectedness (IRFC) algorithm for this application as a potential practical tool. After preprocessing to correct for background image non-uniformities and the non-standardness of MRI intensities, seeds are specified for the airway and its crucial background tissue components in only the 3D image corresponding to the first time instance of the 4D volume. Subsequently the process runs without human interaction and completes segmenting the whole 4D volume in 10 sec. Our evaluations indicate that the segmentations are of very good quality achieving true positive and false positive volume fractions and boundary distance with respect to reference manual segmentations of about 93%, 0.1%, and 0.5 mm, respectively.

  17. Dynamic Multiscale Boundary Conditions for 4D CT Images of Healthy and Emphysematous Rat

    SciTech Connect

    Jacob, Rick E.; Carson, James P.; Thomas, Mathew; Einstein, Daniel R.

    2013-06-14

    Changes in the shape of the lung during breathing determine the movement of airways and alveoli, and thus impact airflow dynamics. Modeling airflow dynamics in health and disease is a key goal for predictive multiscale models of respiration. Past efforts to model changes in lung shape during breathing have measured shape at multiple breath-holds. However, breath-holds do not capture hysteretic differences between inspiration and expiration resulting from the additional energy required for inspiration. Alternatively, imaging dynamically – without breath-holds – allows measurement of hysteretic differences. In this study, we acquire multiple micro-CT images per breath (4DCT) in live rats, and from these images we develop, for the first time, dynamic volume maps. These maps show changes in local volume across the entire lung throughout the breathing cycle and accurately predict the global pressure-volume (PV) hysteresis.

  18. Image reconstruction for robot assisted ultrasound tomography

    NASA Astrophysics Data System (ADS)

    Aalamifar, Fereshteh; Zhang, Haichong K.; Rahmim, Arman; Boctor, Emad M.

    2016-04-01

    An investigation of several image reconstruction methods for robot-assisted ultrasound (US) tomography setup is presented. In the robot-assisted setup, an expert moves the US probe to the location of interest, and a robotic arm automatically aligns another US probe with it. The two aligned probes can then transmit and receive US signals which are subsequently used for tomographic reconstruction. This study focuses on reconstruction of the speed of sound. In various simulation evaluations as well as in an experiment with a millimeter-range inaccuracy, we demonstrate that the limited data provided by two probes can be used to reconstruct pixel-wise images differentiating between media with different speeds of sound. Combining the results of this investigation with the developed robot-assisted US tomography setup, we envision feasibility of this setup for tomographic imaging in applications beyond breast imaging, with potentially significant efficacy in cancer diagnosis.

  19. Light field display and 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Iwane, Toru

    2016-06-01

    Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.

  20. Image Reconstruction for Prostate Specific Nuclear Medicine imagers

    SciTech Connect

    Mark Smith

    2007-01-11

    There is increasing interest in the design and construction of nuclear medicine detectors for dedicated prostate imaging. These include detectors designed for imaging the biodistribution of radiopharmaceuticals labeled with single gamma as well as positron-emitting radionuclides. New detectors and acquisition geometries present challenges and opportunities for image reconstruction. In this contribution various strategies for image reconstruction for these special purpose imagers are reviewed. Iterative statistical algorithms provide a framework for reconstructing prostate images from a wide variety of detectors and acquisition geometries for PET and SPECT. The key to their success is modeling the physics of photon transport and data acquisition and the Poisson statistics of nuclear decay. Analytic image reconstruction methods can be fast and are useful for favorable acquisition geometries. Future perspectives on algorithm development and data analysis for prostate imaging are presented.

  1. 4-D flow magnetic resonance imaging: blood flow quantification compared to 2-D phase-contrast magnetic resonance imaging and Doppler echocardiography

    PubMed Central

    Gabbour, Maya; Schnell, Susanne; Jarvis, Kelly; Robinson, Joshua D.; Markl, Michael

    2015-01-01

    Background Doppler echocardiography (echo) is the reference standard for blood flow velocity analysis, and two-dimensional (2-D) phase-contrast magnetic resonance imaging (MRI) is considered the reference standard for quantitative blood flow assessment. However, both clinical standard-of-care techniques are limited by 2-D acquisitions and single-direction velocity encoding and may make them inadequate to assess the complex three-dimensional hemodynamics seen in congenital heart disease. Four-dimensional flow MRI (4-D flow) enables qualitative and quantitative analysis of complex blood flow in the heart and great arteries. Objectives The objectives of this study are to compare 4-D flow with 2-D phase-contrast MRI for quantification of aortic and pulmonary flow and to evaluate the advantage of 4-D flow-based volumetric flow analysis compared to 2-D phase-contrast MRI and echo for peak velocity assessment in children and young adults. Materials and methods Two-dimensional phase-contrast MRI of the aortic root, main pulmonary artery (MPA), and right and left pulmonary arteries (RPA, LPA) and 4-D flow with volumetric coverage of the aorta and pulmonary arteries were performed in 50 patients (mean age: 13.1±6.4 years). Four-dimensional flow analyses included calculation of net flow and regurgitant fraction with 4-D flow analysis planes similarly positioned to 2-D planes. In addition, 4-D flow volumetric assessment of aortic root/ascending aorta and MPA peak velocities was performed and compared to 2-D phase-contrast MRI and echo. Results Excellent correlation and agreement were found between 2-D phase-contrast MRI and 4-D flow for net flow (r=0.97, P<0.001) and excellent correlation with good agreement was found for regurgitant fraction (r= 0.88, P<0.001) in all vessels. Two-dimensional phase-contrast MRI significantly underestimated aortic (P= 0.032) and MPA (P<0.001) peak velocities compared to echo, while volumetric 4-D flow analysis resulted in higher (aortic: P=0

  2. Bayesian image reconstruction: Application to emission tomography

    SciTech Connect

    Nunez, J.; Llacer, J.

    1989-02-01

    In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.

  3. Bayesian image reconstruction - The pixon and optimal image modeling

    NASA Technical Reports Server (NTRS)

    Pina, R. K.; Puetter, R. C.

    1993-01-01

    In this paper we describe the optimal image model, maximum residual likelihood method (OptMRL) for image reconstruction. OptMRL is a Bayesian image reconstruction technique for removing point-spread function blurring. OptMRL uses both a goodness-of-fit criterion (GOF) and an 'image prior', i.e., a function which quantifies the a priori probability of the image. Unlike standard maximum entropy methods, which typically reconstruct the image on the data pixel grid, OptMRL varies the image model in order to find the optimal functional basis with which to represent the image. We show how an optimal basis for image representation can be selected and in doing so, develop the concept of the 'pixon' which is a generalized image cell from which this basis is constructed. By allowing both the image and the image representation to be variable, the OptMRL method greatly increases the volume of solution space over which the image is optimized. Hence the likelihood of the final reconstructed image is greatly increased. For the goodness-of-fit criterion, OptMRL uses the maximum residual likelihood probability distribution introduced previously by Pina and Puetter (1992). This GOF probability distribution, which is based on the spatial autocorrelation of the residuals, has the advantage that it ensures spatially uncorrelated image reconstruction residuals.

  4. A 3D- and 4D-ESR imaging system for small animals.

    PubMed

    Oikawa, K; Ogata, T; Togashi, H; Yokoyama, H; Ohya-Nishiguchi, H; Kamada, H

    1996-01-01

    A new version of in vivo ESR-CT system composed of custom-made 0.7 GHz ESR spectrometer, air-core magnet with a field-scanning coil, three field-gradient coils, and two computers enables up- and down-field, and rapid magnetic-field scanning linearly controlled by computer. 3D-pictures of distribution of nitroxide radicals injected in brains and livers of rats and mice were obtained in 1.5 min with resolution of 1 mm. We have also succeeded in obtaining spatial-time imagings of the animals.

  5. Weighted iterative reconstruction for magnetic particle imaging

    NASA Astrophysics Data System (ADS)

    Knopp, T.; Rahmer, J.; Sattel, T. F.; Biederer, S.; Weizenecker, J.; Gleich, B.; Borgert, J.; Buzug, T. M.

    2010-03-01

    Magnetic particle imaging (MPI) is a new imaging technique capable of imaging the distribution of superparamagnetic particles at high spatial and temporal resolution. For the reconstruction of the particle distribution, a system of linear equations has to be solved. The mathematical solution to this linear system can be obtained using a least-squares approach. In this paper, it is shown that the quality of the least-squares solution can be improved by incorporating a weighting matrix using the reciprocal of the matrix-row energy as weights. A further benefit of this weighting is that iterative algorithms, such as the conjugate gradient method, converge rapidly yielding the same image quality as obtained by singular value decomposition in only a few iterations. Thus, the weighting strategy in combination with the conjugate gradient method improves the image quality and substantially shortens the reconstruction time. The performance of weighting strategy and reconstruction algorithms is assessed with experimental data of a 2D MPI scanner.

  6. Evolutionary approach to image reconstruction from projections

    NASA Astrophysics Data System (ADS)

    Nakao, Zensho; Ali, Fathelalem F.; Takashibu, Midori; Chen, Yen-Wei

    1997-10-01

    We present an evolutionary approach for reconstructing CT images; the algorithm reconstructs two-dimensional unknown images from four one-dimensional projections. A genetic algorithm works on a randomly generated population of strings each of which contains encodings of an image. The traditional, as well as new, genetic operators are applied on each generation. The mean square error between the projection data of the image encoded into a string and original projection data is used to estimate the string fitness. A Laplacian constraint term is included in the fitness function of the genetic algorithm for handling smooth images. Two new modified versions of the original genetic algorithm are presented. Results obtained by the original algorithm and the modified versions are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the evolutionary method is more effective than ART in the particular case of limiting projection directions to four.

  7. Multiresolution reconstruction method to optoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Patrickeyev, Igor; Oraevsky, Alexander A.

    2003-06-01

    A new method for reconstruction of optoacoustic images is proposed. The method of image reconstruction incorporates multiresolution wavelet filtering into spherical back-projection algorithm. According to our method, each optoacoustic signal detected with an array of ultrawide-band transducers is decomposed into a set of self-similar wavelets with different resolution (characteristic frequency) and then back-projected along the spherical traces for each resolution scale separately. The advantage of this approach is that one can reconstruct objects of a preferred size or a range of sizes. The sum of all images reconstructed with different resolutions yields an image that visualizes small and large objects at once. An approximate speed of the proposed algorithm is of the same order as algorithm, based on the Fast Fourier Transform (FFT). The accuracy of the proposed method is illustrated by images, which are reconstructed from simulated optoacoustic signals as well as signals measured with the Laser Optoacoustic Imaging System (LOIS) from a loop of blood vessel embedded in a gel phantom. The method can be used for contrast-enhanced optoacoustic imaging in the depth of tissue, i.e. for medical applications such as breast cancer or prostate cancer detection.

  8. 4-D imaging and monitoring of the Solfatara crater (Italy) by ambient noise tomography

    NASA Astrophysics Data System (ADS)

    Pilz, Marco; Parolai, Stefano; Woith, Heiko; Gresse, Marceau; Vandemeulebrouck, Jean

    2016-04-01

    Imaging shallow subsurface structures and monitoring related temporal variations are two of the main tasks for modern geosciences and seismology. Although many observations have reported temporal velocity changes, e.g., in volcanic areas and on landslides, new methods based on passive sources like ambient seismic noise can provide accurate spatially and temporally resolved information on the velocity structure and on velocity changes. The success of these passive applications is explained by the fact that these methods are based on surface waves which are always present in the ambient seismic noise wave field because they are excited preferentially by superficial sources. Such surface waves can easily be extracted because they dominate the Greeńs function between receivers located at the surface. For real-time monitoring of the shallow velocity structure of the Solfatara crater, one of the forty volcanoes in the Campi Flegrei area characterized by an intense hydrothermal activity due to the interaction of deep convection and meteoric water, we have installed a dense network of 50 seismological sensing units covering the whole surface area in the framework of the European project MED-SUV (The MED-SUV project has received funding from the European Union Seventh Framework Programme FP7 under Grant agreement no 308665). Continuous recordings of the ambient seismic noise over several days as well as signals of an active vibroseis source have been used. Based on a weighted inversion procedure for 3D-passive imaging using ambient noise cross-correlations of both Rayleigh and Love waves, we will present a high-resolution shear-wave velocity model of the structure beneath the Solfatara crater and its temporal changes. Results of seismic tomography are compared with a 3-D electrical resistivity model and CO2 flux map.

  9. SU-E-QI-17: Dependence of 3D/4D PET Quantitative Image Features On Noise

    SciTech Connect

    Oliver, J; Budzevich, M; Zhang, G; Latifi, K; Dilling, T; Balagurunathan, Y; Gu, Y; Grove, O; Feygelman, V; Gillies, R; Moros, E; Lee, H.

    2014-06-15

    Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.

  10. Heuristic optimization in penumbral image for high resolution reconstructed image

    SciTech Connect

    Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.

    2010-10-15

    Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.

  11. Computational acceleration for MR image reconstruction in partially parallel imaging.

    PubMed

    Ye, Xiaojing; Chen, Yunmei; Huang, Feng

    2011-05-01

    In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images. PMID:20833599

  12. 4D imaging of fracturing in organic-rich shales during heating

    SciTech Connect

    Maya Kobchenko; Hamed Panahi; François Renard; Dag K. Dysthe; Anders Malthe-Sørenssen; Adriano Mazzini; Julien Scheibert1; Bjørn Jamtveit; Paul Meakin

    2011-12-01

    To better understand the mechanisms of fracture pattern development and fluid escape in low permeability rocks, we performed time-resolved in situ X-ray tomography imaging to investigate the processes that occur during the slow heating (from 60 to 400 C) of organic-rich Green River shale. At about 350 C cracks nucleated in the sample, and as the temperature continued to increase, these cracks propagated parallel to shale bedding and coalesced, thus cutting across the sample. Thermogravimetry and gas chromatography revealed that the fracturing occurring at {approx}350 C was associated with significant mass loss and release of light hydrocarbons generated by the decomposition of immature organic matter. Kerogen decomposition is thought to cause an internal pressure build up sufficient to form cracks in the shale, thus providing pathways for the outgoing hydrocarbons. We show that a 2D numerical model based on this idea qualitatively reproduces the experimentally observed dynamics of crack nucleation, growth and coalescence, as well as the irregular outlines of the cracks. Our results provide a new description of fracture pattern formation in low permeability shales.

  13. Computational biomechanics and experimental validation of vessel deformation based on 4D-CT imaging of the porcine aorta

    NASA Astrophysics Data System (ADS)

    Hazer, Dilana; Finol, Ender A.; Kostrzewa, Michael; Kopaigorenko, Maria; Richter, Götz-M.; Dillmann, Rüdiger

    2009-02-01

    Cardiovascular disease results from pathological biomechanical conditions and fatigue of the vessel wall. Image-based computational modeling provides a physical and realistic insight into the patient-specific biomechanics and enables accurate predictive simulations of development, growth and failure of cardiovascular disease. An experimental validation is necessary for the evaluation and the clinical implementation of such computational models. In the present study, we have implemented dynamic Computed-Tomography (4D-CT) imaging and catheter-based in vivo measured pressures to numerically simulate and experimentally evaluate the biomechanics of the porcine aorta. The computations are based on the Finite Element Method (FEM) and simulate the arterial wall response to the transient pressure-based boundary condition. They are evaluated by comparing the numerically predicted wall deformation and that calculated from the acquired 4D-CT data. The dynamic motion of the vessel is quantified by means of the hydraulic diameter, analyzing sequences at 5% increments over the cardiac cycle. Our results show that accurate biomechanical modeling is possible using FEM-based simulations. The RMS error of the computed hydraulic diameter at five cross-sections of the aorta was 0.188, 0.252, 0.280, 0.237 and 0.204 mm, which is equivalent to 1.7%, 2.3%, 2.7%, 2.3% and 2.0%, respectively, when expressed as a function of the time-averaged hydraulic diameter measured from the CT images. The present investigation is a first attempt to simulate and validate vessel deformation based on realistic morphological data and boundary conditions. An experimentally validated system would help in evaluating individual therapies and optimal treatment strategies in the field of minimally invasive endovascular surgery.

  14. BIOFILM IMAGE RECONSTRUCTION FOR ASSESSING STRUCTURAL PARAMETERS

    PubMed Central

    Renslow, Ryan; Lewandowski, Zbigniew; Beyenal, Haluk

    2011-01-01

    The structure of biofilms can be numerically quantified from microscopy images using structural parameters. These parameters are used in biofilm image analysis to compare biofilms, to monitor temporal variation in biofilm structure, to quantify the effects of antibiotics on biofilm structure and to determine the effects of environmental conditions on biofilm structure. It is often hypothesized that biofilms with similar structural parameter values will have similar structures; however, this hypothesis has never been tested. The main goal was to test the hypothesis that the commonly used structural parameters can characterize the differences or similarities between biofilm structures. To achieve this goal 1) biofilm image reconstruction was developed as a new tool for assessing structural parameters, 2) independent reconstructions using the same starting structural parameters were tested to see how they differed from each other, 3) the effect of the original image parameter values on reconstruction success was evaluated and 4) the effect of the number and type of the parameters on reconstruction success was evaluated. It was found that two biofilms characterized by identical commonly used structural parameter values may look different, that the number and size of clusters in the original biofilm image affect image reconstruction success and that, in general, a small set of arbitrarily selected parameters may not reveal relevant differences between biofilm structures. PMID:21280029

  15. Approach for reconstructing anisoplanatic adaptive optics images.

    PubMed

    Aubailly, Mathieu; Roggemann, Michael C; Schulz, Timothy J

    2007-08-20

    Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view corresponding approximately to the isoplanatic angle theta(0). For field angles larger than theta(0), the point spread function (PSF) gradually degrades as the field angle increases. We present a technique to estimate the PSF of an adaptive optics telescope as function of the field angle, and use this information in a space-varying image reconstruction technique. Simulated anisoplanatic intensity images of a star field are reconstructed by means of a block-processing method using the predicted local PSF. Two methods for image recovery are used: matrix inversion with Tikhonov regularization, and the Lucy-Richardson algorithm. Image reconstruction results obtained using the space-varying predicted PSF are compared to space invariant deconvolution results obtained using the on-axis PSF. The anisoplanatic reconstruction technique using the predicted PSF provides a significant improvement of the mean squared error between the reconstructed image and the object compared to the deconvolution performed using the on-axis PSF. PMID:17712366

  16. Multidimensional immunolabeling and 4D time-lapse imaging of vital ex vivo lung tissue

    PubMed Central

    Vierkotten, Sarah; Lindner, Michael; Königshoff, Melanie; Eickelberg, Oliver

    2015-01-01

    During the last decades, the study of cell behavior was largely accomplished in uncoated or extracellular matrix (ECM)-coated plastic dishes. To date, considerable cell biological efforts have tried to model in vitro the natural microenvironment found in vivo. For the lung, explants cultured ex vivo as lung tissue cultures (LTCs) provide a three-dimensional (3D) tissue model containing all cells in their natural microenvironment. Techniques for assessing the dynamic live interaction between ECM and cellular tissue components, however, are still missing. Here, we describe specific multidimensional immunolabeling of living 3D-LTCs, derived from healthy and fibrotic mouse lungs, as well as patient-derived 3D-LTCs, and concomitant real-time four-dimensional multichannel imaging thereof. This approach allowed the evaluation of dynamic interactions between mesenchymal cells and macrophages with their ECM. Furthermore, fibroblasts transiently expressing focal adhesions markers incorporated into the 3D-LTCs, paving new ways for studying the dynamic interaction between cellular adhesions and their natural-derived ECM. A novel protein transfer technology (FuseIt/Ibidi) shuttled fluorescently labeled α-smooth muscle actin antibodies into the native cells of living 3D-LTCs, enabling live monitoring of α-smooth muscle actin-positive stress fibers in native tissue myofibroblasts residing in fibrotic lesions of 3D-LTCs. Finally, this technique can be applied to healthy and diseased human lung tissue, as well as to adherent cells in conventional two-dimensional cell culture. This novel method will provide valuable new insights into the dynamics of ECM (patho)biology, studying in detail the interaction between ECM and cellular tissue components in their natural microenvironment. PMID:26092995

  17. Efficient MR image reconstruction for compressed MR imaging.

    PubMed

    Huang, Junzhou; Zhang, Shaoting; Metaxas, Dimitris

    2011-10-01

    In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (TV) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and TV norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. PMID:21742542

  18. Efficient MR image reconstruction for compressed MR imaging.

    PubMed

    Huang, Junzhou; Zhang, Shaoting; Metaxas, Dimitris

    2010-01-01

    In this paper, we propose an efficient algorithm for MR image reconstruction. The algorithm minimizes a linear combination of three terms corresponding to a least square data fitting, total variation (TV) and L1 norm regularization. This has been shown to be very powerful for the MR image reconstruction. First, we decompose the original problem into L1 and TV norm regularization subproblems respectively. Then, these two subproblems are efficiently solved by existing techniques. Finally, the reconstructed image is obtained from the weighted average of solutions from two subproblems in an iterative framework. We compare the proposed algorithm with previous methods in term of the reconstruction accuracy and computation complexity. Numerous experiments demonstrate the superior performance of the proposed algorithm for compressed MR image reconstruction. PMID:20879224

  19. Geometric reconstruction using tracked ultrasound strain imaging

    NASA Astrophysics Data System (ADS)

    Pheiffer, Thomas S.; Simpson, Amber L.; Ondrake, Janet E.; Miga, Michael I.

    2013-03-01

    The accurate identification of tumor margins during neurosurgery is a primary concern for the surgeon in order to maximize resection of malignant tissue while preserving normal function. The use of preoperative imaging for guidance is standard of care, but tumor margins are not always clear even when contrast agents are used, and so margins are often determined intraoperatively by visual and tactile feedback. Ultrasound strain imaging creates a quantitative representation of tissue stiffness which can be used in real-time. The information offered by strain imaging can be placed within a conventional image-guidance workflow by tracking the ultrasound probe and calibrating the image plane, which facilitates interpretation of the data by placing it within a common coordinate space with preoperative imaging. Tumor geometry in strain imaging is then directly comparable to the geometry in preoperative imaging. This paper presents a tracked ultrasound strain imaging system capable of co-registering with preoperative tomograms and also of reconstructing a 3D surface using the border of the strain lesion. In a preliminary study using four phantoms with subsurface tumors, tracked strain imaging was registered to preoperative image volumes and then tumor surfaces were reconstructed using contours extracted from strain image slices. The volumes of the phantom tumors reconstructed from tracked strain imaging were approximately between 1.5 to 2.4 cm3, which was similar to the CT volumes of 1.0 to 2.3 cm3. Future work will be done to robustly characterize the reconstruction accuracy of the system.

  20. Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

    SciTech Connect

    Kipritidis, John Keall, Paul J.; Siva, Shankar; Hofman, Michael S.; Callahan, Jason; Hicks, Rodney J.

    2014-01-15

    Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metrics model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant

  1. Image reconstruction algorithms with wavelet filtering for optoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Gawali, S.; Leggio, L.; Broadway, C.; González, P.; Sánchez, M.; Rodríguez, S.; Lamela, H.

    2016-03-01

    Optoacoustic imaging (OAI) is a hybrid biomedical imaging modality based on the generation and detection of ultrasound by illuminating the target tissue by laser light. Typically, laser light in visible or near infrared spectrum is used as an excitation source. OAI is based on the implementation of image reconstruction algorithms using the spatial distribution of optical absorption in tissues. In this work, we apply a time-domain back-projection (BP) reconstruction algorithm and a wavelet filtering for point and line detection, respectively. A comparative study between point detection and integrated line detection has been carried out by evaluating their effects on the image reconstructed. Our results demonstrate that the back-projection algorithm proposed is efficient for reconstructing high-resolution images of absorbing spheres embedded in a non-absorbing medium when it is combined with the wavelet filtering.

  2. Multi-contrast magnetic resonance image reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Meng; Chen, Yunmei; Zhang, Hao; Huang, Feng

    2015-03-01

    In clinical exams, multi-contrast images from conventional MRI are scanned with the same field of view (FOV) for complementary diagnostic information, such as proton density- (PD-), T1- and T2-weighted images. Their sharable information can be utilized for more robust and accurate image reconstruction. In this work, we propose a novel model and an efficient algorithm for joint image reconstruction and coil sensitivity estimation in multi-contrast partially parallel imaging (PPI) in MRI. Our algorithm restores the multi-contrast images by minimizing an energy function consisting of an L2-norm fidelity term to reduce construction errors caused by motion, a regularization term of underlying images to preserve common anatomical features by using vectorial total variation (VTV) regularizer, and updating sensitivity maps by Tikhonov smoothness based on their physical property. We present the numerical results including T1- and T2-weighted MR images recovered from partially scanned k-space data and provide the comparisons between our results and those obtained from the related existing works. Our numerical results indicate that the proposed method using vectorial TV and penalties on sensitivities can be made promising and widely used for multi-contrast multi-channel MR image reconstruction.

  3. 4-D segmentation and normalization of 3He MR images for intrasubject assessment of ventilated lung volumes

    NASA Astrophysics Data System (ADS)

    Contrella, Benjamin; Tustison, Nicholas J.; Altes, Talissa A.; Avants, Brian B.; Mugler, John P., III; de Lange, Eduard E.

    2012-03-01

    Although 3He MRI permits compelling visualization of the pulmonary air spaces, quantitation of absolute ventilation is difficult due to confounds such as field inhomogeneity and relative intensity differences between image acquisition; the latter complicating longitudinal investigations of ventilation variation with respiratory alterations. To address these potential difficulties, we present a 4-D segmentation and normalization approach for intra-subject quantitative analysis of lung hyperpolarized 3He MRI. After normalization, which combines bias correction and relative intensity scaling between longitudinal data, partitioning of the lung volume time series is performed by iterating between modeling of the combined intensity histogram as a Gaussian mixture model and modulating the spatial heterogeneity tissue class assignments through Markov random field modeling. Evaluation of the algorithm was retrospectively applied to a cohort of 10 asthmatics between 19-25 years old in which spirometry and 3He MR ventilation images were acquired both before and after respiratory exacerbation by a bronchoconstricting agent (methacholine). Acquisition was repeated under the same conditions from 7 to 467 days (mean +/- standard deviation: 185 +/- 37.2) later. Several techniques were evaluated for matching intensities between the pre and post-methacholine images with the 95th percentile value histogram matching demonstrating superior correlations with spirometry measures. Subsequent analysis evaluated segmentation parameters for assessing ventilation change in this cohort. Current findings also support previous research that areas of poor ventilation in response to bronchoconstriction are relatively consistent over time.

  4. MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

    SciTech Connect

    Chen, G; Pan, X; Stayman, J; Samei, E

    2014-06-15

    Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical

  5. SU-D-207-03: Development of 4D-CBCT Imaging System with Dual Source KV X-Ray Tubes

    SciTech Connect

    Nakamura, M; Ishihara, Y; Matsuo, Y; Ueki, N; Iizuka, Y; Mizowaki, T; Hiraoka, M

    2015-06-15

    Purpose: The purposes of this work are to develop 4D-CBCT imaging system with orthogonal dual source kV X-ray tubes, and to determine the imaging doses from 4D-CBCT scans. Methods: Dual source kV X-ray tubes were used for the 4D-CBCT imaging. The maximum CBCT field of view was 200 mm in diameter and 150 mm in length, and the imaging parameters were 110 kV, 160 mA and 5 ms. The rotational angle was 105°, the rotational speed of the gantry was 1.5°/s, the gantry rotation time was 70 s, and the image acquisition interval was 0.3°. The observed amplitude of infrared marker motion during respiration was used to sort each image into eight respiratory phase bins. The EGSnrc/BEAMnrc and EGSnrc/DOSXYZnrc packages were used to simulate kV X-ray dose distributions of 4D-CBCT imaging. The kV X-ray dose distributions were calculated for 9 lung cancer patients based on the planning CT images with dose calculation grid size of 2.5 x 2.5 x 2.5 mm. The dose covering a 2-cc volume of skin (D2cc), defined as the inner 5 mm of the skin surface with the exception of bone structure, was assessed. Results: A moving object was well identified on 4D-CBCT images in a phantom study. Given a gantry rotational angle of 105° and the configuration of kV X-ray imaging subsystems, both kV X-ray fields overlapped at a part of skin surface. The D2cc for the 4D-CBCT scans was in the range 73.8–105.4 mGy. Linear correlation coefficient between the 1000 minus averaged SSD during CBCT scanning and D2cc was −0.65 (with a slope of −0.17) for the 4D-CBCT scans. Conclusion: We have developed 4D-CBCT imaging system with dual source kV X-ray tubes. The total imaging dose with 4D-CBCT scans was up to 105.4 mGy.

  6. Accelerated Compressed Sensing Based CT Image Reconstruction.

    PubMed

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200

  7. Accelerated Compressed Sensing Based CT Image Reconstruction

    PubMed Central

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R.; Paul, Narinder S.; Cobbold, Richard S. C.

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization. PMID:26167200

  8. Analysis of the advantage of individual PTVs defined on axial 3D CT and 4D CT images for liver cancer.

    PubMed

    Li, Fengxiang; Li, Jianbin; Xing, Jun; Zhang, Yingjie; Fan, Tingyong; Xu, Min; Shang, Dongping; Liu, Tonghai; Song, Jinlong

    2012-11-08

    The purpose of this study was to compare positional and volumetric differences of planning target volumes (PTVs) defined on axial three dimensional CT (3D CT) and four dimensional CT (4D CT) for liver cancer. Fourteen patients with liver cancer underwent 3D CT and 4D CT simulation scans during free breathing. The tumor motion was measured by 4D CT. Three internal target volumes (ITVs) were produced based on the clinical target volume from 3DCT (CTV3D): i) A conventional ITV (ITVconv) was produced by adding 10 mm in CC direction and 5 mm in LR and and AP directions to CTV3D; ii) A specific ITV (ITVspec) was created using a specific margin in transaxial direction; iii) ITVvector was produced by adding an isotropic margin derived from the individual tumor motion vector. ITV4D was defined on the fusion of CTVs on all phases of 4D CT. PTVs were generated by adding a 5 mm setup margin to ITVs. The average centroid shifts between PTVs derived from 3DCT and PTV4D in left-right (LR), anterior-posterior (AP), and cranial-caudal (CC) directions were close to zero. Comparing PTV4D to PTVconv, PTVspec, and PTVvector resulted in a decrease in volume size by 33.18% ± 12.39%, 24.95% ± 13.01%, 48.08% ± 15.32%, respectively. The mean degree of inclusions (DI) of PTV4D in PTVconv, and PTV4D in PTVspec, and PTV4D in PTVvector was 0.98, 0.97, and 0.99, which showed no significant correlation to tumor motion vector (r = -0.470, 0.259, and 0.244; p = 0.090, 0.371, and 0.401). The mean DIs of PTVconv in PTV4D, PTVspec in PTV4D, and PTVvector in PTV4D was 0.66, 0.73, and 0.52. The size of individual PTV from 4D CT is significantly less than that of PTVs from 3DCT. The position of targets derived from axial 3DCT images scatters around the center of 4D targets randomly. Compared to conventional PTV, the use of 3D CT-based PTVs with individual margins cannot significantly reduce normal tissues being unnecessarily irradiated, but may contribute to reducing the risk of missing targets for

  9. Image reconstructions with the rotating RF coil

    NASA Astrophysics Data System (ADS)

    Trakic, A.; Wang, H.; Weber, E.; Li, B. K.; Poole, M.; Liu, F.; Crozier, S.

    2009-12-01

    Recent studies have shown that rotating a single RF transceive coil (RRFC) provides a uniform coverage of the object and brings a number of hardware advantages (i.e. requires only one RF channel, averts coil-coil coupling interactions and facilitates large-scale multi-nuclear imaging). Motion of the RF coil sensitivity profile however violates the standard Fourier Transform definition of a time-invariant signal, and the images reconstructed in this conventional manner can be degraded by ghosting artifacts. To overcome this problem, this paper presents Time Division Multiplexed — Sensitivity Encoding (TDM-SENSE), as a new image reconstruction scheme that exploits the rotation of the RF coil sensitivity profile to facilitate ghost-free image reconstructions and reductions in image acquisition time. A transceive RRFC system for head imaging at 2 Tesla was constructed and applied in a number of in vivo experiments. In this initial study, alias-free head images were obtained in half the usual scan time. It is hoped that new sequences and methods will be developed by taking advantage of coil motion.

  10. 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.

  11. Stochastic image reconstruction for a dual-particle imaging system

    NASA Astrophysics Data System (ADS)

    Hamel, M. C.; Polack, J. K.; Poitrasson-Rivière, A.; Flaska, M.; Clarke, S. D.; Pozzi, S. A.; Tomanin, A.; Peerani, P.

    2016-02-01

    Stochastic image reconstruction has been applied to a dual-particle imaging system being designed for nuclear safeguards applications. The dual-particle imager (DPI) is a combined Compton-scatter and neutron-scatter camera capable of producing separate neutron and photon images. The stochastic origin ensembles (SOE) method was investigated as an imaging method for the DPI because only a minimal estimation of system response is required to produce images with quality that is comparable to common maximum-likelihood methods. This work contains neutron and photon SOE image reconstructions for a 252Cf point source, two mixed-oxide (MOX) fuel canisters representing point sources, and the MOX fuel canisters representing a distributed source. Simulation of the DPI using MCNPX-PoliMi is validated by comparison of simulated and measured results. Because image quality is dependent on the number of counts and iterations used, the relationship between these quantities is investigated.

  12. Integrated Image Reconstruction and Gradient Nonlinearity Correction

    PubMed Central

    Tao, Shengzhen; Trzasko, Joshua D.; Shu, Yunhong; Huston, John; Bernstein, Matt A.

    2014-01-01

    Purpose To describe a model-based reconstruction strategy for routine magnetic resonance imaging (MRI) that accounts for gradient nonlinearity (GNL) during rather than after transformation to the image domain, and demonstrate that this approach reduces the spatial resolution loss that occurs during strictly image-domain GNL-correction. Methods After reviewing conventional GNL-correction methods, we propose a generic signal model for GNL-affected MRI acquisitions, discuss how it incorporates into contemporary image reconstruction platforms, and describe efficient non-uniform fast Fourier transform (NUFFT)-based computational routines for these. The impact of GNL-correction on spatial resolution by the conventional and proposed approaches is investigated on phantom data acquired at varying offsets from gradient isocenter, as well as on fully-sampled and (retrospectively) undersampled in vivo acquisitions. Results Phantom results demonstrate that resolution loss that occurs during GNL-correction is significantly less for the proposed strategy than for the standard approach at distances >10 cm from isocenter with a 35 cm FOV gradient coil. The in vivo results suggest that the proposed strategy better preserves fine anatomical detail than retrospective GNL-correction while offering comparable geometric correction. Conclusion Accounting for GNL during image reconstruction allows geometric distortion to be corrected with less spatial resolution loss than is typically observed with the conventional image domain correction strategy. PMID:25298258

  13. Optimal Discretization Resolution in Algebraic Image Reconstruction

    NASA Astrophysics Data System (ADS)

    Sharif, Behzad; Kamalabadi, Farzad

    2005-11-01

    In this paper, we focus on data-limited tomographic imaging problems where the underlying linear inverse problem is ill-posed. A typical regularized reconstruction algorithm uses algebraic formulation with a predetermined discretization resolution. If the selected resolution is too low, we may loose useful details of the underlying image and if it is too high, the reconstruction will be unstable and the representation will fit irrelevant features. In this work, two approaches are introduced to address this issue. The first approach is using Mallow's CL method or generalized cross-validation. For each of the two methods, a joint estimator of regularization parameter and discretization resolution is proposed and their asymptotic optimality is investigated. The second approach is a Bayesian estimator of the model order using a complexity-penalizing prior. Numerical experiments focus on a space imaging application from a set of limited-angle tomographic observations.

  14. Mirror Surface Reconstruction from a Single Image.

    PubMed

    Liu, Miaomiao; Hartley, Richard; Salzmann, Mathieu

    2015-04-01

    This paper tackles the problem of reconstructing the shape of a smooth mirror surface from a single image. In particular, we consider the case where the camera is observing the reflection of a static reference target in the unknown mirror. We first study the reconstruction problem given dense correspondences between 3D points on the reference target and image locations. In such conditions, our differential geometry analysis provides a theoretical proof that the shape of the mirror surface can be recovered if the pose of the reference target is known. We then relax our assumptions by considering the case where only sparse correspondences are available. In this scenario, we formulate reconstruction as an optimization problem, which can be solved using a nonlinear least-squares method. We demonstrate the effectiveness of our method on both synthetic and real images. We then provide a theoretical analysis of the potential degenerate cases with and without prior knowledge of the pose of the reference target. Finally we show that our theory can be similarly applied to the reconstruction of the surface of transparent object.

  15. Sparse image reconstruction for molecular imaging.

    PubMed

    Ting, Michael; Raich, Raviv; Hero, Alfred O

    2009-06-01

    The application that motivates this paper is molecular imaging at the atomic level. When discretized at subatomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. This paper, therefore, does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing the joint p.d.f. of the observation and image conditioned on the hyperparameters. A thresholding rule that generalizes the hard and soft thresholding rule appears in the course of the derivation. This so-called hybrid thresholding rule, when used in the iterative thresholding framework, gives rise to the hybrid estimator, a generalization of the lasso. Estimates of the hyperparameters for the lasso and hybrid estimator are obtained via Stein's unbiased risk estimate (SURE). A numerical study with a Gaussian psf and two sparse images shows that the hybrid estimator outperforms the lasso.

  16. Speckle image reconstruction of the adaptive optics solar images.

    PubMed

    Zhong, Libo; Tian, Yu; Rao, Changhui

    2014-11-17

    Speckle image reconstruction, in which the speckle transfer function (STF) is modeled as annular distribution according to the angular dependence of adaptive optics (AO) compensation and the individual STF in each annulus is obtained by the corresponding Fried parameter calculated from the traditional spectral ratio method, is used to restore the solar images corrected by AO system in this paper. The reconstructions of the solar images acquired by a 37-element AO system validate this method and the image quality is improved evidently. Moreover, we found the photometric accuracy of the reconstruction is field dependent due to the influence of AO correction. With the increase of angular separation of the object from the AO lockpoint, the relative improvement becomes approximately more and more effective and tends to identical in the regions far away the central field of view. The simulation results show this phenomenon is mainly due to the disparity of the calculated STF from the real AO STF with the angular dependence.

  17. Propagation phasor approach for holographic image reconstruction

    PubMed Central

    Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

    2016-01-01

    To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671

  18. Propagation phasor approach for holographic image reconstruction

    NASA Astrophysics Data System (ADS)

    Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

    2016-03-01

    To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears.

  19. Context dependent anti-aliasing image reconstruction

    NASA Technical Reports Server (NTRS)

    Beaudet, Paul R.; Hunt, A.; Arlia, N.

    1989-01-01

    Image Reconstruction has been mostly confined to context free linear processes; the traditional continuum interpretation of digital array data uses a linear interpolator with or without an enhancement filter. Here, anti-aliasing context dependent interpretation techniques are investigated for image reconstruction. Pattern classification is applied to each neighborhood to assign it a context class; a different interpolation/filter is applied to neighborhoods of differing context. It is shown how the context dependent interpolation is computed through ensemble average statistics using high resolution training imagery from which the lower resolution image array data is obtained (simulation). A quadratic least squares (LS) context-free image quality model is described from which the context dependent interpolation coefficients are derived. It is shown how ensembles of high-resolution images can be used to capture the a priori special character of different context classes. As a consequence, a priori information such as the translational invariance of edges along the edge direction, edge discontinuity, and the character of corners is captured and can be used to interpret image array data with greater spatial resolution than would be expected by the Nyquist limit. A Gibb-like artifact associated with this super-resolution is discussed. More realistic context dependent image quality models are needed and a suggestion is made for using a quality model which now is finding application in data compression.

  20. Real-time image-content-based beamline control for smart 4D X-ray imaging.

    PubMed

    Vogelgesang, Matthias; Farago, Tomas; Morgeneyer, Thilo F; Helfen, Lukas; Dos Santos Rolo, Tomy; Myagotin, Anton; Baumbach, Tilo

    2016-09-01

    Real-time processing of X-ray image data acquired at synchrotron radiation facilities allows for smart high-speed experiments. This includes workflows covering parameterized and image-based feedback-driven control up to the final storage of raw and processed data. Nevertheless, there is presently no system that supports an efficient construction of such experiment workflows in a scalable way. Thus, here an architecture based on a high-level control system that manages low-level data acquisition, data processing and device changes is described. This system is suitable for routine as well as prototypical experiments, and provides specialized building blocks to conduct four-dimensional in situ, in vivo and operando tomography and laminography. PMID:27577784

  1. Three-dimensional volumetric object reconstruction using computational integral imaging.

    PubMed

    Hong, Seung-Hyun; Jang, Ju-Seog; Javidi, Bahram

    2004-02-01

    We propose a three-dimensional (3D) imaging technique that can sense a 3D scene and computationally reconstruct it as a 3D volumetric image. Sensing of the 3D scene is carried out by obtaining elemental images optically using a pickup microlens array and a detector array. Reconstruction of volume pixels of the scene is accomplished by computationally simulating optical reconstruction according to ray optics. The entire pixels of the recorded elemental images contribute to volumetric reconstruction of the 3D scene. Image display planes at arbitrary distances from the display microlens array are computed and reconstructed by back propagating the elemental images through a computer synthesized pinhole array based on ray optics. We present experimental results of 3D image sensing and volume pixel reconstruction to test and verify the performance of the algorithm and the imaging system. The volume pixel values can be used for 3D image surface reconstruction.

  2. SU-E-J-154: Image Quality Assessment of Contrast-Enhanced 4D-CT for Pancreatic Adenocarcinoma in Radiotherapy Simulation

    SciTech Connect

    Choi, W; Xue, M; Patel, K; Regine, W; Wang, J; D’Souza, W; Lu, W; Kang, M; Klahr, P

    2015-06-15

    Purpose: This study presents quantitative and qualitative assessment of the image qualities in contrast-enhanced (CE) 3D-CT, 4D-CT and CE 4D-CT to identify feasibility for replacing the clinical standard simulation with a single CE 4D-CT for pancreatic adenocarcinoma (PDA) in radiotherapy simulation. Methods: Ten PDA patients were enrolled and underwent three CT scans: a clinical standard pair of CE 3D-CT immediately followed by a 4D-CT, and a CE 4D-CT one week later. Physicians qualitatively evaluated the general image quality and regional vessel definitions and gave a score from 1 to 5. Next, physicians delineated the contours of the tumor (T) and the normal pancreatic parenchyma (P) on the three CTs (CE 3D-CT, 50% phase for 4D-CT and CE 4D-CT), then high density areas were automatically removed by thresholding at 500 HU and morphological operations. The pancreatic tumor contrast-to-noise ratio (CNR), signal-tonoise ratio (SNR) and conspicuity (C, absolute difference of mean enhancement levels in P and T) were computed to quantitatively assess image quality. The Wilcoxon rank sum test was used to compare these quantities. Results: In qualitative evaluations, CE 3D-CT and CE 4D-CT scored equivalently (4.4±0.4 and 4.3±0.4) and both were significantly better than 4D-CT (3.1±0.6). In quantitative evaluations, the C values were higher in CE 4D-CT (28±19 HU, p=0.19 and 0.17) than the clinical standard pair of CE 3D-CT and 4D-CT (17±12 and 16±17 HU, p=0.65). In CE 3D-CT and CE 4D-CT, mean CNR (1.8±1.4 and 1.8±1.7, p=0.94) and mean SNR (5.8±2.6 and 5.5±3.2, p=0.71) both were higher than 4D-CT (CNR: 1.1±1.3, p<0.3; SNR: 3.3±2.1, p<0.1). The absolute enhancement levels for T and P were higher in CE 4D-CT (87, 82 HU) than in CE 3D-CT (60, 56) and 4DCT (53, 70). Conclusions: The individually optimized CE 4D-CT is feasible and achieved comparable image qualities to the clinical standard simulation. This study was supported in part by Philips Healthcare.

  3. Near Real-Time Solar Image Reconstruction

    NASA Astrophysics Data System (ADS)

    Yang, G.; Denker, C.; Wang, H.

    2001-05-01

    We use a Linux Beowulf cluster to build a system for near real-time solar image reconstruction with the goal to obtain diffraction limited solar images at a cadence of one minute. This gives us immediate access to high-level data products and enables direct visualization of dynamic processes on the Sun. Space weather warnings and flare forecasting will benefit from this project. The image processing algorithms are based on the speckle masking method combined with frame selection. The parallel programs use explicit message passing via Parallel Virtual Machine (PVM). The preliminary results are very promising. Now, we can construct a 256 by 256 pixel image out of 50 short-exposure images within one minute on a Beowulf cluster with four 500~MHz CPUs. In addition, we want to explore the possibility of applying parallel computing on Beowulf clusters to other complex data reduction and analysis problems that we encounter, e.g., in multi-dimensional spectro-polarimetry.

  4. Performance-based assessment of reconstructed images

    SciTech Connect

    Hanson, Kenneth

    2009-01-01

    During the early 90s, I engaged in a productive and enjoyable collaboration with Robert Wagner and his colleague, Kyle Myers. We explored the ramifications of the principle that tbe quality of an image should be assessed on the basis of how well it facilitates the performance of appropriate visual tasks. We applied this principle to algorithms used to reconstruct scenes from incomplete and/or noisy projection data. For binary visual tasks, we used both the conventional disk detection and a new challenging task, inspired by the Rayleigh resolution criterion, of deciding whether an object was a blurred version of two dots or a bar. The results of human and machine observer tests were summarized with the detectability index based on the area under the ROC curve. We investigated a variety of reconstruction algorithms, including ART, with and without a nonnegativity constraint, and the MEMSYS3 algorithm. We concluded that the performance of the Raleigh task was optimized when the strength of the prior was near MEMSYS's default 'classic' value for both human and machine observers. A notable result was that the most-often-used metric of rms error in the reconstruction was not necessarily indicative of the value of a reconstructed image for the purpose of performing visual tasks.

  5. 4D-Imaging of the Lung: Reproducibility of Lesion Size and Displacement on Helical CT, MRI, and Cone Beam CT in a Ventilated Ex Vivo System

    SciTech Connect

    Biederer, Juergen Dinkel, Julien; Remmert, Gregor; Jetter, Siri; Nill, Simeon; Moser, Torsten; Bendl, Rolf; Thierfelder, Carsten; Fabel, Michael; Oelfke, Uwe; Bock, Michael; Plathow, Christian; Bolte, Hendrik; Welzel, Thomas; Hoffmann, Beata; Hartmann, Guenter; Schlegel, Wolfgang; Debus, Juergen; Heller, Martin

    2009-03-01

    Purpose: Four-dimensional (4D) imaging is a key to motion-adapted radiotherapy of lung tumors. We evaluated in a ventilated ex vivo system how size and displacement of artificial pulmonary nodules are reproduced with helical 4D-CT, 4D-MRI, and linac-integrated cone beam CT (CBCT). Methods and Materials: Four porcine lungs with 18 agarose nodules (mean diameters 1.3-1.9 cm), were ventilated inside a chest phantom at 8/min and subject to 4D-CT (collimation 24 x 1.2 mm, pitch 0.1, slice/increment 24x10{sup 2}/1.5/0.8 mm, pitch 0.1, temporal resolution 0.5 s), 4D-MRI (echo-shared dynamic three-dimensional-flash; repetition/echo time 2.13/0.72 ms, voxel size 2.7 x 2.7 x 4.0 mm, temporal resolution 1.4 s) and linac-integrated 4D-CBCT (720 projections, 3-min rotation, temporal resolution {approx}1 s). Static CT without respiration served as control. Three observers recorded lesion size (RECIST-diameters x/y/z) and axial displacement. Interobserver- and interphase-variation coefficients (IO/IP VC) of measurements indicated reproducibility. Results: Mean x/y/z lesion diameters in cm were equal on static and dynamic CT (1.88/1.87; 1.30/1.39; 1.71/1.73; p > 0.05), but appeared larger on MRI and CBCT (2.06/1.95 [p < 0.05 vs. CT]; 1.47/1.28 [MRI vs. CT/CBCT p < 0.05]; 1.86/1.83 [CT vs. CBCT p < 0.05]). Interobserver-VC for lesion sizes were 2.54-4.47% (CT), 2.29-4.48% (4D-CT); 5.44-6.22% (MRI) and 4.86-6.97% (CBCT). Interphase-VC for lesion sizes ranged from 2.28% (4D-CT) to 10.0% (CBCT). Mean displacement in cm decreased from static CT (1.65) to 4D-CT (1.40), CBCT (1.23) and MRI (1.16). Conclusions: Lesion sizes are exactly reproduced with 4D-CT but overestimated on 4D-MRI and CBCT with a larger variability due to limited temporal and spatial resolution. All 4D-modalities underestimate lesion displacement.

  6. Clinical evaluation of 4D PET motion compensation strategies for treatment verification in ion beam therapy

    NASA Astrophysics Data System (ADS)

    Gianoli, Chiara; Kurz, Christopher; Riboldi, Marco; Bauer, Julia; Fontana, Giulia; Baroni, Guido; Debus, Jürgen; Parodi, Katia

    2016-06-01

    A clinical trial named PROMETHEUS is currently ongoing for inoperable hepatocellular carcinoma (HCC) at the Heidelberg Ion Beam Therapy Center (HIT, Germany). In this framework, 4D PET-CT datasets are acquired shortly after the therapeutic treatment to compare the irradiation induced PET image with a Monte Carlo PET prediction resulting from the simulation of treatment delivery. The extremely low count statistics of this measured PET image represents a major limitation of this technique, especially in presence of target motion. The purpose of the study is to investigate two different 4D PET motion compensation strategies towards the recovery of the whole count statistics for improved image quality of the 4D PET-CT datasets for PET-based treatment verification. The well-known 4D-MLEM reconstruction algorithm, embedding the motion compensation in the reconstruction process of 4D PET sinograms, was compared to a recently proposed pre-reconstruction motion compensation strategy, which operates in sinogram domain by applying the motion compensation to the 4D PET sinograms. With reference to phantom and patient datasets, advantages and drawbacks of the two 4D PET motion compensation strategies were identified. The 4D-MLEM algorithm was strongly affected by inverse inconsistency of the motion model but demonstrated the capability to mitigate the noise-break-up effects. Conversely, the pre-reconstruction warping showed less sensitivity to inverse inconsistency but also more noise in the reconstructed images. The comparison was performed by relying on quantification of PET activity and ion range difference, typically yielding similar results. The study demonstrated that treatment verification of moving targets could be accomplished by relying on the whole count statistics image quality, as obtained from the application of 4D PET motion compensation strategies. In particular, the pre-reconstruction warping was shown to represent a promising choice when combined with intra-reconstruction

  7. Clinical evaluation of 4D PET motion compensation strategies for treatment verification in ion beam therapy.

    PubMed

    Gianoli, Chiara; Kurz, Christopher; Riboldi, Marco; Bauer, Julia; Fontana, Giulia; Baroni, Guido; Debus, Jürgen; Parodi, Katia

    2016-06-01

    A clinical trial named PROMETHEUS is currently ongoing for inoperable hepatocellular carcinoma (HCC) at the Heidelberg Ion Beam Therapy Center (HIT, Germany). In this framework, 4D PET-CT datasets are acquired shortly after the therapeutic treatment to compare the irradiation induced PET image with a Monte Carlo PET prediction resulting from the simulation of treatment delivery. The extremely low count statistics of this measured PET image represents a major limitation of this technique, especially in presence of target motion. The purpose of the study is to investigate two different 4D PET motion compensation strategies towards the recovery of the whole count statistics for improved image quality of the 4D PET-CT datasets for PET-based treatment verification. The well-known 4D-MLEM reconstruction algorithm, embedding the motion compensation in the reconstruction process of 4D PET sinograms, was compared to a recently proposed pre-reconstruction motion compensation strategy, which operates in sinogram domain by applying the motion compensation to the 4D PET sinograms. With reference to phantom and patient datasets, advantages and drawbacks of the two 4D PET motion compensation strategies were identified. The 4D-MLEM algorithm was strongly affected by inverse inconsistency of the motion model but demonstrated the capability to mitigate the noise-break-up effects. Conversely, the pre-reconstruction warping showed less sensitivity to inverse inconsistency but also more noise in the reconstructed images. The comparison was performed by relying on quantification of PET activity and ion range difference, typically yielding similar results. The study demonstrated that treatment verification of moving targets could be accomplished by relying on the whole count statistics image quality, as obtained from the application of 4D PET motion compensation strategies. In particular, the pre-reconstruction warping was shown to represent a promising choice when combined with intra-reconstruction

  8. 4D Electron Tomography

    NASA Astrophysics Data System (ADS)

    Kwon, Oh-Hoon; Zewail, Ahmed H.

    2010-06-01

    Electron tomography provides three-dimensional (3D) imaging of noncrystalline and crystalline equilibrium structures, as well as elemental volume composition, of materials and biological specimens, including those of viruses and cells. We report the development of 4D electron tomography by integrating the fourth dimension (time resolution) with the 3D spatial resolution obtained from a complete tilt series of 2D projections of an object. The different time frames of tomograms constitute a movie of the object in motion, thus enabling studies of nonequilibrium structures and transient processes. The method was demonstrated using carbon nanotubes of a bracelet-like ring structure for which 4D tomograms display different modes of motion, such as breathing and wiggling, with resonance frequencies up to 30 megahertz. Applications can now make use of the full space-time range with the nanometer-femtosecond resolution of ultrafast electron tomography.

  9. Hyperspectral image reconstruction for diffuse optical tomography

    PubMed Central

    Larusson, Fridrik; Fantini, Sergio; Miller, Eric L.

    2011-01-01

    We explore the development and performance of algorithms for hyperspectral diffuse optical tomography (DOT) for which data from hundreds of wavelengths are collected and used to determine the concentration distribution of chromophores in the medium under investigation. An efficient method is detailed for forming the images using iterative algorithms applied to a linearized Born approximation model assuming the scattering coefficient is spatially constant and known. The L-surface framework is employed to select optimal regularization parameters for the inverse problem. We report image reconstructions using 126 wavelengths with estimation error in simulations as low as 0.05 and mean square error of experimental data of 0.18 and 0.29 for ink and dye concentrations, respectively, an improvement over reconstructions using fewer specifically chosen wavelengths. PMID:21483616

  10. Deep Reconstruction Models for Image Set Classification.

    PubMed

    Hayat, Munawar; Bennamoun, Mohammed; An, Senjian

    2015-04-01

    Image set classification finds its applications in a number of real-life scenarios such as classification from surveillance videos, multi-view camera networks and personal albums. Compared with single image based classification, it offers more promises and has therefore attracted significant research attention in recent years. Unlike many existing methods which assume images of a set to lie on a certain geometric surface, this paper introduces a deep learning framework which makes no such prior assumptions and can automatically discover the underlying geometric structure. Specifically, a Template Deep Reconstruction Model (TDRM) is defined whose parameters are initialized by performing unsupervised pre-training in a layer-wise fashion using Gaussian Restricted Boltzmann Machines (GRBMs). The initialized TDRM is then separately trained for images of each class and class-specific DRMs are learnt. Based on the minimum reconstruction errors from the learnt class-specific models, three different voting strategies are devised for classification. Extensive experiments are performed to demonstrate the efficacy of the proposed framework for the tasks of face and object recognition from image sets. Experimental results show that the proposed method consistently outperforms the existing state of the art methods. PMID:26353289

  11. TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion

    SciTech Connect

    Wei, J; Yuan, A; Li, G

    2014-06-15

    Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational

  12. A sparse reconstruction algorithm for ultrasonic images in nondestructive testing.

    PubMed

    Guarneri, Giovanni Alfredo; Pipa, Daniel Rodrigues; Neves Junior, Flávio; de Arruda, Lúcia Valéria Ramos; Zibetti, Marcelo Victor Wüst

    2015-01-01

    Ultrasound imaging systems (UIS) are essential tools in nondestructive testing (NDT). In general, the quality of images depends on two factors: system hardware features and image reconstruction algorithms. This paper presents a new image reconstruction algorithm for ultrasonic NDT. The algorithm reconstructs images from A-scan signals acquired by an ultrasonic imaging system with a monostatic transducer in pulse-echo configuration. It is based on regularized least squares using a l1 regularization norm. The method is tested to reconstruct an image of a point-like reflector, using both simulated and real data. The resolution of reconstructed image is compared with four traditional ultrasonic imaging reconstruction algorithms: B-scan, SAFT, ω-k SAFT and regularized least squares (RLS). The method demonstrates significant resolution improvement when compared with B-scan-about 91% using real data. The proposed scheme also outperforms traditional algorithms in terms of signal-to-noise ratio (SNR). PMID:25905700

  13. SU-E-J-200: A Dosimetric Analysis of 3D Versus 4D Image-Based Dose Calculation for Stereotactic Body Radiation Therapy in Lung Tumors

    SciTech Connect

    Ma, M; Rouabhi, O; Flynn, R; Xia, J; Bayouth, J

    2014-06-01

    Purpose: To evaluate the dosimetric difference between 3D and 4Dweighted dose calculation using patient specific respiratory trace and deformable image registration for stereotactic body radiation therapy in lung tumors. Methods: Two dose calculation techniques, 3D and 4D-weighed dose calculation, were used for dosimetric comparison for 9 lung cancer patients. The magnitude of the tumor motion varied from 3 mm to 23 mm. Breath-hold exhale CT was used for 3D dose calculation with ITV generated from the motion observed from 4D-CT. For 4D-weighted calculation, dose of each binned CT image from the ten breathing amplitudes was first recomputed using the same planning parameters as those used in the 3D calculation. The dose distribution of each binned CT was mapped to the breath-hold CT using deformable image registration. The 4D-weighted dose was computed by summing the deformed doses with the temporal probabilities calculated from their corresponding respiratory traces. Dosimetric evaluation criteria includes lung V20, mean lung dose, and mean tumor dose. Results: Comparing with 3D calculation, lung V20, mean lung dose, and mean tumor dose using 4D-weighted dose calculation were changed by −0.67% ± 2.13%, −4.11% ± 6.94% (−0.36 Gy ± 0.87 Gy), −1.16% ± 1.36%(−0.73 Gy ± 0.85 Gy) accordingly. Conclusion: This work demonstrates that conventional 3D dose calculation method may overestimate the lung V20, MLD, and MTD. The absolute difference between 3D and 4D-weighted dose calculation in lung tumor may not be clinically significant. This research is supported by Siemens Medical Solutions USA, Inc and Iowa Center for Research By Undergraduates.

  14. Abdominal 4D Flow MR Imaging in a Breath Hold: Combination of Spiral Sampling and Dynamic Compressed Sensing for Highly Accelerated Acquisition

    PubMed Central

    Knight-Greenfield, Ashley; Jajamovich, Guido; Besa, Cecilia; Cui, Yong; Stalder, Aurélien; Markl, Michael; Taouli, Bachir

    2015-01-01

    Purpose To develop a highly accelerated phase-contrast cardiac-gated volume flow measurement (four-dimensional [4D] flow) magnetic resonance (MR) imaging technique based on spiral sampling and dynamic compressed sensing and to compare this technique with established phase-contrast imaging techniques for the quantification of blood flow in abdominal vessels. Materials and Methods This single-center prospective study was compliant with HIPAA and approved by the institutional review board. Ten subjects (nine men, one woman; mean age, 51 years; age range, 30–70 years) were enrolled. Seven patients had liver disease. Written informed consent was obtained from all participants. Two 4D flow acquisitions were performed in each subject, one with use of Cartesian sampling with respiratory tracking and the other with use of spiral sampling and a breath hold. Cartesian two-dimensional (2D) cine phase-contrast images were also acquired in the portal vein. Two observers independently assessed vessel conspicuity on phase-contrast three-dimensional angiograms. Quantitative flow parameters were measured by two independent observers in major abdominal vessels. Intertechnique concordance was quantified by using Bland-Altman and logistic regression analyses. Results There was moderate to substantial agreement in vessel conspicuity between 4D flow acquisitions in arteries and veins (κ = 0.71 and 0.61, respectively, for observer 1; κ = 0.71 and 0.44 for observer 2), whereas more artifacts were observed with spiral 4D flow (κ = 0.30 and 0.20). Quantitative measurements in abdominal vessels showed good equivalence between spiral and Cartesian 4D flow techniques (lower bound of the 95% confidence interval: 63%, 77%, 60%, and 64% for flow, area, average velocity, and peak velocity, respectively). For portal venous flow, spiral 4D flow was in better agreement with 2D cine phase-contrast flow (95% limits of agreement: −8.8 and 9.3 mL/sec, respectively) than was Cartesian 4D flow (95

  15. MAME Models for 4D Live-cell Imaging of Tumor: Microenvironment Interactions that Impact Malignant Progression

    PubMed Central

    Sameni, Mansoureh; Anbalagan, Arulselvi; Olive, Mary B.; Moin, Kamiar; Mattingly, Raymond R.; Sloane, Bonnie F.

    2012-01-01

    We have developed 3D coculture models, which we term MAME (mammary architecture and microenvironment engineering), and used them for live-cell imaging in real-time of cell:cell interactions. Our overall goal was to develop models that recapitulate the architecture of preinvasive breast lesions to study their progression to an invasive phenotype. Specifically, we developed models to analyze interactions among pre-malignant breast epithelial cell variants and other cell types of the tumor microenvironment that have been implicated in enhancing or reducing the progression of preinvasive breast epithelial cells to invasive ductal carcinomas. Other cell types studied to date are myoepithelial cells, fibroblasts, macrophages and blood and lymphatic microvascular endothelial cells. In addition to the MAME models, which are designed to recapitulate the cellular interactions within the breast during cancer progression, we have developed comparable models for the progression of prostate cancers. Here we illustrate the procedures for establishing the 3D cocultures along with the use of live-cell imaging and a functional proteolysis assay to follow the transition of cocultures of breast ductal carcinoma in situ (DCIS) cells and fibroblasts to an invasive phenotype over time, in this case over twenty-three days in culture. The MAME cocultures consist of multiple layers. Fibroblasts are embedded in the bottom layer of type I collagen. On that is placed a layer of reconstituted basement membrane (rBM) on which DCIS cells are seeded. A final top layer of 2% rBM is included and replenished with every change of media. To image proteolysis associated with the progression to an invasive phenotype, we use dye-quenched (DQ) fluorescent matrix proteins (DQ-collagen I mixed with the layer of collagen I and DQ-collagen IV mixed with the middle layer of rBM) and observe live cultures using confocal microscopy. Optical sections are captured, processed and reconstructed in 3D with Volocity

  16. A Pilot Evaluation of a 4-Dimensional Cone-Beam Computed Tomographic Scheme Based on Simultaneous Motion Estimation and Image Reconstruction

    SciTech Connect

    Dang, Jun; Gu, Xuejun; Pan, Tinsu; Wang, Jing

    2015-02-01

    Purpose: To evaluate the performance of a 4-dimensional (4-D) cone-beam computed tomographic (CBCT) reconstruction scheme based on simultaneous motion estimation and image reconstruction (SMEIR) through patient studies. Methods and Materials: The SMEIR algorithm contains 2 alternating steps: (1) motion-compensated CBCT reconstruction using projections from all phases to reconstruct a reference phase 4D-CBCT by explicitly considering the motion models between each different phase and (2) estimation of motion models directly from projections by matching the measured projections to the forward projection of the deformed reference phase 4D-CBCT. Four lung cancer patients were scanned for 4 to 6 minutes to obtain approximately 2000 projections for each patient. To evaluate the performance of the SMEIR algorithm on a conventional 1-minute CBCT scan, the number of projections at each phase was reduced by a factor of 5, 8, or 10 for each patient. Then, 4D-CBCTs were reconstructed from the down-sampled projections using Feldkamp-Davis-Kress, total variation (TV) minimization, prior image constrained compressive sensing (PICCS), and SMEIR. Using the 4D-CBCT reconstructed from the fully sampled projections as a reference, the relative error (RE) of reconstructed images, root mean square error (RMSE), and maximum error (MaxE) of estimated tumor positions were analyzed to quantify the performance of the SMEIR algorithm. Results: The SMEIR algorithm can achieve results consistent with the reference 4D-CBCT reconstructed with many more projections per phase. With an average of 30 to 40 projections per phase, the MaxE in tumor position detection is less than 1 mm in SMEIR for all 4 patients. Conclusion: The results from a limited number of patients show that SMEIR is a promising tool for high-quality 4D-CBCT reconstruction and tumor motion modeling.

  17. Transformation of light double cones in the human retina: the origin of trichromatism, of 4D-spatiotemporal vision, and of patchwise 4D Fourier transformation in Talbot imaging

    NASA Astrophysics Data System (ADS)

    Lauinger, Norbert

    1997-09-01

    The interpretation of the 'inverted' retina of primates as an 'optoretina' (a light cones transforming diffractive cellular 3D-phase grating) integrates the functional, structural, and oscillatory aspects of a cortical layer. It is therefore relevant to consider prenatal developments as a basis of the macro- and micro-geometry of the inner eye. This geometry becomes relevant for the postnatal trichromatic synchrony organization (TSO) as well as the adaptive levels of human vision. It is shown that the functional performances, the trichromatism in photopic vision, the monocular spatiotemporal 3D- and 4D-motion detection, as well as the Fourier optical image transformation with extraction of invariances all become possible. To transform light cones into reciprocal gratings especially the spectral phase conditions in the eikonal of the geometrical optical imaging before the retinal 3D-grating become relevant first, then in the von Laue resp. reciprocal von Laue equation for 3D-grating optics inside the grating and finally in the periodicity of Talbot-2/Fresnel-planes in the near-field behind the grating. It is becoming possible to technically realize -- at least in some specific aspects -- such a cortical optoretina sensor element with its typical hexagonal-concentric structure which leads to these visual functions.

  18. Prior image constrained image reconstruction in emerging computed tomography applications

    NASA Astrophysics Data System (ADS)

    Brunner, Stephen T.

    Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation

  19. Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging

    NASA Astrophysics Data System (ADS)

    Ishihara, Yasutoshi; Kuwabara, Tsuyoshi; Honma, Takumi; Nakagawa, Yohei

    Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function—defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.

  20. Image reconstruction of IRAS survey scans

    NASA Technical Reports Server (NTRS)

    Bontekoe, Tj. Romke

    1990-01-01

    The IRAS survey data can be used successfully to produce images of extended objects. The major difficulties, viz. non-uniform sampling, different response functions for each detector, and varying signal-to-noise levels for each detector for each scan, were resolved. The results of three different image construction techniques are compared: co-addition, constrained least squares, and maximum entropy. The maximum entropy result is superior. An image of the galaxy M51 with an average spatial resolution of 45 arc seconds is presented, using 60 micron survey data. This exceeds the telescope diffraction limit of 1 minute of arc, at this wavelength. Data fusion is a proposed method for combining data from different instruments, with different spacial resolutions, at different wavelengths. Data estimates of the physical parameters, temperature, density and composition, can be made from the data without prior image (re-)construction. An increase in the accuracy of these parameters is expected as the result of this more systematic approach.

  1. IMRT treatment plans and functional planning with functional lung imaging from 4D-CT for thoracic cancer patients

    PubMed Central

    2013-01-01

    Background and purpose Currently, the inhomogeneity of the pulmonary function is not considered when treatment plans are generated in thoracic cancer radiotherapy. This study evaluates the dose of treatment plans on highly-functional volumes and performs functional treatment planning by incorporation of ventilation data from 4D-CT. Materials and methods Eleven patients were included in this retrospective study. Ventilation was calculated using 4D-CT. Two treatment plans were generated for each case, the first one without the incorporation of the ventilation and the second with it. The dose of the first plans was overlapped with the ventilation and analyzed. Highly-functional regions were avoided in the second treatment plans. Results For small targets in the first plans (PTV < 400 cc, 6 cases), all V5, V20 and the mean lung dose values for the highly-functional regions were lower than that of the total lung. For large targets, two out of five cases had higher V5 and V20 values for the highly-functional regions. All the second plans were within constraints. Conclusion Radiation treatments affect functional lung more seriously in large tumor cases. With compromise of dose to other critical organs, functional treatment planning to reduce dose in highly-functional lung volumes can be achieved PMID:23281734

  2. Photogrammetric 3D reconstruction using mobile imaging

    NASA Astrophysics Data System (ADS)

    Fritsch, Dieter; Syll, Miguel

    2015-03-01

    In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

  3. MMSE Reconstruction for 3D Freehand Ultrasound Imaging

    PubMed Central

    Huang, Wei; Zheng, Yibin

    2008-01-01

    The reconstruction of 3D ultrasound (US) images from mechanically registered, but otherwise irregularly positioned, B-scan slices is of great interest in image guided therapy procedures. Conventional 3D ultrasound algorithms have low computational complexity, but the reconstructed volume suffers from severe speckle contamination. Furthermore, the current method cannot reconstruct uniform high-resolution data from several low-resolution B-scans. In this paper, the minimum mean-squared error (MMSE) method is applied to 3D ultrasound reconstruction. Data redundancies due to overlapping samples as well as correlation of the target and speckle are naturally accounted for in the MMSE reconstruction algorithm. Thus, the reconstruction process unifies the interpolation and spatial compounding. Simulation results for synthetic US images are presented to demonstrate the excellent reconstruction. PMID:18382623

  4. A novel CT-FFR method for the coronary artery based on 4D-CT image analysis and structural and fluid analysis

    NASA Astrophysics Data System (ADS)

    Hirohata, K.; Kano, A.; Goryu, A.; Ooga, J.; Hongo, T.; Higashi, S.; Fujisawa, Y.; Wakai, S.; Arakita, K.; Ikeda, Y.; Kaminaga, S.; Ko, B. S.; Seneviratne, S. K.

    2015-03-01

    Non invasive fractional flow reserve derived from CT coronary angiography (CT-FFR) has to date been typically performed using the principles of fluid analysis in which a lumped parameter coronary vascular bed model is assigned to represent the impedance of the downstream coronary vascular networks absent in the computational domain for each coronary outlet. This approach may have a number of limitations. It may not account for the impact of the myocardial contraction and relaxation during the cardiac cycle, patient-specific boundary conditions for coronary artery outlets and vessel stiffness. We have developed a novel approach based on 4D-CT image tracking (registration) and structural and fluid analysis, to address these issues. In our approach, we analyzed the deformation variation of vessels and the volume variation of vessels, primarily from 70% to 100% of cardiac phase, to better define boundary conditions and stiffness of vessels. We used a statistical estimation method based on a hierarchical Bayes model to integrate 4D-CT measurements and structural and fluid analysis data. Under these analysis conditions, we performed structural and fluid analysis to determine pressure, flow rate and CT-FFR. The consistency of this method has been verified by a comparison of 4D-CTFFR analysis results derived from five clinical 4D-CT datasets with invasive measurements of FFR. Additionally, phantom experiments of flexible tubes with/without stenosis using pulsating pumps, flow sensors and pressure sensors were performed. Our results show that the proposed 4D-CT-FFR analysis method has the potential to accurately estimate the effect of coronary artery stenosis on blood flow.

  5. Total variation minimization-based multimodality medical image reconstruction

    NASA Astrophysics Data System (ADS)

    Cui, Xuelin; Yu, Hengyong; Wang, Ge; Mili, Lamine

    2014-09-01

    Since its recent inception, simultaneous image reconstruction for multimodality fusion has received a great deal of attention due to its superior imaging performance. On the other hand, the compressed sensing (CS)-based image reconstruction methods have undergone a rapid development because of their ability to significantly reduce the amount of raw data. In this work, we combine computed tomography (CT) and magnetic resonance imaging (MRI) into a single CS-based reconstruction framework. From a theoretical viewpoint, the CS-based reconstruction methods require prior sparsity knowledge to perform reconstruction. In addition to the conventional data fidelity term, the multimodality imaging information is utilized to improve the reconstruction quality. Prior information in this context is that most of the medical images can be approximated as piecewise constant model, and the discrete gradient transform (DGT), whose norm is the total variation (TV), can serve as a sparse representation. More importantly, the multimodality images from the same object must share structural similarity, which can be captured by DGT. The prior information on similar distributions from the sparse DGTs is employed to improve the CT and MRI image quality synergistically for a CT-MRI scanner platform. Numerical simulation with undersampled CT and MRI datasets is conducted to demonstrate the merits of the proposed hybrid image reconstruction approach. Our preliminary results confirm that the proposed method outperforms the conventional CT and MRI reconstructions when they are applied separately.

  6. Tree STEM Reconstruction Using Vertical Fisheye Images: a Preliminary Study

    NASA Astrophysics Data System (ADS)

    Berveglieri, A.; Tommaselli, A. M. G.

    2016-06-01

    A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM) technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.

  7. 4-D OCT in Developmental Cardiology

    NASA Astrophysics Data System (ADS)

    Jenkins, Michael W.; Rollins, Andrew M.

    Although strong evidence exists to suggest that altered cardiac function can lead to CHDs, few studies have investigated the influential role of cardiac function and biophysical forces on the development of the cardiovascular system due to a lack of proper in vivo imaging tools. 4-D imaging is needed to decipher the complex spatial and temporal patterns of biomechanical forces acting upon the heart. Numerous solutions over the past several years have demonstrated 4-D OCT imaging of the developing cardiovascular system. This chapter will focus on these solutions and explain their context in the evolution of 4-D OCT imaging. The first sections describe the relevant techniques (prospective gating, direct 4-D imaging, retrospective gating), while later sections focus on 4-D Doppler imaging and measurements of force implementing 4-D OCT Doppler. Finally, the techniques are summarized, and some possible future directions are discussed.

  8. Fast iterative image reconstruction of 3D PET data

    SciTech Connect

    Kinahan, P.E.; Townsend, D.W.; Michel, C.

    1996-12-31

    For count-limited PET imaging protocols, two different approaches to reducing statistical noise are volume, or 3D, imaging to increase sensitivity, and statistical reconstruction methods to reduce noise propagation. These two approaches have largely been developed independently, likely due to the perception of the large computational demands of iterative 3D reconstruction methods. We present results of combining the sensitivity of 3D PET imaging with the noise reduction and reconstruction speed of 2D iterative image reconstruction methods. This combination is made possible by using the recently-developed Fourier rebinning technique (FORE), which accurately and noiselessly rebins 3D PET data into a 2D data set. The resulting 2D sinograms are then reconstructed independently by the ordered-subset EM (OSEM) iterative reconstruction method, although any other 2D reconstruction algorithm could be used. We demonstrate significant improvements in image quality for whole-body 3D PET scans by using the FORE+OSEM approach compared with the standard 3D Reprojection (3DRP) algorithm. In addition, the FORE+OSEM approach involves only 2D reconstruction and it therefore requires considerably less reconstruction time than the 3DRP algorithm, or any fully 3D statistical reconstruction algorithm.

  9. The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imaging.

    PubMed

    Fayad, Hadi; Odille, Freddy; Schmidt, Holger; Würslin, Christian; Küstner, Thomas; Feblinger, Jacques; Visvikis, Dimitris

    2015-03-21

    Respiratory motion is a source of artifacts in multimodality imaging such as PET/MR. Solutions include retrospective or prospective gating. They have however found limited use in clinical practice, since their increased overall acquisition duration to maintain overall image quality. More elaborate methods consist of using 4D MR datasets to extract spatial deformations in order to correct for the respiratory motion in PET. The main drawbacks of such approaches is the relatively long acquisition times associated with 4D MR imaging which is often incompatible with clinical PET/MR protocols. The objective of this work was to overcome these limitations by exploiting a generalized reconstruction by inversion of coupled systems (GRICS) approach. The methodology is based on a joint estimation of motion during the MR image reconstruction process, providing internal structure motion and associated deformation matrices for retrospective use in PET respiratory motion correction. This method was first validated on four MR volunteers and two PET/MR patient datasets by comparing GRICS generated MR images to 4D MR series obtained by retrospective gating. In a second step 4D PET datasets corresponding to acquired 4D MR images were simulated using the GATE Monte Carlo simulation platform. GRICS generated deformation matrices were subsequently used to correct respiratory motion in comparison to the 4D MR image based deformations both for the simulated and the two 4D PET/MR patient datasets. Results confirm that GRICS synchronized MR images correlate well with the acquired 4D MR series. Similarly, the use of GRICS for respiratory motion correction allows an equivalent percentage improvement on lesion contrast, position and size, considering the PET simulated tumors as well as PET real tumors. This work demonstrates the potential interest of using GRICS for PET respiratory motion correction in combined PET/MR using shorter duration acquisitions without the need for 4D MRI and

  10. The use of a generalized reconstruction by inversion of coupled systems (GRICS) approach for generic respiratory motion correction in PET/MR imaging

    NASA Astrophysics Data System (ADS)

    Fayad, Hadi; Odille, Freddy; Schmidt, Holger; Würslin, Christian; Küstner, Thomas; Feblinger, Jacques; Visvikis, Dimitris

    2015-03-01

    Respiratory motion is a source of artifacts in multimodality imaging such as PET/MR. Solutions include retrospective or prospective gating. They have however found limited use in clinical practice, since their increased overall acquisition duration to maintain overall image quality. More elaborate methods consist of using 4D MR datasets to extract spatial deformations in order to correct for the respiratory motion in PET. The main drawbacks of such approaches is the relatively long acquisition times associated with 4D MR imaging which is often incompatible with clinical PET/MR protocols. The objective of this work was to overcome these limitations by exploiting a generalized reconstruction by inversion of coupled systems (GRICS) approach. The methodology is based on a joint estimation of motion during the MR image reconstruction process, providing internal structure motion and associated deformation matrices for retrospective use in PET respiratory motion correction. This method was first validated on four MR volunteers and two PET/MR patient datasets by comparing GRICS generated MR images to 4D MR series obtained by retrospective gating. In a second step 4D PET datasets corresponding to acquired 4D MR images were simulated using the GATE Monte Carlo simulation platform. GRICS generated deformation matrices were subsequently used to correct respiratory motion in comparison to the 4D MR image based deformations both for the simulated and the two 4D PET/MR patient datasets. Results confirm that GRICS synchronized MR images correlate well with the acquired 4D MR series. Similarly, the use of GRICS for respiratory motion correction allows an equivalent percentage improvement on lesion contrast, position and size, considering the PET simulated tumors as well as PET real tumors. This work demonstrates the potential interest of using GRICS for PET respiratory motion correction in combined PET/MR using shorter duration acquisitions without the need for 4D MRI and

  11. Magnetic Particle / Magnetic Resonance Imaging: In-Vitro MPI-Guided Real Time Catheter Tracking and 4D Angioplasty Using a Road Map and Blood Pool Tracer Approach

    PubMed Central

    Jung, Caroline; Kaul, Michael Gerhard; Werner, Franziska; Them, Kolja; Reimer, Rudolph; Nielsen, Peter; vom Scheidt, Annika; Adam, Gerhard; Knopp, Tobias; Ittrich, Harald

    2016-01-01

    Purpose In-vitro evaluation of the feasibility of 4D real time tracking of endovascular devices and stenosis treatment with a magnetic particle imaging (MPI) / magnetic resonance imaging (MRI) road map approach and an MPI-guided approach using a blood pool tracer. Materials and Methods A guide wire and angioplasty-catheter were labeled with a thin layer of magnetic lacquer. For real time MPI a custom made software framework was developed. A stenotic vessel phantom filled with saline or superparamagnetic iron oxide nanoparticles (MM4) was equipped with bimodal fiducial markers for co-registration in preclinical 7T MRI and MPI. In-vitro angioplasty was performed inflating the balloon with saline or MM4. MPI data were acquired using a field of view of 37.3×37.3×18.6 mm3 and a frame rate of 46 volumes/sec. Analysis of the magnetic lacquer-marks on the devices were performed with electron microscopy, atomic absorption spectrometry and micro-computed tomography. Results Magnetic marks allowed for MPI/MRI guidance of interventional devices. Bimodal fiducial markers enable MPI/MRI image fusion for MRI based roadmapping. MRI roadmapping and the blood pool tracer approach facilitate MPI real time monitoring of in-vitro angioplasty. Successful angioplasty was verified with MPI and MRI. Magnetic marks consist of micrometer sized ferromagnetic plates mainly composed of iron and iron oxide. Conclusions 4D real time MP imaging, tracking and guiding of endovascular instruments and in-vitro angioplasty is feasible. In addition to an approach that requires a blood pool tracer, MRI based roadmapping might emerge as a promising tool for radiation free 4D MPI-guided interventions. PMID:27249022

  12. Noise and resolution of Bayesian reconstruction for multiple image configurations

    SciTech Connect

    Chinn, G.; Huang, Sung Cheng

    1993-12-01

    Images reconstructed by Bayesian and maximum-likelihood (ML) using a Gibbs prior with prior weight {beta} were compared with images produced by filtered back projection (FBP) from sinogram data simulated with different counts and image configurations. Bayesian images were generated by the OSL algorithm accelerated by an over relaxation parameter. For relatively low {beta}, Bayesian images can yield an overall improvement to the images compared to ML reconstruction. However, for larger {beta}, Bayesian images degrade from the standpoint of noise and quantitation. Compared to FBP, the ML images were superior in a mean square error sense in regions of low activity level and for small structures. At a comparable noise level to FBP, Bayesian reconstruction can be used to effectively recover higher resolution images. The overall performance is dependent on the image structure and the weight of the Bayesian prior.

  13. MO-C-17A-02: A Novel Method for Evaluating Hepatic Stiffness Based On 4D-MRI and Deformable Image Registration

    SciTech Connect

    Cui, T; Liang, X; Czito, B; Palta, M; Bashir, M; Yin, F; Cai, J

    2014-06-15

    Purpose: Quantitative imaging of hepatic stiffness has significant potential in radiation therapy, ranging from treatment planning to response assessment. This study aims to develop a novel, noninvasive method to quantify liver stiffness with 3D strains liver maps using 4D-MRI and deformable image registration (DIR). Methods: Five patients with liver cancer were imaged with an institutionally developed 4D-MRI technique under an IRB-approved protocol. Displacement vector fields (DVFs) across the liver were generated via DIR of different phases of 4D-MRI. Strain tensor at each voxel of interest (VOI) was computed from the relative displacements between the VOI and each of the six adjacent voxels. Three principal strains (E{sub 1}, E{sub 2} and E{sub 3}) of the VOI were derived as the eigenvalue of the strain tensor, which represent the magnitudes of the maximum and minimum stretches. Strain tensors for two regions of interest (ROIs) were calculated and compared for each patient, one within the tumor (ROI{sub 1}) and the other in normal liver distant from the heart (ROI{sub 2}). Results: 3D strain maps were successfully generated fort each respiratory phase of 4D-MRI for all patients. Liver deformations induced by both respiration and cardiac motion were observed. Differences in strain values adjacent to the distant from the heart indicate significant deformation caused by cardiac expansion during diastole. The large E{sub 1}/E{sub 2} (∼2) and E{sub 1}/E{sub 2} (∼10) ratios reflect the predominance of liver deformation in the superior-inferior direction. The mean E{sub 1} in ROI{sub 1} (0.12±0.10) was smaller than in ROI{sub 2} (0.15±0.12), reflecting a higher degree of stiffness of the cirrhotic tumor. Conclusion: We have successfully developed a novel method for quantitatively evaluating regional hepatic stiffness based on DIR of 4D-MRI. Our initial findings indicate that liver strain is heterogeneous, and liver tumors may have lower principal strain values

  14. Imaging 4-D hydrogeologic processes with geophysics: an example using crosswell electrical measurements to characterize a tracer plume

    NASA Astrophysics Data System (ADS)

    Singha, K.; Gorelick, S. M.

    2005-05-01

    Geophysical methods provide an inexpensive way to collect spatially exhaustive data about hydrogeologic, mechanical or geochemical parameters. In the presence of heterogeneity over multiple scales of these parameters at most field sites, geophysical data can contribute greatly to our understanding about the subsurface by providing important data we would otherwise lack without extensive, and often expensive, direct sampling. Recent work has highlighted the use of time-lapse geophysical data to help characterize hydrogeologic processes. We investigate the potential for making quantitative assessments of sodium-chloride tracer transport using 4-D crosswell electrical resistivity tomography (ERT) in a sand and gravel aquifer at the Massachusetts Military Reservation on Cape Cod. Given information about the relation between electrical conductivity and tracer concentration, we can estimate spatial moments from the 3-D ERT inversions, which give us information about tracer mass, center of mass, and dispersivity through time. The accuracy of these integrated measurements of tracer plume behavior is dependent on spatially variable resolution. The ERT inversions display greater apparent dispersion than tracer plumes estimated by 3D advective-dispersive simulation. This behavior is attributed to reduced measurement sensitivity to electrical conductivity values with distance from the electrodes and differential smoothing from tomographic inversion. The latter is a problem common to overparameterized inverse problems, which often occur when real-world budget limitations preclude extensive well-drilling or additional data collection. These results prompt future work on intelligent methods for reparameterizing the inverse problem and coupling additional disparate data sets.

  15. Synergistic image reconstruction for hybrid ultrasound and photoacoustic computed tomography

    NASA Astrophysics Data System (ADS)

    Matthews, Thomas P.; Wang, Kun; Wang, Lihong V.; Anastasio, Mark A.

    2015-03-01

    Conventional photoacoustic computed tomography (PACT) image reconstruction methods assume that the object and surrounding medium are described by a constant speed-of-sound (SOS) value. In order to accurately recover fine structures, SOS heterogeneities should be quantified and compensated for during PACT reconstruction. To address this problem, several groups have proposed hybrid systems that combine PACT with ultrasound computed tomography (USCT). In such systems, a SOS map is reconstructed first via USCT. Consequently, this SOS map is employed to inform the PACT reconstruction method. Additionally, the SOS map can provide structural information regarding tissue, which is complementary to the functional information from the PACT image. We propose a paradigm shift in the way that images are reconstructed in hybrid PACT-USCT imaging. Inspired by our observation that information about the SOS distribution is encoded in PACT measurements, we propose to jointly reconstruct the absorbed optical energy density and SOS distributions from a combined set of USCT and PACT measurements, thereby reducing the two reconstruction problems into one. This innovative approach has several advantages over conventional approaches in which PACT and USCT images are reconstructed independently: (1) Variations in the SOS will automatically be accounted for, optimizing PACT image quality; (2) The reconstructed PACT and USCT images will possess minimal systematic artifacts because errors in the imaging models will be optimally balanced during the joint reconstruction; (3) Due to the exploitation of information regarding the SOS distribution in the full-view PACT data, our approach will permit high-resolution reconstruction of the SOS distribution from sparse array data.

  16. Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

    NASA Astrophysics Data System (ADS)

    Bowen, S. R.; Nyflot, M. J.; Herrmann, C.; Groh, C. M.; Meyer, J.; Wollenweber, S. D.; Stearns, C. W.; Kinahan, P. E.; Sandison, G. A.

    2015-05-01

    Effective positron emission tomography / computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [18F]FDG. The lung lesion insert was driven by six different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses, and 2%-2 mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10-20%, treatment planning errors were 5-10%, and treatment delivery errors were 5-30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5-10% in PET/CT imaging, <5% in treatment planning, and <2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT planning, and RT

  17. Imaging and dosimetric errors in 4D PET/CT-guided radiotherapy from patient-specific respiratory patterns: a dynamic motion phantom end-to-end study

    PubMed Central

    Bowen, S R; Nyflot, M J; Hermann, C; Groh, C; Meyer, J; Wollenweber, S D; Stearns, C W; Kinahan, P E; Sandison, G A

    2015-01-01

    Effective positron emission tomography/computed tomography (PET/CT) guidance in radiotherapy of lung cancer requires estimation and mitigation of errors due to respiratory motion. An end-to-end workflow was developed to measure patient-specific motion-induced uncertainties in imaging, treatment planning, and radiation delivery with respiratory motion phantoms and dosimeters. A custom torso phantom with inserts mimicking normal lung tissue and lung lesion was filled with [18F]FDG. The lung lesion insert was driven by 6 different patient-specific respiratory patterns or kept stationary. PET/CT images were acquired under motionless ground truth, tidal breathing motion-averaged (3D), and respiratory phase-correlated (4D) conditions. Target volumes were estimated by standardized uptake value (SUV) thresholds that accurately defined the ground-truth lesion volume. Non-uniform dose-painting plans using volumetrically modulated arc therapy (VMAT) were optimized for fixed normal lung and spinal cord objectives and variable PET-based target objectives. Resulting plans were delivered to a cylindrical diode array at rest, in motion on a platform driven by the same respiratory patterns (3D), or motion-compensated by a robotic couch with an infrared camera tracking system (4D). Errors were estimated relative to the static ground truth condition for mean target-to-background (T/Bmean) ratios, target volumes, planned equivalent uniform target doses (EUD), and 2%-2mm gamma delivery passing rates. Relative to motionless ground truth conditions, PET/CT imaging errors were on the order of 10–20%, treatment planning errors were 5–10%, and treatment delivery errors were 5–30% without motion compensation. Errors from residual motion following compensation methods were reduced to 5–10% in PET/CT imaging, < 5% in treatment planning, and < 2% in treatment delivery. We have demonstrated that estimation of respiratory motion uncertainty and its propagation from PET/CT imaging to RT

  18. High-Resolution 4D Imaging of Technetium Transport in Porous Media using Preclinical SPECT-CT

    NASA Astrophysics Data System (ADS)

    Dogan, M.; DeVol, T. A.; Groen, H.; Moysey, S. M.; Ramakers, R.; Powell, B. A.

    2015-12-01

    Preclinical SPECT-CT (single-photon emission computed tomography with integrated X-ray computed tomography) offers the potential to quantitatively image the dynamic three-dimensional distribution of radioisotopes with sub-millimeter resolution, overlaid with structural CT images (20-200 micron resolution), making this an attractive method for studying transport in porous media. A preclinical SPECT-CT system (U-SPECT4CT, MILabs BV. Utrecht, The Netherlands) was evaluated for imaging flow and transport of 99mTc (t1/2=6hrs) using a 46,5mm by 156,4mm column packed with individual layers consisting of <0.2mm diameter silica gel, 0.2-0.25, 0.5, 1.0, 2.0, 3.0, and 4.0mm diameter glass beads, and a natural soil sample obtained from the Savannah River Site. The column was saturated with water prior to injecting the 99mTc solution. During the injection the flow was interrupted intermittently for 10 minute periods to allow for the acquisition of a SPECT image of the transport front. Non-uniformity of the front was clearly observed in the images as well as the retarded movement of 99mTc in the soil layer. The latter is suggesting good potential for monitoring transport processes occurring on the timescale of hours. After breakthrough of 99mTc was achieved, the flow was stopped and SPECT data were collected in one hour increments to evaluate the sensitivity of the instrument as the isotope decayed. Fused SPECT- CT images allowed for improved interpretation of 99mTc distributions within individual pore spaces. With ~3 MBq remaining in the column, the lowest activity imaged, it was not possible to clearly discriminate any of the pore spaces.

  19. Calibration and Image Reconstruction for the Hurricane Imaging Radiometer (HIRAD)

    NASA Technical Reports Server (NTRS)

    Ruf, Christopher; Roberts, J. Brent; Biswas, Sayak; James, Mark W.; Miller, Timothy

    2012-01-01

    The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a aprox 70 km swath width with approx 3 km spatial resolution. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.

  20. Numerical modelling and image reconstruction in diffuse optical tomography

    PubMed Central

    Dehghani, Hamid; Srinivasan, Subhadra; Pogue, Brian W.; Gibson, Adam

    2009-01-01

    The development of diffuse optical tomography as a functional imaging modality has relied largely on the use of model-based image reconstruction. The recovery of optical parameters from boundary measurements of light propagation within tissue is inherently a difficult one, because the problem is nonlinear, ill-posed and ill-conditioned. Additionally, although the measured near-infrared signals of light transmission through tissue provide high imaging contrast, the reconstructed images suffer from poor spatial resolution due to the diffuse propagation of light in biological tissue. The application of model-based image reconstruction is reviewed in this paper, together with a numerical modelling approach to light propagation in tissue as well as generalized image reconstruction using boundary data. A comprehensive review and details of the basis for using spatial and structural prior information are also discussed, whereby the use of spectral and dual-modality systems can improve contrast and spatial resolution. PMID:19581256

  1. Assessing Cardiac Injury in Mice With Dual Energy-MicroCT, 4D-MicroCT, and MicroSPECT Imaging After Partial Heart Irradiation

    SciTech Connect

    Lee, Chang-Lung; Min, Hooney; Befera, Nicholas; Clark, Darin; Qi, Yi; Das, Shiva; Johnson, G. Allan; Badea, Cristian T.; Kirsch, David G.

    2014-03-01

    Purpose: To develop a mouse model of cardiac injury after partial heart irradiation (PHI) and to test whether dual energy (DE)-microCT and 4-dimensional (4D)-microCT can be used to assess cardiac injury after PHI to complement myocardial perfusion imaging using micro-single photon emission computed tomography (SPECT). Methods and Materials: To study cardiac injury from tangent field irradiation in mice, we used a small-field biological irradiator to deliver a single dose of 12 Gy x-rays to approximately one-third of the left ventricle (LV) of Tie2Cre; p53{sup FL/+} and Tie2Cre; p53{sup FL/−} mice, where 1 or both alleles of p53 are deleted in endothelial cells. Four and 8 weeks after irradiation, mice were injected with gold and iodinated nanoparticle-based contrast agents, and imaged with DE-microCT and 4D-microCT to evaluate myocardial vascular permeability and cardiac function, respectively. Additionally, the same mice were imaged with microSPECT to assess myocardial perfusion. Results: After PHI with tangent fields, DE-microCT scans showed a time-dependent increase in accumulation of gold nanoparticles (AuNp) in the myocardium of Tie2Cre; p53{sup FL/−} mice. In Tie2Cre; p53{sup FL/−} mice, extravasation of AuNp was observed within the irradiated LV, whereas in the myocardium of Tie2Cre; p53{sup FL/+} mice, AuNp were restricted to blood vessels. In addition, data from DE-microCT and microSPECT showed a linear correlation (R{sup 2} = 0.97) between the fraction of the LV that accumulated AuNp and the fraction of LV with a perfusion defect. Furthermore, 4D-microCT scans demonstrated that PHI caused a markedly decreased ejection fraction, and higher end-diastolic and end-systolic volumes, to develop in Tie2Cre; p53{sup FL/−} mice, which were associated with compensatory cardiac hypertrophy of the heart that was not irradiated. Conclusions: Our results show that DE-microCT and 4D-microCT with nanoparticle-based contrast agents are novel imaging approaches

  2. Reconstruction of biofilm images: combining local and global structural parameters

    SciTech Connect

    Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk

    2014-11-07

    Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parameters into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.

  3. PAINTER: a spatiospectral image reconstruction algorithm for optical interferometry.

    PubMed

    Schutz, Antony; Ferrari, André; Mary, David; Soulez, Ferréol; Thiébaut, Éric; Vannier, Martin

    2014-11-01

    Astronomical optical interferometers sample the Fourier transform of the intensity distribution of a source at the observation wavelength. Because of rapid perturbations caused by atmospheric turbulence, the phases of the complex Fourier samples (visibilities) cannot be directly exploited. Consequently, specific image reconstruction methods have been devised in the last few decades. Modern polychromatic optical interferometric instruments are now paving the way to multiwavelength imaging. This paper is devoted to the derivation of a spatiospectral (3D) image reconstruction algorithm, coined Polychromatic opticAl INTErferometric Reconstruction software (PAINTER). The algorithm relies on an iterative process, which alternates estimation of polychromatic images and complex visibilities. The complex visibilities are not only estimated from squared moduli and closure phases, but also differential phases, which helps to better constrain the polychromatic reconstruction. Simulations on synthetic data illustrate the efficiency of the algorithm and, in particular, the relevance of injecting a differential phases model in the reconstruction.

  4. Algebraic Reconstruction Technique (ART) for parallel imaging reconstruction of undersampled radial data: Application to cardiac cine

    PubMed Central

    Li, Shu; Chan, Cheong; Stockmann, Jason P.; Tagare, Hemant; Adluru, Ganesh; Tam, Leo K.; Galiana, Gigi; Constable, R. Todd; Kozerke, Sebastian; Peters, Dana C.

    2014-01-01

    Purpose To investigate algebraic reconstruction technique (ART) for parallel imaging reconstruction of radial data, applied to accelerated cardiac cine. Methods A GPU-accelerated ART reconstruction was implemented and applied to simulations, point spread functions (PSF) and in twelve subjects imaged with radial cardiac cine acquisitions. Cine images were reconstructed with radial ART at multiple undersampling levels (192 Nr x Np = 96 to 16). Images were qualitatively and quantitatively analyzed for sharpness and artifacts, and compared to filtered back-projection (FBP), and conjugate gradient SENSE (CG SENSE). Results Radial ART provided reduced artifacts and mainly preserved spatial resolution, for both simulations and in vivo data. Artifacts were qualitatively and quantitatively less with ART than FBP using 48, 32, and 24 Np, although FBP provided quantitatively sharper images at undersampling levels of 48-24 Np (all p<0.05). Use of undersampled radial data for generating auto-calibrated coil-sensitivity profiles resulted in slightly reduced quality. ART was comparable to CG SENSE. GPU-acceleration increased ART reconstruction speed 15-fold, with little impact on the images. Conclusion GPU-accelerated ART is an alternative approach to image reconstruction for parallel radial MR imaging, providing reduced artifacts while mainly maintaining sharpness compared to FBP, as shown by its first application in cardiac studies. PMID:24753213

  5. An automated landmark-based elastic registration technique for large deformation recovery from 4-D CT lung images

    NASA Astrophysics Data System (ADS)

    Negahdar, Mohammadreza; Zacarias, Albert; Milam, Rebecca A.; Dunlap, Neal; Woo, Shiao Y.; Amini, Amir A.

    2012-03-01

    The treatment plan evaluation for lung cancer patients involves pre-treatment and post-treatment volume CT imaging of the lung. However, treatment of the tumor volume lung results in structural changes to the lung during the course of treatment. In order to register the pre-treatment volume to post-treatment volume, there is a need to find robust and homologous features which are not affected by the radiation treatment along with a smooth deformation field. Since airways are well-distributed in the entire lung, in this paper, we propose use of airway tree bifurcations for registration of the pre-treatment volume to the post-treatment volume. A dedicated and automated algorithm has been developed that finds corresponding airway bifurcations in both images. To derive the 3-D deformation field, a B-spline transformation model guided by mutual information similarity metric was used to guarantee the smoothness of the transformation while combining global information from bifurcation points. Therefore, the approach combines both global statistical intensity information with local image feature information. Since during normal breathing, the lung undergoes large nonlinear deformations, it is expected that the proposed method would also be applicable to large deformation registration between maximum inhale and maximum exhale images in the same subject. The method has been evaluated by registering 3-D CT volumes at maximum exhale data to all the other temporal volumes in the POPI-model data.

  6. NiftyFit: a Software Package for Multi-parametric Model-Fitting of 4D Magnetic Resonance Imaging Data.

    PubMed

    Melbourne, Andrew; Toussaint, Nicolas; Owen, David; Simpson, Ivor; Anthopoulos, Thanasis; De Vita, Enrico; Atkinson, David; Ourselin, Sebastien

    2016-07-01

    Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require.

  7. NiftyFit: a Software Package for Multi-parametric Model-Fitting of 4D Magnetic Resonance Imaging Data.

    PubMed

    Melbourne, Andrew; Toussaint, Nicolas; Owen, David; Simpson, Ivor; Anthopoulos, Thanasis; De Vita, Enrico; Atkinson, David; Ourselin, Sebastien

    2016-07-01

    Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software package for such multi-contrast Magnetic Resonance Imaging that provides a unified model-fitting framework. We describe model-fitting functionality for Arterial Spin Labeled MRI, T1 Relaxometry, T2 relaxometry and Diffusion Weighted imaging, providing command line documentation to generate the figures in the manuscript. Software and data (using the nifti file format) used in this article are simultaneously provided for download. We also present some extended applications of the joint model fitting framework applied to diffusion weighted imaging and T2 relaxometry, in order to both improve parameter estimation in these models and generate new parameters that link different MR modalities. NiftyFit is intended as a clear and open-source educational release so that the user may adapt and develop their own functionality as they require. PMID:26972806

  8. SU-E-J-151: Dosimetric Evaluation of DIR Mapped Contours for Image Guided Adaptive Radiotherapy with 4D Cone-Beam CT

    SciTech Connect

    Balik, S; Weiss, E; Williamson, J; Hugo, G; Jan, N; Zhang, L; Roman, N; Christensen, G

    2014-06-01

    Purpose: To estimate dosimetric errors resulting from using contours deformably mapped from planning CT to 4D cone beam CT (CBCT) images for image-guided adaptive radiotherapy of locally advanced non-small cell lung cancer (NSCLC). Methods: Ten locally advanced non-small cell lung cancer (NSCLC) patients underwent one planning 4D fan-beam CT (4DFBCT) and weekly 4DCBCT scans. Multiple physicians delineated the gross tumor volume (GTV) and normal structures in planning CT images and only GTV in CBCT images. Manual contours were mapped from planning CT to CBCTs using small deformation, inverse consistent linear elastic (SICLE) algorithm for two scans in each patient. Two physicians reviewed and rated the DIR-mapped (auto) and manual GTV contours as clinically acceptable (CA), clinically acceptable after minor modification (CAMM) and unacceptable (CU). Mapped normal structures were visually inspected and corrected if necessary, and used to override tissue density for dose calculation. CTV (6mm expansion of GTV) and PTV (5mm expansion of CTV) were created. VMAT plans were generated using the DIR-mapped contours to deliver 66 Gy in 33 fractions with 95% and 100% coverage (V66) to PTV and CTV, respectively. Plan evaluation for V66 was based on manual PTV and CTV contours. Results: Mean PTV V66 was 84% (range 75% – 95%) and mean CTV V66 was 97% (range 93% – 100%) for CAMM scored plans (12 plans); and was 90% (range 80% – 95%) and 99% (range 95% – 100%) for CA scored plans (7 plans). The difference in V66 between CAMM and CA was significant for PTV (p = 0.03) and approached significance for CTV (p = 0.07). Conclusion: The quality of DIR-mapped contours directly impacted the plan quality for 4DCBCT-based adaptation. Larger safety margins may be needed when planning with auto contours for IGART with 4DCBCT images. Reseach was supported by NIH P01CA116602.

  9. 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.

  10. 4D megahertz optical coherence tomography (OCT): imaging and live display beyond 1 gigavoxel/sec (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Huber, Robert A.; Draxinger, Wolfgang; Wieser, Wolfgang; Kolb, Jan Philip; Pfeiffer, Tom; Karpf, Sebastian N.; Eibl, Matthias; Klein, Thomas

    2016-03-01

    Over the last 20 years, optical coherence tomography (OCT) has become a valuable diagnostic tool in ophthalmology with several 10,000 devices sold today. Other applications, like intravascular OCT in cardiology and gastro-intestinal imaging will follow. OCT provides 3-dimensional image data with microscopic resolution of biological tissue in vivo. In most applications, off-line processing of the acquired OCT-data is sufficient. However, for OCT applications like OCT aided surgical microscopes, for functional OCT imaging of tissue after a stimulus, or for interactive endoscopy an OCT engine capable of acquiring, processing and displaying large and high quality 3D OCT data sets at video rate is highly desired. We developed such a prototype OCT engine and demonstrate live OCT with 25 volumes per second at a size of 320x320x320 pixels. The computer processing load of more than 1.5 TFLOPS was handled by a GTX 690 graphics processing unit with more than 3000 stream processors operating in parallel. In the talk, we will describe the optics and electronics hardware as well as the software of the system in detail and analyze current limitations. The talk also focuses on new OCT applications, where such a system improves diagnosis and monitoring of medical procedures. The additional acquisition of hyperspectral stimulated Raman signals with the system will be discussed.

  11. A new method for automatic tracking of facial landmarks in 3D motion captured images (4D).

    PubMed

    Al-Anezi, T; Khambay, B; Peng, M J; O'Leary, E; Ju, X; Ayoub, A

    2013-01-01

    The aim of this study was to validate the automatic tracking of facial landmarks in 3D image sequences. 32 subjects (16 males and 16 females) aged 18-35 years were recruited. 23 anthropometric landmarks were marked on the face of each subject with non-permanent ink using a 0.5mm pen. The subjects were asked to perform three facial animations (maximal smile, lip purse and cheek puff) from rest position. Each animation was captured by the 3D imaging system. A single operator manually digitised the landmarks on the 3D facial models and their locations were compared with those of the automatically tracked ones. To investigate the accuracy of manual digitisation, the operator re-digitised the same set of 3D images of 10 subjects (5 male and 5 female) at 1 month interval. The discrepancies in x, y and z coordinates between the 3D position of the manual digitised landmarks and that of the automatic tracked facial landmarks were within 0.17mm. The mean distance between the manually digitised and the automatically tracked landmarks using the tracking software was within 0.55 mm. The automatic tracking of facial landmarks demonstrated satisfactory accuracy which would facilitate the analysis of the dynamic motion during facial animations. PMID:23218511

  12. A new method for automatic tracking of facial landmarks in 3D motion captured images (4D).

    PubMed

    Al-Anezi, T; Khambay, B; Peng, M J; O'Leary, E; Ju, X; Ayoub, A

    2013-01-01

    The aim of this study was to validate the automatic tracking of facial landmarks in 3D image sequences. 32 subjects (16 males and 16 females) aged 18-35 years were recruited. 23 anthropometric landmarks were marked on the face of each subject with non-permanent ink using a 0.5mm pen. The subjects were asked to perform three facial animations (maximal smile, lip purse and cheek puff) from rest position. Each animation was captured by the 3D imaging system. A single operator manually digitised the landmarks on the 3D facial models and their locations were compared with those of the automatically tracked ones. To investigate the accuracy of manual digitisation, the operator re-digitised the same set of 3D images of 10 subjects (5 male and 5 female) at 1 month interval. The discrepancies in x, y and z coordinates between the 3D position of the manual digitised landmarks and that of the automatic tracked facial landmarks were within 0.17mm. The mean distance between the manually digitised and the automatically tracked landmarks using the tracking software was within 0.55 mm. The automatic tracking of facial landmarks demonstrated satisfactory accuracy which would facilitate the analysis of the dynamic motion during facial animations.

  13. 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.

  14. Basis Functions in Image Reconstruction From Projections: A Tutorial Introduction

    NASA Astrophysics Data System (ADS)

    Herman, Gabor T.

    2015-11-01

    The series expansion approaches to image reconstruction from projections assume that the object to be reconstructed can be represented as a linear combination of fixed basis functions and the task of the reconstruction algorithm is to estimate the coefficients in such a linear combination based on the measured projection data. It is demonstrated that using spherically symmetric basis functions (blobs), instead of ones based on the more traditional pixels, yields superior reconstructions of medically relevant objects. The demonstration uses simulated computerized tomography projection data of head cross-sections and the series expansion method ART for the reconstruction. In addition to showing the results of one anecdotal example, the relative efficacy of using pixel and blob basis functions in image reconstruction from projections is also evaluated using a statistical hypothesis testing based task oriented comparison methodology. The superiority of the efficacy of blob basis functions over that of pixel basis function is found to be statistically significant.

  15. Usefulness of four dimensional (4D) PET/CT imaging in the evaluation of thoracic lesions and in radiotherapy planning: Review of the literature.

    PubMed

    Sindoni, Alessandro; Minutoli, Fabio; Pontoriero, Antonio; Iatì, Giuseppe; Baldari, Sergio; Pergolizzi, Stefano

    2016-06-01

    In the past decade, Positron Emission Tomography (PET) has become a routinely used methodology for the assessment of solid tumors, which can detect functional abnormalities even before they become morphologically evident on conventional imaging. PET imaging has been reported to be useful in characterizing solitary pulmonary nodules, guiding biopsy, improving lung cancer staging, guiding therapy, monitoring treatment response and predicting outcome. This review focuses on the most relevant and recent literature findings, highlighting the current role of PET/CT and the evaluation of 4D-PET/CT modality for radiation therapy planning applications. Current evidence suggests that gross tumor volume delineation based on 4D-PET/CT information may be the best approach currently available for its delineation in thoracic cancers (lung and non-lung lesions). In our opinion, its use in this clinical setting is strongly encouraged, as it may improve patient treatment outcome in the setting of radiation therapy for cancers of the thoracic region, not only involving lung, but also lymph nodes and esophageal tissue. Literature results warrants further investigation in future prospective studies, especially in the setting of dose escalation. PMID:27133755

  16. 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

  17. Artificial neural network Radon inversion for image reconstruction.

    PubMed

    Rodriguez, A F; Blass, W E; Missimer, J H; Leenders, K L

    2001-04-01

    Image reconstruction techniques are essential to computer tomography. Algorithms such as filtered backprojection (FBP) or algebraic techniques are most frequently used. This paper presents an attempt to apply a feed-forward back-propagation supervised artificial neural network (BPN) to tomographic image reconstruction, specifically to positron emission tomography (PET). The main result is that the network trained with Gaussian test images proved to be successful at reconstructing images from projection sets derived from arbitrary objects. Additional results relate to the design of the network and the full width at half maximum (FWHM) of the Gaussians in the training sets. First, the optimal number of nodes in the middle layer is about an order of magnitude less than the number of input or output nodes. Second, the number of iterations required to achieve a required training set tolerance appeared to decrease exponentially with the number of nodes in the middle layer. Finally, for training sets containing Gaussians of a single width, the optimal accuracy of reconstructing the control set is obtained with a FWHM of three pixels. Intended to explore feasibility, the BPN presented in the following does not provide reconstruction accuracy adequate for immediate application to PET. However, the trained network does reconstruct general images independent of the data with which it was trained. Proposed in the concluding section are several possible refinements that should permit the development of a network capable of fast reconstruction of three-dimensional images from the discrete, noisy projection data characteristic of PET.

  18. MREJ: MRE elasticity reconstruction on ImageJ.

    PubMed

    Xiang, Kui; Zhu, Xia Li; Wang, Chang Xin; Li, Bing Nan

    2013-08-01

    Magnetic resonance elastography (MRE) is a promising method for health evaluation and disease diagnosis. It makes use of elastic waves as a virtual probe to quantify soft tissue elasticity. The wave actuator, imaging modality and elasticity interpreter are all essential components for an MRE system. Efforts have been made to develop more effective actuating mechanisms, imaging protocols and reconstructing algorithms. However, translating MRE wave images into soft tissue elasticity is a nontrivial issue for health professionals. This study contributes an open-source platform - MREJ - for MRE image processing and elasticity reconstruction. It is established on the widespread image-processing program ImageJ. Two algorithms for elasticity reconstruction were implemented with spatiotemporal directional filtering. The usability of the method is shown through virtual palpation on different phantoms and patients. Based on the results, we conclude that MREJ offers the MRE community a convenient and well-functioning program for image processing and elasticity interpretation.

  19. Sparsity-constrained PET image reconstruction with learned dictionaries

    NASA Astrophysics Data System (ADS)

    Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie

    2016-09-01

    PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.

  20. MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods

    PubMed Central

    Schmidt, Johannes F. M.; Santelli, Claudio; Kozerke, Sebastian

    2016-01-01

    An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods. PMID:27116675

  1. Sparsity-constrained PET image reconstruction with learned dictionaries.

    PubMed

    Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie

    2016-09-01

    PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging. PMID:27494441

  2. Surface reconstruction from microscopic images in optical lithography.

    PubMed

    Estellers, Virginia; Thiran, Jean-Philippe; Gabrani, Maria

    2014-08-01

    This paper presents a method to reconstruct 3D surfaces of silicon wafers from 2D images of printed circuits taken with a scanning electron microscope. Our reconstruction method combines the physical model of the optical acquisition system with prior knowledge about the shapes of the patterns in the circuit; the result is a shape-from-shading technique with a shape prior. The reconstruction of the surface is formulated as an optimization problem with an objective functional that combines a data-fidelity term on the microscopic image with two prior terms on the surface. The data term models the acquisition system through the irradiance equation characteristic of the microscope; the first prior is a smoothness penalty on the reconstructed surface, and the second prior constrains the shape of the surface to agree with the expected shape of the pattern in the circuit. In order to account for the variability of the manufacturing process, this second prior includes a deformation field that allows a nonlinear elastic deformation between the expected pattern and the reconstructed surface. As a result, the minimization problem has two unknowns, and the reconstruction method provides two outputs: 1) a reconstructed surface and 2) a deformation field. The reconstructed surface is derived from the shading observed in the image and the prior knowledge about the pattern in the circuit, while the deformation field produces a mapping between the expected shape and the reconstructed surface that provides a measure of deviation between the circuit design models and the real manufacturing process.

  3. Infrared Astronomical Satellite (IRAS) image reconstruction and restoration

    NASA Technical Reports Server (NTRS)

    Gonsalves, R. A.; Lyons, T. D.; Price, S. D.; Levan, P. D.; Aumann, H. H.

    1987-01-01

    IRAS sky mapping data is being reconstructed as images, and an entropy-based restoration algorithm is being applied in an attempt to improve spatial resolution in extended sources. Reconstruction requires interpolation of non-uniformly sampled data. Restoration is accomplished with an iterative algorithm which begins with an inverse filter solution and iterates on it with a weighted entropy-based spectral subtraction.

  4. 4D Imaging of Salt Precipitation during Evaporation from Saline Porous Media Influenced by the Particle Size Distribution

    NASA Astrophysics Data System (ADS)

    Norouzi Rad, M.; Shokri, N.

    2014-12-01

    Understanding the physics of water evaporation from saline porous media is important in many processes such as evaporation from porous media, vegetation, plant growth, biodiversity in soil, and durability of building materials. To investigate the effect of particle size distribution on the dynamics of salt precipitation in saline porous media during evaporation, we applied X-ray micro-tomography technique. Six samples of quartz sand with different grain size distributions were used in the present study enabling us to constrain the effects of particle and pore sizes on salt precipitation patterns and dynamics. The pore size distributions were computed using the pore-scale X-ray images. The packed beds were saturated with NaCl solution of 3 Molal and the X-ray imaging was continued for one day with temporal resolution of 30 min resulting in pore scale information about the evaporation and precipitation dynamics. Our results show more precipitation at the early stage of the evaporation in the case of sand with the larger particle size due to the presence of fewer evaporation sites at the surface. The presence of more preferential evaporation sites at the surface of finer sands significantly modified the patterns and thickness of the salt crust deposited on the surface such that a thinner salt crust was formed in the case of sand with smaller particle size covering larger area at the surface as opposed to the thicker patchy crusts in samples with larger particle sizes. Our results provide new insights regarding the physics of salt precipitation in porous media during evaporation.

  5. Improved Diffusion Imaging through SNR-Enhancing Joint Reconstruction

    PubMed Central

    Haldar, Justin P.; Wedeen, Van J.; Nezamzadeh, Marzieh; Dai, Guangping; Weiner, Michael W.; Schuff, Norbert; Liang, Zhi-Pei

    2012-01-01

    Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio (SNR) represent significant hurdles for many in vivo applications. This paper presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstruction method that takes advantage of the high level of structural correlation observed in typical datasets. Compared to existing denoising methods, the proposed method performs reconstruction directly from the measured complex k-space data, allowing for Gaussian noise modeling and theoretical characterizations of the resolution and SNR of the reconstructed images. In addition, the proposed method is compatible with many different models of the diffusion signal (e.g., diffusion tensor modeling, q-space modeling, etc.). The joint reconstruction method can provide significant improvements in SNR relative to conventional reconstruction techniques, with a relatively minor corresponding loss in image resolution. Results are shown in the context of diffusion spectrum imaging tractography and diffusion tensor imaging, illustrating the potential of this SNR-enhancing joint reconstruction approach for a range of different diffusion imaging experiments. PMID:22392528

  6. Cardiac function and perfusion dynamics measured on a beat-by-beat basis in the live mouse using ultra-fast 4D optoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Ford, Steven J.; Deán-Ben, Xosé L.; Razansky, Daniel

    2015-03-01

    The fast heart rate (~7 Hz) of the mouse makes cardiac imaging and functional analysis difficult when studying mouse models of cardiovascular disease, and cannot be done truly in real-time and 3D using established imaging modalities. Optoacoustic imaging, on the other hand, provides ultra-fast imaging at up to 50 volumetric frames per second, allowing for acquisition of several frames per mouse cardiac cycle. In this study, we combined a recently-developed 3D optoacoustic imaging array with novel analytical techniques to assess cardiac function and perfusion dynamics of the mouse heart at high, 4D spatiotemporal resolution. In brief, the heart of an anesthetized mouse was imaged over a series of multiple volumetric frames. In another experiment, an intravenous bolus of indocyanine green (ICG) was injected and its distribution was subsequently imaged in the heart. Unique temporal features of the cardiac cycle and ICG distribution profiles were used to segment the heart from background and to assess cardiac function. The 3D nature of the experimental data allowed for determination of cardiac volumes at ~7-8 frames per mouse cardiac cycle, providing important cardiac function parameters (e.g., stroke volume, ejection fraction) on a beat-by-beat basis, which has been previously unachieved by any other cardiac imaging modality. Furthermore, ICG distribution dynamics allowed for the determination of pulmonary transit time and thus additional quantitative measures of cardiovascular function. This work demonstrates the potential for optoacoustic cardiac imaging and is expected to have a major contribution toward future preclinical studies of animal models of cardiovascular health and disease.

  7. Image reconstruction in transcranial photoacoustic computed tomography of the brain

    NASA Astrophysics Data System (ADS)

    Mitsuhashi, Kenji; Wang, Lihong V.; Anastasio, Mark A.

    2015-03-01

    Photoacoustic computed tomography (PACT) holds great promise for transcranial brain imaging. However, the strong reflection, scattering, attenuation, and mode-conversion of photoacoustic waves in the skull pose serious challenges to establishing the method. The lack of an appropriate model of solid media in conventional PACT imaging models, which are based on the canonical scalar wave equation, causes a significant model mismatch in the presence of the skull and thus results in deteriorated reconstructed images. The goal of this study was to develop an image reconstruction algorithm that accurately models the skull and thereby ameliorates the quality of reconstructed images. The propagation of photoacoustic waves through the skull was modeled by a viscoelastic stress tensor wave equation, which was subsequently discretized by use of a staggered grid fourth-order finite-difference time-domain (FDTD) method. The matched adjoint of the FDTD-based wave propagation operator was derived for implementing a back-projection operator. Systematic computer simulations were conducted to demonstrate the effectiveness of the back-projection operator for reconstructing images in a realistic three-dimensional PACT brain imaging system. The results suggest that the proposed algorithm can successfully reconstruct images from transcranially-measured pressure data and readily be translated to clinical PACT brain imaging applications.

  8. Exponential filtering of singular values improves photoacoustic image reconstruction.

    PubMed

    Bhatt, Manish; Gutta, Sreedevi; Yalavarthy, Phaneendra K

    2016-09-01

    Model-based image reconstruction techniques yield better quantitative accuracy in photoacoustic image reconstruction. In this work, an exponential filtering of singular values was proposed for carrying out the image reconstruction in photoacoustic tomography. The results were compared with widely popular Tikhonov regularization, time reversal, and the state of the art least-squares QR-based reconstruction algorithms for three digital phantom cases with varying signal-to-noise ratios of data. It was shown that exponential filtering provides superior photoacoustic images of better quantitative accuracy. Moreover, the proposed filtering approach was observed to be less biased toward the regularization parameter and did not come with any additional computational burden as it was implemented within the Tikhonov filtering framework. It was also shown that the standard Tikhonov filtering becomes an approximation to the proposed exponential filtering. PMID:27607501

  9. Digital infrared thermal imaging following anterior cruciate ligament reconstruction.

    PubMed

    Barker, Lauren E; Markowski, Alycia M; Henneman, Kimberly

    2012-03-01

    This case describes the selective use of digital infrared thermal imaging for a 48-year-old woman who was being treated by a physical therapist following left anterior cruciate ligament (ACL) reconstruction with a semitendinosus autograft. PMID:22383168

  10. Online reconstruction of 3D magnetic particle imaging data

    NASA Astrophysics Data System (ADS)

    Knopp, T.; Hofmann, M.

    2016-06-01

    Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s‑1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.

  11. Online reconstruction of 3D magnetic particle imaging data

    NASA Astrophysics Data System (ADS)

    Knopp, T.; Hofmann, M.

    2016-06-01

    Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s-1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.

  12. Time-of-flight PET image reconstruction using origin ensembles.

    PubMed

    Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

    2015-03-01

    The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

  13. Advanced photoacoustic image reconstruction using the k-Wave toolbox

    NASA Astrophysics Data System (ADS)

    Treeby, B. E.; Jaros, J.; Cox, B. T.

    2016-03-01

    Reconstructing images from measured time domain signals is an essential step in tomography-mode photoacoustic imaging. However, in practice, there are many complicating factors that make it difficult to obtain high-resolution images. These include incomplete or undersampled data, filtering effects, acoustic and optical attenuation, and uncertainties in the material parameters. Here, the processing and image reconstruction steps routinely used by the Photoacoustic Imaging Group at University College London are discussed. These include correction for acoustic and optical attenuation, spatial resampling, material parameter selection, image reconstruction, and log compression. The effect of each of these steps is demonstrated using a representative in vivo dataset. All of the algorithms discussed form part of the open-source k-Wave toolbox (available from http://www.k-wave.org).

  14. Application of mathematical modelling methods for acoustic images reconstruction

    NASA Astrophysics Data System (ADS)

    Bolotina, I.; Kazazaeva, A.; Kvasnikov, K.; Kazazaev, A.

    2016-04-01

    The article considers the reconstruction of images by Synthetic Aperture Focusing Technique (SAFT). The work compares additive and multiplicative methods for processing signals received from antenna array. We have proven that the multiplicative method gives a better resolution. The study includes the estimation of beam trajectories for antenna arrays using analytical and numerical methods. We have shown that the analytical estimation method allows decreasing the image reconstruction time in case of linear antenna array implementation.

  15. Beyond maximum entropy: Fractal Pixon-based image reconstruction

    NASA Technical Reports Server (NTRS)

    Puetter, Richard C.; Pina, R. K.

    1994-01-01

    We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other competing methods, including Goodness-of-Fit methods such as Least-Squares fitting and Lucy-Richardson reconstruction, as well as Maximum Entropy (ME) methods such as those embodied in the MEMSYS algorithms. Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME. Our past work has shown how uniform information content pixons can be used to develop a 'Super-ME' method in which entropy is maximized exactly. Recently, however, we have developed a superior pixon basis for the image, the Fractal Pixon Basis (FPB). Unlike the Uniform Pixon Basis (UPB) of our 'Super-ME' method, the FPB basis is selected by employing fractal dimensional concepts to assess the inherent structure in the image. The Fractal Pixon Basis results in the best image reconstructions to date, superior to both UPB and the best ME reconstructions. In this paper, we review the theory of the UPB and FPB pixon and apply our methodology to the reconstruction of far-infrared imaging of the galaxy M51. The results of our reconstruction are compared to published reconstructions of the same data using the Lucy-Richardson algorithm, the Maximum Correlation Method developed at IPAC, and the MEMSYS ME algorithms. The results show that our reconstructed image has a spatial resolution a factor of two better than best previous methods (and a factor of 20 finer than the width of the point response function), and detects sources two orders of magnitude fainter than other methods.

  16. Super-Resolution Image Reconstruction Applied to Medical Ultrasound

    NASA Astrophysics Data System (ADS)

    Ellis, Michael

    Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in

  17. Reconstruction of images from radiofrequency electron paramagnetic resonance spectra.

    PubMed

    Smith, C M; Stevens, A D

    1994-12-01

    This paper discusses methods for obtaining image reconstructions from electron paramagnetic resonance (EPR) spectra which constitute object projections. An automatic baselining technique is described which treats each spectrum consistently; rotating the non-horizontal baselines which are caused by stray magnetic effects onto the horizontal axis. The convolved backprojection method is described for both two- and three-dimensional reconstruction and the effect of cut-off frequency on the reconstruction is illustrated. A slower, indirect, iterative method, which does a non-linear fit to the projection data, is shown to give a far smoother reconstructed image when the method of maximum entropy is used to determine the value of the final residual sum of squares. Although this requires more computing time than the convolved backprojection method, it is more flexible and overcomes the problem of numerical instability encountered in deconvolution. Images from phantom samples in vitro are discussed. The spectral data for these have been accumulated quickly and have a low signal-to-noise ratio. The results show that as few as 16 spectra can still be processed to give an image. Artifacts in the image due to a small number of projections using the convolved backprojection reconstruction method can be removed by applying a threshold, i.e. only plotting contours higher than a given value. These artifacts are not present in an image which has been reconstructed by the maximum entropy technique. At present these techniques are being applied directly to in vivo studies.

  18. Method for image reconstruction of moving radionuclide source distribution

    DOEpatents

    Stolin, Alexander V.; McKisson, John E.; Lee, Seung Joon; Smith, Mark Frederick

    2012-12-18

    A method for image reconstruction of moving radionuclide distributions. Its particular embodiment is for single photon emission computed tomography (SPECT) imaging of awake animals, though its techniques are general enough to be applied to other moving radionuclide distributions as well. The invention eliminates motion and blurring artifacts for image reconstructions of moving source distributions. This opens new avenues in the area of small animal brain imaging with radiotracers, which can now be performed without the perturbing influences of anesthesia or physical restraint on the biological system.

  19. Reconstruction Techniques for Sparse Multistatic Linear Array Microwave Imaging

    SciTech Connect

    Sheen, David M.; Hall, Thomas E.

    2014-06-09

    Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. In this paper, a sparse multi-static array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated and measured imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.

  20. Fuzzy-rule-based image reconstruction for positron emission tomography

    NASA Astrophysics Data System (ADS)

    Mondal, Partha P.; Rajan, K.

    2005-09-01

    Positron emission tomography (PET) and single-photon emission computed tomography have revolutionized the field of medicine and biology. Penalized iterative algorithms based on maximum a posteriori (MAP) estimation eliminate noisy artifacts by utilizing available prior information in the reconstruction process but often result in a blurring effect. MAP-based algorithms fail to determine the density class in the reconstructed image and hence penalize the pixels irrespective of the density class. Reconstruction with better edge information is often difficult because prior knowledge is not taken into account. The recently introduced median-root-prior (MRP)-based algorithm preserves the edges, but a steplike streaking effect is observed in the reconstructed image, which is undesirable. A fuzzy approach is proposed for modeling the nature of interpixel interaction in order to build an artifact-free edge-preserving reconstruction. The proposed algorithm consists of two elementary steps: (1) edge detection, in which fuzzy-rule-based derivatives are used for the detection of edges in the nearest neighborhood window (which is equivalent to recognizing nearby density classes), and (2) fuzzy smoothing, in which penalization is performed only for those pixels for which no edge is detected in the nearest neighborhood. Both of these operations are carried out iteratively until the image converges. Analysis shows that the proposed fuzzy-rule-based reconstruction algorithm is capable of producing qualitatively better reconstructed images than those reconstructed by MAP and MRP algorithms. The reconstructed images are sharper, with small features being better resolved owing to the nature of the fuzzy potential function.

  1. Image oscillation reduction and convergence acceleration for OSEM reconstruction

    SciTech Connect

    Huang, S.C.

    1999-06-01

    The authors have investigated the use of two approaches to reduce the image oscillation of OSEM reconstruction that is due to the inconsistencies among different partial subsets of the projection measurements (sinogram) when considering as a group. One approach pre-processes the sinogram to make it satisfy a sinogram consistency condition. The second approach takes the average of the intermediary images (i.e., smoothes image values over sub-iterations). Both approaches were found to be capable of reducing the image oscillation, and combination of both was most effective. With these approaches, the convergence of OSEM reconstruction is further improved. For computer simulated data and real PET data, a single iteration of these new OSEM reconstruction was shown to yield images comparable to those with 80 EM iterations.

  2. Compensation for air voids in photoacoustic computed tomography image reconstruction

    NASA Astrophysics Data System (ADS)

    Matthews, Thomas P.; Li, Lei; Wang, Lihong V.; Anastasio, Mark A.

    2016-03-01

    Most image reconstruction methods in photoacoustic computed tomography (PACT) assume that the acoustic properties of the object and the surrounding medium are homogeneous. This can lead to strong artifacts in the reconstructed images when there are significant variations in sound speed or density. Air voids represent a particular challenge due to the severity of the differences between the acoustic properties of air and water. In whole-body small animal imaging, the presence of air voids in the lungs, stomach, and gastrointestinal system can limit image quality over large regions of the object. Iterative reconstruction methods based on the photoacoustic wave equation can account for these acoustic variations, leading to improved resolution, improved contrast, and a reduction in the number of imaging artifacts. However, the strong acoustic heterogeneities can lead to instability or errors in the numerical wave solver. Here, the impact of air voids on PACT image reconstruction is investigated, and procedures for their compensation are proposed. The contributions of sound speed and density variations to the numerical stability of the wave solver are considered, and a novel approach for mitigating the impact of air voids while reducing the computational burden of image reconstruction is identified. These results are verified by application to an experimental phantom.

  3. 4D seismic to image a thin carbonate reservoir during a miscible C02 flood: Hall-Gurney Field, Kansas, USA

    USGS Publications Warehouse

    Raef, A.E.; Miller, R.D.; Franseen, E.K.; Byrnes, A.P.; Watney, W.L.; Harrison, W.E.

    2005-01-01

    The movement of miscible CO2 injected into a shallow (900 m) thin (3.6-6m) carbonate reservoir was monitored using the high-resolution parallel progressive blanking (PPB) approach. The approach concentrated on repeatability during acquisition and processing, and use of amplitude envelope 4D horizon attributes. Comparison of production data and reservoir simulations to seismic images provided a measure of the effectiveness of time-lapse (TL) to detect weak anomalies associated with changes in fluid concentration. Specifically, the method aided in the analysis of high-resolution data to distinguish subtle seismic characteristics and associated trends related to depositional lithofacies and geometries and structural elements of this carbonate reservoir that impact fluid character and EOR efforts.

  4. Geoaccurate three-dimensional reconstruction via image-based geometry

    NASA Astrophysics Data System (ADS)

    Walvoord, Derek J.; Rossi, Adam J.; Paul, Bradley D.; Brower, Bernie; Pellechia, Matthew F.

    2013-05-01

    Recent technological advances in computing capabilities and persistent surveillance systems have led to increased focus on new methods of exploiting geospatial data, bridging traditional photogrammetric techniques and state-of-the-art multiple view geometry methodology. The structure from motion (SfM) problem in Computer Vision addresses scene reconstruction from uncalibrated cameras, and several methods exist to remove the inherent projective ambiguity. However, the reconstruction remains in an arbitrary world coordinate frame without knowledge of its relationship to a xed earth-based coordinate system. This work presents a novel approach for obtaining geoaccurate image-based 3-dimensional reconstructions in the absence of ground control points by using a SfM framework and the full physical sensor model of the collection system. Absolute position and orientation information provided by the imaging platform can be used to reconstruct the scene in a xed world coordinate system. Rather than triangulating pixels from multiple image-to-ground functions, each with its own random error, the relative reconstruction is computed via image-based geometry, i.e., geometry derived from image feature correspondences. In other words, the geolocation accuracy is improved using the relative distances provided by the SfM reconstruction. Results from the Exelis Wide-Area Motion Imagery (WAMI) system are provided to discuss conclusions and areas for future work.

  5. Photo-consistency registration of a 4D cardiac motion model to endoscopic video for image guidance of robotic coronary artery bypass

    NASA Astrophysics Data System (ADS)

    Figl, Michael; Rueckert, Daniel; Edwards, Eddie

    2009-02-01

    The aim of the work described in this paper is registration of a 4D preoperative motion model of the heart to the video view of the patient through the intraoperative endoscope. The heart motion is cyclical and can be modelled using multiple reconstructions of cardiac gated coronary CT. We propose the use of photoconsistency between the two views through the da Vinci endoscope to align to the preoperative heart surface model from CT. The temporal alignment from the video to the CT model could in principle be obtained from the ECG signal. We propose averaging of the photoconsistency over the cardiac cycle to improve the registration compared to a single view. Though there is considerable motion of the heart, after correct temporal alignment we suggest that the remaining motion should be close to rigid. Results are presented for simulated renderings and for real video of a beating heart phantom. We found much smoother sections at the minimum when using multiple phases for the registration, furthermore convergence was found to be better when more phases are used.

  6. Model-based reconstruction for x-ray diffraction imaging

    NASA Astrophysics Data System (ADS)

    Sridhar, Venkatesh; Kisner, Sherman J.; Skatter, Sondre; Bouman, Charles A.

    2016-05-01

    In this paper, we propose a novel 4D model-based iterative reconstruction (MBIR) algorithm for low-angle scatter X-ray Diffraction (XRD) that can substantially increase the SNR. Our forward model is based on a Poisson photon counting model that incorporates a spatial point-spread function, detector energy response and energy-dependent attenuation correction. Our prior model uses a Markov random field (MRF) together with a reduced spectral bases set determined using non-negative matrix factorization. We demonstrate the effectiveness of our method with real data sets.

  7. Reconstruction of large, irregularly sampled multidimensional images. A tensor-based approach.

    PubMed

    Morozov, Oleksii Vyacheslav; Unser, Michael; Hunziker, Patrick

    2011-02-01

    Many practical applications require the reconstruction of images from irregularly sampled data. The spline formalism offers an attractive framework for solving this problem; the currently available methods, however, are hard to deploy for large-scale interpolation problems in dimensions greater than two (3-D, 3-D+time) because of an exponential increase of their computational cost (curse of dimensionality). Here, we revisit the standard regularized least-squares formulation of the interpolation problem, and propose to perform the reconstruction in a uniform tensor-product B-spline basis as an alternative to the classical solution involving radial basis functions. Our analysis reveals that the underlying multilinear system of equations admits a tensor decomposition with an extreme sparsity of its one dimensional components. We exploit this property for implementing a parallel, memory-efficient system solver. We show that the computational complexity of the proposed algorithm is essentially linear in the number of measurements and that its dependency on the number of dimensions is significantly less than that of the original sparse matrix-based implementation. The net benefit is a substantial reduction in memory requirement and operation count when compared to standard matrix-based algorithms, so that even 4-D problems with millions of samples become computationally feasible on desktop PCs in reasonable time. After validating the proposed algorithm in 3-D and 4-D, we apply it to a concrete imaging problem: the reconstruction of medical ultrasound images (3-D+time) from a large set of irregularly sampled measurements, acquired by a fast rotating ultrasound transducer.

  8. 4-D imaging of sub-second dynamics in pore-scale processes using real-time synchrotron X-ray tomography

    NASA Astrophysics Data System (ADS)

    Dobson, Katherine J.; Coban, Sophia B.; McDonald, Samuel A.; Walsh, Joanna N.; Atwood, Robert C.; Withers, Philip J.

    2016-07-01

    A variable volume flow cell has been integrated with state-of-the-art ultra-high-speed synchrotron X-ray tomography imaging. The combination allows the first real-time (sub-second) capture of dynamic pore (micron)-scale fluid transport processes in 4-D (3-D + time). With 3-D data volumes acquired at up to 20 Hz, we perform in situ experiments that capture high-frequency pore-scale dynamics in 5-25 mm diameter samples with voxel (3-D equivalent of a pixel) resolutions of 2.5 to 3.8 µm. The data are free from motion artefacts and can be spatially registered or collected in the same orientation, making them suitable for detailed quantitative analysis of the dynamic fluid distribution pathways and processes. The methods presented here are capable of capturing a wide range of high-frequency nonequilibrium pore-scale processes including wetting, dilution, mixing, and reaction phenomena, without sacrificing significant spatial resolution. As well as fast streaming (continuous acquisition) at 20 Hz, they also allow larger-scale and longer-term experimental runs to be sampled intermittently at lower frequency (time-lapse imaging), benefiting from fast image acquisition rates to prevent motion blur in highly dynamic systems. This marks a major technical breakthrough for quantification of high-frequency pore-scale processes: processes that are critical for developing and validating more accurate multiscale flow models through spatially and temporally heterogeneous pore networks.

  9. Integration of image/video understanding engine into 4D/RCS architecture for intelligent perception-based behavior of robots in real-world environments

    NASA Astrophysics Data System (ADS)

    Kuvich, Gary

    2004-10-01

    To be completely successful, robots need to have reliable perceptual systems that are similar to human vision. It is hard to use geometric operations for processing of natural images. Instead, the brain builds a relational network-symbolic structure of visual scene, using different clues to set up the relational order of surfaces and objects with respect to the observer and to each other. Feature, symbol, and predicate are equivalent in the biologically inspired Network-Symbolic systems. A linking mechanism binds these features/symbols into coherent structures, and image converts from a "raster" into a "vector" representation. View-based object recognition is a hard problem for traditional algorithms that directly match a primary view of an object to a model. In Network-Symbolic Models, the derived structure, not the primary view, is a subject for recognition. Such recognition is not affected by local changes and appearances of the object as seen from a set of similar views. Once built, the model of visual scene changes slower then local information in the visual buffer. It allows for disambiguating visual information and effective control of actions and navigation via incremental relational changes in visual buffer. Network-Symbolic models can be seamlessly integrated into the NIST 4D/RCS architecture and better interpret images/video for situation awareness, target recognition, navigation and actions.

  10. Influence of Iterative Reconstruction Algorithms on PET Image Resolution

    NASA Astrophysics Data System (ADS)

    Karpetas, G. E.; Michail, C. M.; Fountos, G. P.; Valais, I. G.; Nikolopoulos, D.; Kandarakis, I. S.; Panayiotakis, G. S.

    2015-09-01

    The aim of the present study was to assess image quality of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction. The simulated PET scanner was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the modulation transfer function (MTF). MTF curves were estimated from transverse reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL, the ordered subsets separable paraboloidal surrogate (OSSPS), the median root prior (MRP) and OSMAPOSL with quadratic prior, algorithms. OSMAPOSL reconstruction was assessed by using fixed subsets and various iterations, as well as by using various beta (hyper) parameter values. MTF values were found to increase with increasing iterations. MTF also improves by using lower beta values. The simulated PET evaluation method, based on the TLC plane source, can be useful in the resolution assessment of PET scanners.

  11. Image reconstruction in higher dimensions: myocardial perfusion imaging of tracer dynamics with cardiac motion due to deformation and respiration

    NASA Astrophysics Data System (ADS)

    Shrestha, Uttam M.; Seo, Youngho; Botvinick, Elias H.; Gullberg, Grant T.

    2015-11-01

    Myocardial perfusion imaging (MPI) using slow rotating large field of view cameras requires spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration. In vivo, MPI contains additional degrees of freedom involving unavoidable motion of the heart due to quasiperiodic beating and the effects of respiration, which can severely degrade the quality of the images. This work develops a technique for a single photon emission computed tomography (SPECT) that reconstructs the distribution of the radiotracer concentration in the myocardium using a tensor product of different sets of basis functions that approximately describe the spatiotemporal variation of the radiotracer concentration and the motion of the heart. In this study the temporal B-spline basis functions are chosen to reflect the dynamics of the radiotracer, while the intrinsic deformation and the extrinsic motion of the heart are described by a product of a discrete set of Gaussian basis functions. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it deforms due to cardiac beating, and is displaced due to respiratory motion. These results are compared with the conventional 4D-spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. The higher dimensional reconstruction method proposed here improves bias, yet the signal-to-noise ratio (SNR) decreases slightly due to redistribution of the counts over the cardiac-respiratory gates. Additionally, there is a trade-off between the number of gates and the number of projections per gate to achieve high contrast images.

  12. Image Reconstruction in Higher Dimensions: Myocardial Perfusion Imaging of Tracer Dynamics with Cardiac Motion Due to Deformation and Respiration

    PubMed Central

    Shrestha, Uttam M.; Seo, Youngho; Botvinick, Elias H.; Gullberg, Grant T.

    2015-01-01

    Myocardial perfusion imaging (MPI) using slow rotating large field of view cameras requires spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration. In vivo, MPI contains additional degrees of freedom involving unavoidable motion of the heart due to quasiperiodic beating and the effects of respiration, which can severely degrade the quality of the images. This work develops a technique for a single photon emission computed tomography (SPECT) that reconstructs the distribution of the radiotracer concentration in the myocardium using a tensor product of different sets of basis functions that approximately describe the spatiotemporal variation of the radiotracer concentration and the motion of the heart. In this study the temporal B-spline basis functions are chosen to reflect the dynamics of the radiotracer, while the intrinsic deformation and the extrinsic motion of the heart are described by a product of a discrete set of Gaussian basis functions. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it deforms due to cardiac beating, and is displaced due to respiratory motion. These results are compared with the conventional 4D-spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. The higher dimensional reconstruction method proposed here improves bias, yet the signal-to-noise ratio (SNR) decreases due to redistribution of the counts over the cardiac-respiratory gates. However, there is a trade-off between the number of gates and the number of projections per gate to achieve high contrast images. PMID:26450115

  13. Image reconstruction in higher dimensions: myocardial perfusion imaging of tracer dynamics with cardiac motion due to deformation and respiration

    DOE PAGES

    Shrestha, Uttam M.; Seo, Youngho; Botvinick, Elias H.; Gullberg, Grant T.

    2015-10-09

    Myocardial perfusion imaging (MPI) using slow rotating large field of view cameras requires spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration. In vivo, MPI contains additional degrees of freedom involving unavoidable motion of the heart due to quasiperiodic beating and the effects of respiration, which can severely degrade the quality of the images. This work develops a technique for a single photon emission computed tomography (SPECT) that reconstructs the distribution of the radiotracer concentration in the myocardium using a tensor product of different sets of basis functions that approximately describe the spatiotemporal variationmore » of the radiotracer concentration and the motion of the heart. In this study the temporal B-spline basis functions are chosen to reflect the dynamics of the radiotracer, while the intrinsic deformation and the extrinsic motion of the heart are described by a product of a discrete set of Gaussian basis functions. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it deforms due to cardiac beating, and is displaced due to respiratory motion. We find these results are compared with the conventional 4D-spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. The higher dimensional reconstruction method proposed here improves bias, yet the signal-to-noise ratio (SNR) decreases slightly due to redistribution of the counts over the cardiac-respiratory gates. Additionally, there is a trade-off between the number of gates and the number of projections per gate to achieve high contrast images.« less

  14. Image reconstruction in higher dimensions: myocardial perfusion imaging of tracer dynamics with cardiac motion due to deformation and respiration

    SciTech Connect

    Shrestha, Uttam M.; Seo, Youngho; Botvinick, Elias H.; Gullberg, Grant T.

    2015-10-09

    Myocardial perfusion imaging (MPI) using slow rotating large field of view cameras requires spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration. In vivo, MPI contains additional degrees of freedom involving unavoidable motion of the heart due to quasiperiodic beating and the effects of respiration, which can severely degrade the quality of the images. This work develops a technique for a single photon emission computed tomography (SPECT) that reconstructs the distribution of the radiotracer concentration in the myocardium using a tensor product of different sets of basis functions that approximately describe the spatiotemporal variation of the radiotracer concentration and the motion of the heart. In this study the temporal B-spline basis functions are chosen to reflect the dynamics of the radiotracer, while the intrinsic deformation and the extrinsic motion of the heart are described by a product of a discrete set of Gaussian basis functions. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it deforms due to cardiac beating, and is displaced due to respiratory motion. We find these results are compared with the conventional 4D-spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. The higher dimensional reconstruction method proposed here improves bias, yet the signal-to-noise ratio (SNR) decreases slightly due to redistribution of the counts over the cardiac-respiratory gates. Additionally, there is a trade-off between the number of gates and the number of projections per gate to achieve high contrast images.

  15. Image reconstruction in higher dimensions: myocardial perfusion imaging of tracer dynamics with cardiac motion due to deformation and respiration.

    PubMed

    Shrestha, Uttam M; Seo, Youngho; Botvinick, Elias H; Gullberg, Grant T

    2015-11-01

    Myocardial perfusion imaging (MPI) using slow rotating large field of view cameras requires spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration. In vivo, MPI contains additional degrees of freedom involving unavoidable motion of the heart due to quasiperiodic beating and the effects of respiration, which can severely degrade the quality of the images. This work develops a technique for a single photon emission computed tomography (SPECT) that reconstructs the distribution of the radiotracer concentration in the myocardium using a tensor product of different sets of basis functions that approximately describe the spatiotemporal variation of the radiotracer concentration and the motion of the heart. In this study the temporal B-spline basis functions are chosen to reflect the dynamics of the radiotracer, while the intrinsic deformation and the extrinsic motion of the heart are described by a product of a discrete set of Gaussian basis functions. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it deforms due to cardiac beating, and is displaced due to respiratory motion. These results are compared with the conventional 4D-spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. The higher dimensional reconstruction method proposed here improves bias, yet the signal-to-noise ratio (SNR) decreases slightly due to redistribution of the counts over the cardiac-respiratory gates. Additionally, there is a trade-off between the number of gates and the number of projections per gate to achieve high contrast images. PMID:26450115

  16. Probe and object function reconstruction in incoherent stem imaging

    SciTech Connect

    Nellist, P.D.; Pennycook, S.J.

    1996-09-01

    Using the phase-object approximation it is shown how an annular dark- field (ADF) detector in a scanning transmission electron microscope (STEM) leads to an image which can be described by an incoherent model. The point spread function is found to be simply the illuminating probe intensity. An important consequence of this is that there is no phase problem in the imaging process, which allows various image processing methods to be applied directly to the image intensity data. Using an image of a GaAs<110>, the probe intensity profile is reconstructed, confirming the existence of a 1.3 {Angstrom} probe in a 300kV STEM. It is shown that simply deconvolving this reconstructed probe from the image data does not improve its interpretability because the dominant effects of the imaging process arise simply from the restricted resolution of the microscope. However, use of the reconstructed probe in a maximum entropy reconstruction is demonstrated, which allows information beyond the resolution limit to be restored and does allow improved image interpretation.

  17. Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging

    PubMed Central

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar

    2015-01-01

    Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466

  18. Reconstruction of indoor scene from a single image

    NASA Astrophysics Data System (ADS)

    Wu, Di; Li, Hongyu; Zhang, Lin

    2015-03-01

    Given a single image of an indoor scene without any prior knowledge, is it possible for a computer to automatically reconstruct the structure of the scene? This letter proposes a reconstruction method, called RISSIM, to recover the 3D modelling of an indoor scene from a single image. The proposed method is composed of three steps: the estimation of vanishing points, the detection and classification of lines, and the plane mapping. To find vanishing points, a new feature descriptor, named "OCR", is defined to describe the texture orientation. With Phrase Congruency and Harris Detector, the line segments can be detected exactly, which is a prerequisite. Perspective transform is a defined as a reliable method whereby the points on the image can be represented on a 3D model. Experimental results show that the 3D structure of an indoor scene can be well reconstructed from a single image although the available depth information is limited.

  19. Fair-view image reconstruction with dual dictionaries.

    PubMed

    Lu, Yang; Zhao, Jun; Wang, Ge

    2012-01-01

    In this paper, we formulate the problem of computed tomography (CT)under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively.Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV.

  20. Few-view image reconstruction with dual dictionaries

    PubMed Central

    Lu, Yang; Zhao, Jun; Wang, Ge

    2011-01-01

    In this paper, we formulate the problem of computed tomography (CT) under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively. Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV. PMID:22155989

  1. Cervigram image segmentation based on reconstructive sparse representations

    NASA Astrophysics Data System (ADS)

    Zhang, Shaoting; Huang, Junzhou; Wang, Wei; Huang, Xiaolei; Metaxas, Dimitris

    2010-03-01

    We proposed an approach based on reconstructive sparse representations to segment tissues in optical images of the uterine cervix. Because of large variations in image appearance caused by the changing of the illumination and specular reflection, the color and texture features in optical images often overlap with each other and are not linearly separable. By leveraging sparse representations the data can be transformed to higher dimensions with sparse constraints and become more separated. K-SVD algorithm is employed to find sparse representations and corresponding dictionaries. The data can be reconstructed from its sparse representations and positive and/or negative dictionaries. Classification can be achieved based on comparing the reconstructive errors. In the experiments we applied our method to automatically segment the biomarker AcetoWhite (AW) regions in an archive of 60,000 images of the uterine cervix. Compared with other general methods, our approach showed lower space and time complexity and higher sensitivity.

  2. Bayesian image reconstruction for improving detection performance of muon tomography.

    PubMed

    Wang, Guobao; Schultz, Larry J; Qi, Jinyi

    2009-05-01

    Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

  3. High-resolution light field reconstruction using a hybrid imaging system.

    PubMed

    Wang, Xiang; Li, Lin; Hou, GuangQi

    2016-04-01

    Recently, light field cameras have drawn much attraction for their innovative performance in photographic and scientific applications. However, narrow baselines and constrained spatial resolution of current light field cameras impose restrictions on their usability. Therefore, we design a hybrid imaging system containing a light field camera and a high-resolution digital single lens reflex camera, and these two kinds of cameras share the same optical path with a beam splitter so as to achieve the reconstruction of high-resolution light fields. The high-resolution 4D light fields are reconstructed with a phase-based perspective variation strategy. First, we apply complex steerable pyramid decomposition on the high-resolution image from the digital single lens reflex camera. Then, we perform phase-based perspective-shift processing with the disparity value, which is extracted from the upsampled light field depth map, to create high-resolution synthetic light field images. High-resolution digital refocused images and high-resolution depth maps can be generated in this way. Furthermore, controlling the magnitude of the perspective shift enables us to change the depth of field rendering in the digital refocused images. We show several experimental results to demonstrate the effectiveness of our approach.

  4. Scalar wave-optical reconstruction of plenoptic camera images.

    PubMed

    Junker, André; Stenau, Tim; Brenner, Karl-Heinz

    2014-09-01

    We investigate the reconstruction of plenoptic camera images in a scalar wave-optical framework. Previous publications relating to this topic numerically simulate light propagation on the basis of ray tracing. However, due to continuing miniaturization of hardware components it can be assumed that in combination with low-aperture optical systems this technique may not be generally valid. Therefore, we study the differences between ray- and wave-optical object reconstructions of true plenoptic camera images. For this purpose we present a wave-optical reconstruction algorithm, which can be run on a regular computer. Our findings show that a wave-optical treatment is capable of increasing the detail resolution of reconstructed objects.

  5. Tomographic mesh generation for OSEM reconstruction of SPECT images

    NASA Astrophysics Data System (ADS)

    Lu, Yao; Yu, Bo; Vogelsang, Levon; Krol, Andrzej; Xu, Yuesheng; Hu, Xiaofei; Feiglin, David

    2009-02-01

    To improve quality of OSEM SPECT reconstruction in the mesh domain, we implemented an adaptive mesh generation method that produces tomographic mesh consisting of triangular elements with size and density commensurate with geometric detail of the objects. Node density and element size change smoothly as a function of distance from the edges and edge curvature without creation of 'bad' elements. Tomographic performance of mesh-based OSEM reconstruction is controlled by the tomographic mesh structure, i.e. node density distribution, which in turn is ruled by the number of key points on the boundaries. A greedy algorithm is used to influence the distribution of nodes on the boundaries. The relationship between tomographic mesh properties and OSEM reconstruction quality has been investigated. We conclude that by selecting adequate number of key points, one can produce a tomographic mesh with lowest number of nodes that is sufficient to provide desired quality of reconstructed images, appropriate for the imaging system properties.

  6. Prospective regularization design in prior-image-based reconstruction.

    PubMed

    Dang, Hao; Siewerdsen, Jeffrey H; Stayman, J Webster

    2015-12-21

    Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in

  7. Prospective regularization design in prior-image-based reconstruction

    NASA Astrophysics Data System (ADS)

    Dang, Hao; Siewerdsen, Jeffrey H.; Webster Stayman, J.

    2015-12-01

    Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in

  8. Three-dimensional image reconstruction for electrical impedance tomography.

    PubMed

    Kleinermann, F; Avis, N J; Judah, S K; Barber, D C

    1996-11-01

    Very little work has been conducted on three-dimensional aspects of electrical impedance tomography (EIT), partly due to the increased computational complexity over the two-dimensional aspects of EIT. Nevertheless, extending EIT to three-dimensional data acquisition and image reconstruction may afford significant advantages such as an increase in the size of the independent data set and improved spatial resolution. However, considerable challenges are associated with the software aspects of three-dimensional EIT systems due to the requirement for accurate three-dimensional forward problem modelling and the derivation of three-dimensional image reconstruction algorithms. This paper outlines the work performed to date to derive a three-dimensional image reconstruction algorithm for EIT based on the inversion of the sensitivity matrix approach for a finite right circular cylinder. A comparison in terms of the singular-value spectra and the singular vectors between the sensitivity matrices for a three-dimensional cylinder and a two-dimensional disc has been performed. This comparison shows that the three-dimensional image reconstruction algorithm recruits more central information at lower condition numbers than the two-dimensional image reconstruction algorithm.

  9. An adaptive filtered back-projection for photoacoustic image reconstruction

    SciTech Connect

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-05-15

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  10. An adaptive filtered back-projection for photoacoustic image reconstruction

    PubMed Central

    Huang, He; Bustamante, Gilbert; Peterson, Ralph; Ye, Jing Yong

    2015-01-01

    Purpose: The purpose of this study is to develop an improved filtered-back-projection (FBP) algorithm for photoacoustic tomography (PAT), which allows image reconstruction with higher quality compared to images reconstructed through traditional algorithms. Methods: A rigorous expression of a weighting function has been derived directly from a photoacoustic wave equation and used as a ramp filter in Fourier domain. The authors’ new algorithm utilizes this weighting function to precisely calculate each photoacoustic signal’s contribution and then reconstructs the image based on the retarded potential generated from the photoacoustic sources. In addition, an adaptive criterion has been derived for selecting the cutoff frequency of a low pass filter. Two computational phantoms were created to test the algorithm. The first phantom contained five spheres with each sphere having different absorbances. The phantom was used to test the capability for correctly representing both the geometry and the relative absorbed energy in a planar measurement system. The authors also used another phantom containing absorbers of different sizes with overlapping geometry to evaluate the performance of the new method for complicated geometry. In addition, random noise background was added to the simulated data, which were obtained by using an arc-shaped array of 50 evenly distributed transducers that spanned 160° over a circle with a radius of 65 mm. A normalized factor between the neighbored transducers was applied for correcting measurement signals in PAT simulations. The authors assumed that the scanned object was mounted on a holder that rotated over the full 360° and the scans were set to a sampling rate of 20.48 MHz. Results: The authors have obtained reconstructed images of the computerized phantoms by utilizing the new FBP algorithm. From the reconstructed image of the first phantom, one can see that this new approach allows not only obtaining a sharp image but also showing

  11. Beyond maximum entropy: Fractal pixon-based image reconstruction

    NASA Technical Reports Server (NTRS)

    Puetter, R. C.; Pina, R. K.

    1994-01-01

    We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other methods, including Goodness-of-Fit (e.g. Least-Squares and Lucy-Richardson) and Maximum Entropy (ME). Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME.

  12. Reconstruction of electrostatic force microscopy images

    NASA Astrophysics Data System (ADS)

    Strassburg, E.; Boag, A.; Rosenwaks, Y.

    2005-08-01

    An efficient algorithm to restore the actual surface potential image from Kelvin probe force microscopy measurements of semiconductors is presented. The three-dimensional potential of the tip-sample system is calculated using an integral equation-based boundary element method combined with modeling the semiconductor by an equivalent dipole-layer and image-charge model. The derived point spread function of the measuring tip is then used to restore the actual surface potential from the measured image, using noise filtration and deconvolution algorithms. The model is then used to restore high-resolution Kelvin probe microscopy images of semiconductor surfaces.

  13. Optimization and image quality assessment of the alpha-image reconstruction algorithm: iterative reconstruction with well-defined image quality metrics

    NASA Astrophysics Data System (ADS)

    Lebedev, Sergej; Sawall, Stefan; Kuchenbecker, Stefan; Faby, Sebastian; Knaup, Michael; Kachelrieß, Marc

    2015-03-01

    The reconstruction of CT images with low noise and highest spatial resolution is a challenging task. Usually, a trade-off between at least these two demands has to be found or several reconstructions with mutually exclusive properties, i.e. either low noise or high spatial resolution, have to be performed. Iterative reconstruction methods might be suitable tools to overcome these limitations and provide images of highest diagnostic quality with formerly mutually exclusive image properties. While image quality metrics like the modulation transfer function (MTF) or the point spread function (PSF) are well-defined in case of standard reconstructions, e.g. filtered backprojection, the iterative algorithms lack these metrics. To overcome this issue alternate methodologies like the model observers have been proposed recently to allow a quantification of a usually task-dependent image quality metric.1 As an alternative we recently proposed an iterative reconstruction method, the alpha-image reconstruction (AIR), providing well-defined image quality metrics on a per-voxel basis.2 In particular, the AIR algorithm seeks to find weighting images, the alpha-images, that are used to blend between basis images with mutually exclusive image properties. The result is an image with highest diagnostic quality that provides a high spatial resolution and a low noise level. As the estimation of the alpha-images is computationally demanding we herein aim at optimizing this process and highlight the favorable properties of AIR using patient measurements.

  14. Respiratory motion correction in emission tomography image reconstruction.

    PubMed

    Reyes, Mauricio; Malandain, Grégoire; Koulibaly, Pierre Malick; González Ballester, Miguel A; Darcourt, Jacques

    2005-01-01

    In Emission Tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations and imprecise diagnosis. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested with improvements over the spatial activity distribution in lungs lesions, but with the disadvantages of requiring additional instrumentation or discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion correction directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the Maximum Likelihood Expectation Maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.

  15. Image Reconstruction for a Partially Collimated Whole Body PET Scanner.

    PubMed

    Alessio, Adam M; Schmitz, Ruth E; Macdonald, Lawrence R; Wollenweber, Scott D; Stearns, Charles W; Ross, Steven G; Ganin, Alex; Lewellen, Thomas K; Kinahan, Paul E

    2008-06-01

    Partially collimated PET systems have less collimation than conventional 2-D systems and have been shown to offer count rate improvements over 2-D and 3-D systems. Despite this potential, previous efforts have not established image-based improvements with partial collimation and have not customized the reconstruction method for partially collimated data. This work presents an image reconstruction method tailored for partially collimated data. Simulated and measured sensitivity patterns are presented and provide a basis for modification of a fully 3-D reconstruction technique. The proposed method uses a measured normalization correction term to account for the unique sensitivity to true events. This work also proposes a modified scatter correction based on simulated data. Measured image quality data supports the use of the normalization correction term for true events, and suggests that the modified scatter correction is unnecessary.

  16. Sparse representation for the ISAR image reconstruction

    NASA Astrophysics Data System (ADS)

    Hu, Mengqi; Montalbo, John; Li, Shuxia; Sun, Ligang; Qiao, Zhijun G.

    2016-05-01

    In this paper, a sparse representation of the data for an inverse synthetic aperture radar (ISAR) system is provided in two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization that recovers the image with far less samples, which is required by Nyquist-Shannon sampling theorem to increases the efficiency and decrease the cost of calculation in radar imaging.

  17. Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU

    PubMed Central

    Arefan, D.; Talebpour, A.; Ahmadinejhad, N.; Kamali Asl, A.

    2015-01-01

    Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU). At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU) card and the Graphics Processing Unit (GPU). It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU). PMID:26171373

  18. 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.

  19. 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

    Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast

  20. Local fingerprint image reconstruction based on gabor filtering

    NASA Astrophysics Data System (ADS)

    Bakhtiari, Somayeh; Agaian, Sos S.; Jamshidi, Mo

    2012-06-01

    In this paper, we propose two solutions for fingerprint local image reconstruction based on Gabor filtering. Gabor filtering is a popular method for fingerprint image enhancement. However, the reliability of the information in the output image suffers, when the input image has a poor quality. This is the result of the spurious estimates of frequency and orientation by classical approaches, particularly in the scratch regions. In both techniques of this paper, the scratch marks are recognized initially using reliability image which is calculated using the gradient images. The first algorithm is based on an inpainting technique and the second method employs two different kernels for the scratch and the non-scratch parts of the image to calculate the gradient images. The simulation results show that both approaches allow the actual information of the image to be preserved while connecting discontinuities correctly by approximating the orientation matrix more genuinely.

  1. A rapid reconstruction algorithm for three-dimensional scanning images

    NASA Astrophysics Data System (ADS)

    Xiang, Jiying; Wu, Zhen; Zhang, Ping; Huang, Dexiu

    1998-04-01

    A `simulated fluorescence' three-dimensional reconstruction algorithm, which is especially suitable for confocal images of partial transparent biological samples, is proposed in this paper. To make the retina projection of the object reappear and to avoid excessive memory consumption, the original image is rotated and compressed before the processing. A left image and a right image are mixed by different colors to increase the sense of stereo. The details originally hidden in deep layers are well exhibited with the aid of an `auxiliary directional source'. In addition, the time consumption is greatly reduced compared with conventional methods such as `ray tracing'. The realization of the algorithm is interpreted by a group of reconstructed images.

  2. Feasibility of quantitative lung perfusion by 4D CT imaging by a new dynamic-scanning protocol in an animal model

    NASA Astrophysics Data System (ADS)

    Wang, Yang; Goldin, Jonathan G.; Abtin, Fereidoun G.; Brown, Matt; McNitt-Gray, Mike

    2008-03-01

    The purpose of this study is to test a new dynamic Perfusion-CT imaging protocol in an animal model and investigate the feasibility of quantifying perfusion of lung parenchyma to perform functional analysis from 4D CT image data. A novel perfusion-CT protocol was designed with 25 scanning time points: the first at baseline and 24 scans after a bolus injection of contrast material. Post-contrast CT scanning images were acquired with a high sampling rate before the first blood recirculation and then a relatively low sampling rate until 10 minutes after administrating contrast agent. Lower radiation techniques were used to keep the radiation dose to an acceptable level. 2 Yorkshire swine with pulmonary emboli underwent this perfusion- CT protocol at suspended end inspiration. The software tools were designed to measure the quantitative perfusion parameters (perfusion, permeability, relative blood volume, blood flow, wash-in & wash-out enhancement) of voxel or interesting area of lung. The perfusion values were calculated for further lung functional analysis and presented visually as contrast enhancement maps for the volume being examined. The results show increased CT temporal sampling rate provides the feasibility of quantifying lung function and evaluating the pulmonary emboli. Differences between areas with known perfusion defects and those without perfusion defects were observed. In conclusion, the techniques to calculate the lung perfusion on animal model have potential application in human lung functional analysis such as evaluation of functional effects of pulmonary embolism. With further study, these techniques might be applicable in human lung parenchyma characterization and possibly for lung nodule characterization.

  3. A methodology to event reconstruction from trace images.

    PubMed

    Milliet, Quentin; Delémont, Olivier; Sapin, Eric; Margot, Pierre

    2015-03-01

    The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally

  4. Dictionary Approaches to Image Compression and Reconstruction

    NASA Technical Reports Server (NTRS)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1998-01-01

    This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

  5. Dictionary Approaches to Image Compression and Reconstruction

    NASA Technical Reports Server (NTRS)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1998-01-01

    This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as lambda, are discrete time signals, where y represents the dictionary index. A dictionary with a collection of these waveforms Is typically complete or over complete. Given such a dictionary, the goal is to obtain a representation Image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

  6. Joint model of motion and anatomy for PET image reconstruction

    SciTech Connect

    Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama

    2007-12-15

    Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem.

  7. Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.

    PubMed

    Fromm, S A; Sachse, C

    2016-01-01

    Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method.

  8. Penalized maximum-likelihood image reconstruction for lesion detection

    NASA Astrophysics Data System (ADS)

    Qi, Jinyi; Huesman, Ronald H.

    2006-08-01

    Detecting cancerous lesions is one major application in emission tomography. In this paper, we study penalized maximum-likelihood image reconstruction for this important clinical task. Compared to analytical reconstruction methods, statistical approaches can improve the image quality by accurately modelling the photon detection process and measurement noise in imaging systems. To explore the full potential of penalized maximum-likelihood image reconstruction for lesion detection, we derived simplified theoretical expressions that allow fast evaluation of the detectability of a random lesion. The theoretical results are used to design the regularization parameters to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the proposed penalty function, conventional penalty function, and a penalty function for isotropic point spread function. The lesion detectability is measured by a channelized Hotelling observer. The results show that the proposed penalty function outperforms the other penalty functions for lesion detection. The relative improvement is dependent on the size of the lesion. However, we found that the penalty function optimized for a 5 mm lesion still outperforms the other two penalty functions for detecting a 14 mm lesion. Therefore, it is feasible to use the penalty function designed for small lesions in image reconstruction, because detection of large lesions is relatively easy.

  9. Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.

    PubMed

    Fromm, S A; Sachse, C

    2016-01-01

    Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. PMID:27572732

  10. Compressed/reconstructed test images for CRAF/Cassini

    NASA Technical Reports Server (NTRS)

    Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.

    1991-01-01

    A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.

  11. Gadgetron: an open source framework for medical image reconstruction.

    PubMed

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-06-01

    This work presents a new open source framework for medical image reconstruction called the "Gadgetron." The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or "Gadgets" from raw data to reconstructed images. The data processing pipeline is configured dynamically at run-time based on an extensible markup language configuration description. The framework promotes reuse and sharing of reconstruction modules and new Gadgets can be added to the Gadgetron framework through a plugin-like architecture without recompiling the basic framework infrastructure. Gadgets are typically implemented in C/C++, but the framework includes wrapper Gadgets that allow the user to implement new modules in the Python scripting language for rapid prototyping. In addition to the streaming framework infrastructure, the Gadgetron comes with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its application to Cartesian and non-Cartesian parallel magnetic resonance imaging.

  12. Coronary x-ray angiographic reconstruction and image orientation

    SciTech Connect

    Sprague, Kevin; Drangova, Maria; Lehmann, Glen

    2006-03-15

    We have developed an interactive geometric method for 3D reconstruction of the coronary arteries using multiple single-plane angiographic views with arbitrary orientations. Epipolar planes and epipolar lines are employed to trace corresponding vessel segments on these views. These points are utilized to reconstruct 3D vessel centerlines. The accuracy of the reconstruction is assessed using: (1) near-intersection distances of the rays that connect x-ray sources with projected points, (2) distances between traced and projected centerlines. These same two measures enter into a fitness function for a genetic search algorithm (GA) employed to orient the angiographic image planes automatically in 3D avoiding local minima in the search for optimized parameters. Furthermore, the GA utilizes traced vessel shapes (as opposed to isolated anchor points) to assist the optimization process. Differences between two-view and multiview reconstructions are evaluated. Vessel radii are measured and used to render the coronary tree in 3D as a surface. Reconstruction fidelity is demonstrated via (1) virtual phantom, (2) real phantom, and (3) patient data sets, the latter two of which utilize the GA. These simulated and measured angiograms illustrate that the vessel centerlines are reconstructed in 3D with accuracy below 1 mm. The reconstruction method is thus accurate compared to typical vessel dimensions of 1-3 mm. The methods presented should enable a combined interpretation of the severity of coronary artery stenoses and the hemodynamic impact on myocardial perfusion in patients with coronary artery disease.

  13. Coronary x-ray angiographic reconstruction and image orientation.

    PubMed

    Sprague, Kevin; Drangova, Maria; Lehmann, Glen; Slomka, Piotr; Levin, David; Chow, Benjamin; deKemp, Robert

    2006-03-01

    We have developed an interactive geometric method for 3D reconstruction of the coronary arteries using multiple single-plane angiographic views with arbitrary orientations. Epipolar planes and epipolar lines are employed to trace corresponding vessel segments on these views. These points are utilized to reconstruct 3D vessel centerlines. The accuracy of the reconstruction is assessed using: (1) near-intersection distances of the rays that connect x-ray sources with projected points, (2) distances between traced and projected centerlines. These same two measures enter into a fitness function for a genetic search algorithm (GA) employed to orient the angiographic image planes automatically in 3D avoiding local minima in the search for optimized parameters. Furthermore, the GA utilizes traced vessel shapes (as opposed to isolated anchor points) to assist the optimization process. Differences between two-view and multiview reconstructions are evaluated. Vessel radii are measured and used to render the coronary tree in 3D as a surface. Reconstruction fidelity is demonstrated via (1) virtual phantom, (2) real phantom, and (3) patient data sets, the latter two of which utilize the GA. These simulated and measured angiograms illustrate that the vessel center-lines are reconstructed in 3D with accuracy below 1 mm. The reconstruction method is thus accurate compared to typical vessel dimensions of 1-3 mm. The methods presented should enable a combined interpretation of the severity of coronary artery stenoses and the hemodynamic impact on myocardial perfusion in patients with coronary artery disease.

  14. Diffractive centrosymmetric 3D-transmission phase gratings positioned at the image plane of optical systems transform lightlike 4D-WORLD as tunable resonators into spectral metrics...

    NASA Astrophysics Data System (ADS)

    Lauinger, Norbert

    1999-08-01

    Diffractive 3D phase gratings of spherical scatterers dense in hexagonal packing geometry represent adaptively tunable 4D-spatiotemporal filters with trichromatic resonance in visible spectrum. They are described in the (lambda) - chromatic and the reciprocal (nu) -aspects by reciprocal geometric translations of the lightlike Pythagoras theorem, and by the direction cosine for double cones. The most elementary resonance condition in the lightlike Pythagoras theorem is given by the transformation of the grating constants gx, gy, gz of the hexagonal 3D grating to (lambda) h1h2h3 equals (lambda) 111 with cos (alpha) equals 0.5. Through normalization of the chromaticity in the von Laue-interferences to (lambda) 111, the (nu) (lambda) equals (lambda) h1h2h3/(lambda) 111-factor of phase velocity becomes the crucial resonance factor, the 'regulating device' of the spatiotemporal interaction between 3D grating and light, space and time. In the reciprocal space equal/unequal weights and times in spectral metrics result at positions of interference maxima defined by hyperbolas and circles. A database becomes built up by optical interference for trichromatic image preprocessing, motion detection in vector space, multiple range data analysis, patchwide multiple correlations in the spatial frequency spectrum, etc.

  15. Enhanced Optoelectronic Performance of a Passivated Nanowire-Based Device: Key Information from Real-Space Imaging Using 4D Electron Microscopy.

    PubMed

    Khan, Jafar I; Adhikari, Aniruddha; Sun, Jingya; Priante, Davide; Bose, Riya; Shaheen, Basamat S; Ng, Tien Khee; Zhao, Chao; Bakr, Osman M; Ooi, Boon S; Mohammed, Omar F

    2016-05-01

    Managing trap states and understanding their role in ultrafast charge-carrier dynamics, particularly at surface and interfaces, remains a major bottleneck preventing further advancements and commercial exploitation of nanowire (NW)-based devices. A key challenge is to selectively map such ultrafast dynamical processes on the surfaces of NWs, a capability so far out of reach of time-resolved laser techniques. Selective mapping of surface dynamics in real space and time can only be achieved by applying four-dimensional scanning ultrafast electron microscopy (4D S-UEM). Charge carrier dynamics are spatially and temporally visualized on the surface of InGaN NW arrays before and after surface passivation with octadecylthiol (ODT). The time-resolved secondary electron images clearly demonstrate that carrier recombination on the NW surface is significantly slowed down after ODT treatment. This observation is fully supported by enhancement of the performance of the light emitting device. Direct observation of surface dynamics provides a profound understanding of the photophysical mechanisms on materials' surfaces and enables the formulation of effective surface trap state management strategies for the next generation of high-performance NW-based optoelectronic devices. PMID:26938476

  16. Principles of MR image formation and reconstruction.

    PubMed

    Duerk, J L

    1999-11-01

    This article describes a number of concepts that provide insights into the process of MR imaging. The use of shaped, fixed-bandwidth RF pulses and magnetic field gradients is described to provide an understanding of the methods used for slice selection. Variations in the slice-excitation profile are shown as a function of the RF pulse shape used, the truncation method used, and the tip angle. It should be remembered that although the goal is to obtain uniform excitation across the slice, this goal is never achieved in practice, thus necessitating the use of slice gaps in some cases. Excitation, refocusing, and inversion pulses are described. Excitation pulses nutate the spins from the longitudinal axis into the transverse plane, where their magnetization can be detected. Refocusing pulses are used to flip the magnetization through 180 degrees once it is in the transverse plane, so that the influence of magnetic field inhomogeneities is eliminated. Inversion pulses are used to flip the magnetization from the +z to the -z direction in invesrsion-recovery sequences. Radiofrequency pulses can also be used to eliminate either fat or water protons from the images because of the small differences in resonant frequency between these two types of protons. Selective methods based on chemical shift and binomial methods are described. Once the desired magnetization has been tipped into the transverse plane by the slice-selection process, two imaging axes remain to be spatially encoded. One axis is easily encoded by the application of a second magnetic field gradient that establishes a one-to-one mapping between position and frequency during the time that the signal is converted from analog to digital sampling. This frequency-encoding gradient is used in combination with the Fourier transform to determine the location of the precessing magnetization. The second image axis is encoded by a process known as phase encoding. The collected data can be described as the 2D Fourier

  17. Reconstruction techniques for sparse multistatic linear array microwave imaging

    NASA Astrophysics Data System (ADS)

    Sheen, David M.; Hall, Thomas E.

    2014-06-01

    Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. The Pacific Northwest National Laboratory (PNNL) has developed this technology for several applications including concealed weapon detection, groundpenetrating radar, and non-destructive inspection and evaluation. These techniques form three-dimensional images by scanning a diverging beam swept frequency transceiver over a two-dimensional aperture and mathematically focusing or reconstructing the data into three-dimensional images. Recently, a sparse multi-static array technology has been developed that reduces the number of antennas required to densely sample the linear array axis of the spatial aperture. This allows a significant reduction in cost and complexity of the linear-array-based imaging system. The sparse array has been specifically designed to be compatible with Fourier-Transform-based image reconstruction techniques; however, there are limitations to the use of these techniques, especially for extreme near-field operation. In the extreme near-field of the array, back-projection techniques have been developed that account for the exact location of each transmitter and receiver in the linear array and the 3-D image location. In this paper, the sparse array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.

  18. Optimisation techniques for digital image reconstruction from their projections

    NASA Astrophysics Data System (ADS)

    Durrani, T. S.; Goutis, C. E.

    1980-09-01

    A method is proposed for the digital reconstruction of images from their projections based on optimizing specified performance criteria. The reconstruction problem is embedded into the framework of constrained optimization and its solution is shown to lead to a relationship between the image and the one-dimensional Lagrange functions associated with each cost criterion. Two types of geometries (the parallel-beam and fan-beam systems) are considered for the acquisition of projection data and the constrained-optimization problem is solved for both. The ensuing algorithms allow the reconstruction of multidimensional objects from one-dimensional functions only. For digital data a fast reconstruction algorithm is proposed which exploits the symmetries inherent in both a circular domain of image reconstruction and in projections obtained at equispaced angles. Computational complexity is significantly reduced by the use of fast-Fourier-transform techniques, as the underlying relationship between the available projection data and the associated Lagrange multipliers is shown to possess a block circulant matrix structure.

  19. 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.

  20. Improved satellite image compression and reconstruction via genetic algorithms

    NASA Astrophysics Data System (ADS)

    Babb, Brendan; Moore, Frank; Peterson, Michael; Lamont, Gary

    2008-10-01

    A wide variety of signal and image processing applications, including the US Federal Bureau of Investigation's fingerprint compression standard [3] and the JPEG-2000 image compression standard [26], utilize wavelets. This paper describes new research that demonstrates how a genetic algorithm (GA) may be used to evolve transforms that outperform wavelets for satellite image compression and reconstruction under conditions subject to quantization error. The new approach builds upon prior work by simultaneously evolving real-valued coefficients representing matched forward and inverse transform pairs at each of three levels of a multi-resolution analysis (MRA) transform. The training data for this investigation consists of actual satellite photographs of strategic urban areas. Test results show that a dramatic reduction in the error present in reconstructed satellite images may be achieved without sacrificing the compression capabilities of the forward transform. The transforms evolved during this research outperform previous start-of-the-art solutions, which optimized coefficients for the reconstruction transform only. These transforms also outperform wavelets, reducing error by more than 0.76 dB at a quantization level of 64. In addition, transforms trained using representative satellite images do not perform quite as well when subsequently tested against images from other classes (such as fingerprints or portraits). This result suggests that the GA developed for this research is automatically learning to exploit specific attributes common to the class of images represented in the training population.

  1. Brain tissue segmentation in 4D CT using voxel classification

    NASA Astrophysics Data System (ADS)

    van den Boom, R.; Oei, M. T. H.; Lafebre, S.; Oostveen, L. J.; Meijer, F. J. A.; Steens, S. C. A.; Prokop, M.; van Ginneken, B.; Manniesing, R.

    2012-02-01

    A method is proposed to segment anatomical regions of the brain from 4D computer tomography (CT) patient data. The method consists of a three step voxel classification scheme, each step focusing on structures that are increasingly difficult to segment. The first step classifies air and bone, the second step classifies vessels and the third step classifies white matter, gray matter and cerebrospinal fluid. As features the time averaged intensity value and the temporal intensity change value were used. In each step, a k-Nearest-Neighbor classifier was used to classify the voxels. Training data was obtained by placing regions of interest in reconstructed 3D image data. The method has been applied to ten 4D CT cerebral patient data. A leave-one-out experiment showed consistent and accurate segmentation results.

  2. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    PubMed

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  3. Actively triggered 4d cone-beam CT acquisition

    SciTech Connect

    Fast, Martin F.; Wisotzky, Eric; Oelfke, Uwe; Nill, Simeon

    2013-09-15

    Purpose: 4d cone-beam computed tomography (CBCT) scans are usually reconstructed by extracting the motion information from the 2d projections or an external surrogate signal, and binning the individual projections into multiple respiratory phases. In this “after-the-fact” binning approach, however, projections are unevenly distributed over respiratory phases resulting in inefficient utilization of imaging dose. To avoid excess dose in certain respiratory phases, and poor image quality due to a lack of projections in others, the authors have developed a novel 4d CBCT acquisition framework which actively triggers 2d projections based on the forward-predicted position of the tumor.Methods: The forward-prediction of the tumor position was independently established using either (i) an electromagnetic (EM) tracking system based on implanted EM-transponders which act as a surrogate for the tumor position, or (ii) an external motion sensor measuring the chest-wall displacement and correlating this external motion to the phase-shifted diaphragm motion derived from the acquired images. In order to avoid EM-induced artifacts in the imaging detector, the authors devised a simple but effective “Faraday” shielding cage. The authors demonstrated the feasibility of their acquisition strategy by scanning an anthropomorphic lung phantom moving on 1d or 2d sinusoidal trajectories.Results: With both tumor position devices, the authors were able to acquire 4d CBCTs free of motion blurring. For scans based on the EM tracking system, reconstruction artifacts stemming from the presence of the EM-array and the EM-transponders were greatly reduced using newly developed correction algorithms. By tuning the imaging frequency independently for each respiratory phase prior to acquisition, it was possible to harmonize the number of projections over respiratory phases. Depending on the breathing period (3.5 or 5 s) and the gantry rotation time (4 or 5 min), between ∼90 and 145

  4. A 4D Hyperspherical Interpretation of q-Space

    PubMed Central

    Hosseinbor, A. Pasha; Chung, Moo K.; Wu, Yu-Chien; Bendlin, Barbara B.; Alexander, Andrew L.

    2015-01-01

    3D q-space can be viewed as the surface of a 4D hypersphere. In this paper, we seek to develop a 4D hyperspherical interpretation of q-space by projecting it onto a hypersphere and subsequently modeling the q-space signal via 4D hyperspherical harmonics (HSH). Using this orthonormal basis, we derive several well-established q-space indices and numerically estimate the diffusion orientation distribution function (dODF). We also derive the integral transform describing the relationship between the diffusion signal and propagator on a hypersphere. Most importantly, we will demonstrate that for hybrid diffusion imaging (HYDI) acquisitions low order linear expansion of the HSH basis is sufficient to characterize diffusion in neural tissue. In fact, the HSH basis achieves comparable signal and better dODF reconstructions than other well-established methods, such as Bessel Fourier orientation reconstruction (BFOR), using fewer fitting parameters. All in all, this work provides a new way of looking at q-space. PMID:25624043

  5. 4-D imaging of seepage in earthen embankments with time-lapse inversion of self-potential data constrained by acoustic emissions localization

    NASA Astrophysics Data System (ADS)

    Rittgers, J. B.; Revil, A.; Planes, T.; Mooney, M. A.; Koelewijn, A. R.

    2015-02-01

    New methods are required to combine the information contained in the passive electrical and seismic signals to detect, localize and monitor hydromechanical disturbances in porous media. We propose a field experiment showing how passive seismic and electrical data can be combined together to detect a preferential flow path associated with internal erosion in a Earth dam. Continuous passive seismic and electrical (self-potential) monitoring data were recorded during a 7-d full-scale levee (earthen embankment) failure test, conducted in Booneschans, Netherlands in 2012. Spatially coherent acoustic emissions events and the development of a self-potential anomaly, associated with induced concentrated seepage and internal erosion phenomena, were identified and imaged near the downstream toe of the embankment, in an area that subsequently developed a series of concentrated water flows and sand boils, and where liquefaction of the embankment toe eventually developed. We present a new 4-D grid-search algorithm for acoustic emissions localization in both time and space, and the application of the localization results to add spatially varying constraints to time-lapse 3-D modelling of self-potential data in the terms of source current localization. Seismic signal localization results are utilized to build a set of time-invariant yet spatially varying model weights used for the inversion of the self-potential data. Results from the combination of these two passive techniques show results that are more consistent in terms of focused ground water flow with respect to visual observation on the embankment. This approach to geophysical monitoring of earthen embankments provides an improved approach for early detection and imaging of the development of embankment defects associated with concentrated seepage and internal erosion phenomena. The same approach can be used to detect various types of hydromechanical disturbances at larger scales.

  6. Whole Mouse Brain Image Reconstruction from Serial Coronal Sections Using FIJI (ImageJ).

    PubMed

    Paletzki, Ronald; Gerfen, Charles R

    2015-10-01

    Whole-brain reconstruction of the mouse enables comprehensive analysis of the distribution of neurochemical markers, the distribution of anterogradely labeled axonal projections or retrogradely labeled neurons projecting to a specific brain site, or the distribution of neurons displaying activity-related markers in behavioral paradigms. This unit describes a method to produce whole-brain reconstruction image sets from coronal brain sections with up to four fluorescent markers using the freely available image-processing program FIJI (ImageJ).

  7. Building Facade Reconstruction by Fusing Terrestrial Laser Points and Images

    PubMed Central

    Pu, Shi; Vosselman, George

    2009-01-01

    Laser data and optical data have a complementary nature for three dimensional feature extraction. Efficient integration of the two data sources will lead to a more reliable and automated extraction of three dimensional features. This paper presents a semiautomatic building facade reconstruction approach, which efficiently combines information from terrestrial laser point clouds and close range images. A building facade's general structure is discovered and established using the planar features from laser data. Then strong lines in images are extracted using Canny extractor and Hough transformation, and compared with current model edges for necessary improvement. Finally, textures with optimal visibility are selected and applied according to accurate image orientations. Solutions to several challenge problems throughout the collaborated reconstruction, such as referencing between laser points and multiple images and automated texturing, are described. The limitations and remaining works of this approach are also discussed. PMID:22408539

  8. Building facade reconstruction by fusing terrestrial laser points and images.

    PubMed

    Pu, Shi; Vosselman, George

    2009-01-01

    Laser data and optical data have a complementary nature for three dimensional feature extraction. Efficient integration of the two data sources will lead to a more reliable and automated extraction of three dimensional features. This paper presents a semiautomatic building facade reconstruction approach, which efficiently combines information from terrestrial laser point clouds and close range images. A building facade's general structure is discovered and established using the planar features from laser data. Then strong lines in images are extracted using Canny extractor and Hough transformation, and compared with current model edges for necessary improvement. Finally, textures with optimal visibility are selected and applied according to accurate image orientations. Solutions to several challenge problems throughout the collaborated reconstruction, such as referencing between laser points and multiple images and automated texturing, are described. The limitations and remaining works of this approach are also discussed.

  9. Compressed hyperspectral image sensing with joint sparsity reconstruction

    NASA Astrophysics Data System (ADS)

    Liu, Haiying; Li, Yunsong; Zhang, Jing; Song, Juan; Lv, Pei

    2011-10-01

    Recent compressed sensing (CS) results show that it is possible to accurately reconstruct images from a small number of linear measurements via convex optimization techniques. In this paper, according to the correlation analysis of linear measurements for hyperspectral images, a joint sparsity reconstruction algorithm based on interband prediction and joint optimization is proposed. In the method, linear prediction is first applied to remove the correlations among successive spectral band measurement vectors. The obtained residual measurement vectors are then recovered using the proposed joint optimization based POCS (projections onto convex sets) algorithm with the steepest descent method. In addition, a pixel-guided stopping criterion is introduced to stop the iteration. Experimental results show that the proposed algorithm exhibits its superiority over other known CS reconstruction algorithms in the literature at the same measurement rates, while with a faster convergence speed.

  10. Double diffraction of quasiperiodic structures and Bayesian image reconstruction

    NASA Astrophysics Data System (ADS)

    Xu, Jian

    2006-04-01

    We study the spectrum of quasiperiodic structures by using quasiperiodic pulse trains. We find a single sharp diffraction peak when the dynamics of the incident wave matches the arrangement of the scatterers, that is, when the pulse train and the scatterers are in resonance. The maximum diffraction angle and the resonant pulse train determine the positions of the scatterers. These results may provide a methodology for identifying quasicrystals with a very large signal-to-noise ratio. We propose a double diffraction scheme to identify one-dimensional quasiperiodic structures with high precision. The scheme uses a set of scatterers to produce a sequence of quasiperiodic pulses from a single pulse, and then uses these pulses to determine the structure of the second set of scatterers. We find the maximum allowable number of target scatterers, given an experimental setup. Our calculation confirms our simulation results. The reverse problem of spectroscopy is reconstruction that is, given an experimental image, how to reconstruct the original as faithfully as possible. We study the general image reconstruction problem under the Bayesian inference framework. We designed a modified multiplicity prior distribution, and use Gibbs sampling to reconstruct the latent image. In contrast with the traditional entropy prior, our modified multiplicity prior avoids the Sterling's formula approximation, incorporates an Occam's razor, and automatically adapts for the information content in the noisy input. We argue that the mean posterior image is a better representation than the maximum a posterior (MAP) image. We also optimize the Gibbs sampling algorithm to determine the high-dimensional posterior density distribution with high efficiency. Our algorithm runs N2 faster than traditional Gibbs sampler. With the knowledge of the full posterior distribution, statistical measures such as standard error and confident interval can be easily generated. Our algorithm is not only useful for

  11. Helical 4D CT and Comparison with Cine 4D CT

    NASA Astrophysics Data System (ADS)

    Pan, Tinsu

    4D CT was one of the most important developments in radiation oncology in the last decade. Its early development in single slice CT and commercialization in multi-slice CT has radically changed our practice in radiation treatment of lung cancer, and has enabled the stereotactic radiosurgery of early stage lung cancer. In this chapter, we will document the history of 4D CT development, detail the data sufficiency condition governing the 4D CT data collection; present the design of the commercial helical 4D CTs from Philips and Siemens; compare the differences between the helical 4D CT and the GE cine 4D CT in data acquisition, slice thickness, acquisition time and work flow; review the respiratory monitoring devices; and understand the causes of image artifacts in 4D CT.

  12. Lunar Surface Reconstruction from Apollo MC Images

    NASA Astrophysics Data System (ADS)

    Elaksher, Ahmed F.; Al-Jarrah, Ahmad; Walker, Kyle

    2015-07-01

    The last three Apollo lunar missions (15, 16, and 17) carried an integrated photogrammetric mapping system of a metric camera (MC), a high-resolution panoramic camera, a star camera, and a laser altimeter. Recently images taken by the MC were scanned by Arizona State University (ASU); these images contain valuable information for scientific exploration, engineering analysis, and visualization of the Moon's surface. In this article, we took advantage of the large overlaps, the multi viewing, and the high ground resolution of the images taken by the Apollo MC in generating an accurate and reliable surface of the Moon. We started by computing the relative positions and orientations of the exposure stations through a rigorous photogrammetric bundle adjustment process. We then generated a surface model using a hierarchical correlation-based matching algorithm. The matching algorithm was implemented in a multi-photo scheme and permits the exclusion of obscured pixels. The generated surface model was registered with LOLA topographic data and the comparison between the two surfaces yielded an average absolute difference of 36 m. These results look very promising and demonstrate the effectiveness of the proposed algorithm in accounting for depth discontinuities, occlusions, and image-signal noise.

  13. Cascaded diffractive optical elements for improved multiplane image reconstruction.

    PubMed

    Gülses, A Alkan; Jenkins, B Keith

    2013-05-20

    Computer-generated phase-only diffractive optical elements in a cascaded setup are designed by one deterministic and one stochastic algorithm for multiplane image formation. It is hypothesized that increasing the number of elements as wavefront modulators in the longitudinal dimension would enlarge the available solution space, thus enabling enhanced image reconstruction. Numerical results show that increasing the number of holograms improves quality at the output. Design principles, computational methods, and specific conditions are discussed.

  14. Advances in imaging technologies for planning breast reconstruction

    PubMed Central

    Mohan, Anita T.

    2016-01-01

    The role and choice of preoperative imaging for planning in breast reconstruction is still a disputed topic in the reconstructive community, with varying opinion on the necessity, the ideal imaging modality, costs and impact on patient outcomes. Since the advent of perforator flaps their use in microsurgical breast reconstruction has grown. Perforator based flaps afford lower donor morbidity by sparing the underlying muscle provide durable results, superior cosmesis to create a natural looking new breast, and are preferred in the context of radiation therapy. However these surgeries are complex; more technically challenging that implant based reconstruction, and leaves little room for error. The role of imaging in breast reconstruction can assist the surgeon in exploring or confirming flap choices based on donor site characteristics and presence of suitable perforators. Vascular anatomical studies in the lab have provided the surgeon a foundation of knowledge on location and vascular territories of individual perforators to improve our understanding for flap design and safe flap harvest. The creation of a presurgical map in patients can highlight any abnormal or individual anatomical variance to optimize flap design, intraoperative decision-making and execution of flap harvest with greater predictability and efficiency. This article highlights the role and techniques for preoperative planning using the newer technologies that have been adopted in reconstructive clinical practice: computed tomographic angiography (CTA), magnetic resonance angiography (MRA), laser-assisted indocyanine green fluorescence angiography (LA-ICGFA) and dynamic infrared thermography (DIRT). The primary focus of this paper is on the application of CTA and MRA imaging modalities. PMID:27047790

  15. Advances in imaging technologies for planning breast reconstruction.

    PubMed

    Mohan, Anita T; Saint-Cyr, Michel

    2016-04-01

    The role and choice of preoperative imaging for planning in breast reconstruction is still a disputed topic in the reconstructive community, with varying opinion on the necessity, the ideal imaging modality, costs and impact on patient outcomes. Since the advent of perforator flaps their use in microsurgical breast reconstruction has grown. Perforator based flaps afford lower donor morbidity by sparing the underlying muscle provide durable results, superior cosmesis to create a natural looking new breast, and are preferred in the context of radiation therapy. However these surgeries are complex; more technically challenging that implant based reconstruction, and leaves little room for error. The role of imaging in breast reconstruction can assist the surgeon in exploring or confirming flap choices based on donor site characteristics and presence of suitable perforators. Vascular anatomical studies in the lab have provided the surgeon a foundation of knowledge on location and vascular territories of individual perforators to improve our understanding for flap design and safe flap harvest. The creation of a presurgical map in patients can highlight any abnormal or individual anatomical variance to optimize flap design, intraoperative decision-making and execution of flap harvest with greater predictability and efficiency. This article highlights the role and techniques for preoperative planning using the newer technologies that have been adopted in reconstructive clinical practice: computed tomographic angiography (CTA), magnetic resonance angiography (MRA), laser-assisted indocyanine green fluorescence angiography (LA-ICGFA) and dynamic infrared thermography (DIRT). The primary focus of this paper is on the application of CTA and MRA imaging modalities. PMID:27047790

  16. RECONSTRUCTION OF HUMAN LUNG MORPHOLOGY MODELS FROM MAGNETIC RESONANCE IMAGES

    EPA Science Inventory


    Reconstruction of Human Lung Morphology Models from Magnetic Resonance Images
    T. B. Martonen (Experimental Toxicology Division, U.S. EPA, Research Triangle Park, NC 27709) and K. K. Isaacs (School of Public Health, University of North Carolina, Chapel Hill, NC 27514)

  17. An automated 3D reconstruction method of UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  18. Optimized satellite image compression and reconstruction via evolution strategies

    NASA Astrophysics Data System (ADS)

    Babb, Brendan; Moore, Frank; Peterson, Michael

    2009-05-01

    This paper describes the automatic discovery, via an Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), of vectors of real-valued coefficients representing matched forward and inverse transforms that outperform the 9/7 Cohen-Daubechies-Feauveau (CDF) discrete wavelet transform (DWT) for satellite image compression and reconstruction under conditions subject to quantization error. The best transform evolved during this study reduces the mean squared error (MSE) present in reconstructed satellite images by an average of 33.78% (1.79 dB), while maintaining the average information entropy (IE) of compressed images at 99.57% in comparison to the wavelet. In addition, this evolved transform achieves 49.88% (3.00 dB) average MSE reduction when tested on 80 images from the FBI fingerprint test set, and 42.35% (2.39 dB) average MSE reduction when tested on a set of 18 digital photographs, while achieving average IE of 104.36% and 100.08%, respectively. These results indicate that our evolved transform greatly improves the quality of reconstructed images without substantial loss of compression capability over a broad range of image classes.

  19. Super-resolution image reconstruction for ultrasonic nondestructive evaluation.

    PubMed

    Li, Shanglei; Chu, Tsuchin Philip

    2013-12-01

    Ultrasonic testing is one of the most successful nondestructive evaluation (NDE) techniques for the inspection of carbon-fiber-reinforced polymer (CFRP) materials. This paper discusses the application of the iterative backprojection (IBP) super-resolution image reconstruction technique to carbon epoxy laminates with simulated defects to obtain high-resolution images for NDE. Super-resolution image reconstruction is an approach used to overcome the inherent resolution limitations of an existing ultrasonic system. It can greatly improve the image quality and allow more detailed inspection of the region of interest (ROI) with high resolution, improving defect evaluation and accuracy. First, three artificially simulated delamination defects in a CFRP panel were considered to evaluate and validate the application of the IBP method. The results of the validation indicate that both the contrast-tonoise ratio (CNR) and the peak signal-to-noise ratio (PSNR) value of the super-resolution result are better than the bicubic interpolation method. Then, the IBP method was applied to the low-resolution ultrasonic C-scan image sequence with subpixel displacement of two types of defects (delamination and porosity) which were obtained by the micro-scanning imaging technique. The result demonstrated that super-resolution images achieved better visual quality with an improved image resolution compared with raw C-scan images.

  20. A novel data processing technique for image reconstruction of penumbral imaging

    NASA Astrophysics Data System (ADS)

    Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

    2011-06-01

    CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

  1. High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

    NASA Technical Reports Server (NTRS)

    Mareboyana, Manohar; Le Moigne-Stewart, Jacqueline; Bennett, Jerome

    2016-01-01

    In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

  2. High resolution image reconstruction from projection of low resolution images differing in subpixel shifts

    NASA Astrophysics Data System (ADS)

    Mareboyana, Manohar; Le Moigne, Jacqueline; Bennett, Jerome

    2016-05-01

    In this paper, we demonstrate simple algorithms that project low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithms are very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. are used in projection. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML) algorithms. The algorithms are robust and are not overly sensitive to the registration inaccuracies.

  3. Evaluation of the cone beam CT for internal target volume localization in lung stereotactic radiotherapy in comparison with 4D MIP images

    SciTech Connect

    Wang, Lu; Chen, Xiaoming; Lin, Mu-Han; Lin, Teh; Fan, Jiajin; Jin, Lihui; Ma, Charlie M.; Xue, Jun

    2013-11-15

    Purpose: To investigate whether the three-dimensional cone-beam CT (CBCT) is clinically equivalent to the four-dimensional computed tomography (4DCT) maximum intensity projection (MIP) reconstructed images for internal target volume (ITV) localization in image-guided lung stereotactic radiotherapy.Methods: A ball-shaped polystyrene phantom with built-in cube, sphere, and cone of known volumes was attached to a motor-driven platform, which simulates a sinusoidal movement with changeable motion amplitude and frequency. Target motion was simulated in the patient in a superior-inferior (S-I) direction with three motion periods and 2 cm peak-to-peak amplitudes. The Varian onboard Exact-Arms kV CBCT system and the GE LightSpeed four-slice CT integrated with the respiratory-position-management 4DCT scanner were used to scan the moving phantom. MIP images were generated from the 4DCT images. The clinical equivalence of the two sets of images was evaluated by comparing the extreme locations of the moving objects along the motion direction, the centroid position of the ITV, and the ITV volumes that were contoured automatically by Velocity or calculated with an imaging gradient method. The authors compared the ITV volumes determined by the above methods with those theoretically predicted by taking into account the physical object dimensions and the motion amplitudes. The extreme locations were determined by the gradient method along the S-I axis through the center of the object. The centroid positions were determined by autocenter functions. The effect of motion period on the volume sizes was also studied.Results: It was found that the extreme locations of the objects determined from the two image modalities agreed with each other satisfactorily. They were not affected by the motion period. The average difference between the two modalities in the extreme locations was 0.68% for the cube, 1.35% for the sphere, and 0.5% for the cone, respectively. The maximum difference in the

  4. Statistical reconstruction algorithms for continuous wave electron spin resonance imaging

    NASA Astrophysics Data System (ADS)

    Kissos, Imry; Levit, Michael; Feuer, Arie; Blank, Aharon

    2013-06-01

    Electron spin resonance imaging (ESRI) is an important branch of ESR that deals with heterogeneous samples ranging from semiconductor materials to small live animals and even humans. ESRI can produce either spatial images (providing information about the spatially dependent radical concentration) or spectral-spatial images, where an extra dimension is added to describe the absorption spectrum of the sample (which can also be spatially dependent). The mapping of oxygen in biological samples, often referred to as oximetry, is a prime example of an ESRI application. ESRI suffers frequently from a low signal-to-noise ratio (SNR), which results in long acquisition times and poor image quality. A broader use of ESRI is hampered by this slow acquisition, which can also be an obstacle for many biological applications where conditions may change relatively quickly over time. The objective of this work is to develop an image reconstruction scheme for continuous wave (CW) ESRI that would make it possible to reduce the data acquisition time without degrading the reconstruction quality. This is achieved by adapting the so-called "statistical reconstruction" method, recently developed for other medical imaging modalities, to the specific case of CW ESRI. Our new algorithm accounts for unique ESRI aspects such as field modulation, spectral-spatial imaging, and possible limitation on the gradient magnitude (the so-called "limited angle" problem). The reconstruction method shows improved SNR and contrast recovery vs. commonly used back-projection-based methods, for a variety of simulated synthetic samples as well as in actual CW ESRI experiments.

  5. Investigation of limited-view image reconstruction in optoacoustic tomography employing a priori structural information

    NASA Astrophysics Data System (ADS)

    Huang, Chao; Oraevsky, Alexander A.; Anastasio, Mark A.

    2010-08-01

    Optoacoustic tomography (OAT) is an emerging ultrasound-mediated biophotonic imaging modality that has exciting potential for many biomedical imaging applications. There is great interest in conducting B-mode ultrasound and OAT imaging studies for breast cancer detection using a common transducer. In this situation, the range of tomographic view angles is limited, which can result in distortions in the reconstructed OAT image if conventional reconstruction algorithms are applied to limited-view measurement data. In this work, we investigate an image reconstruction method that utilizes information regarding target boundaries to improve the quality of the reconstructed OAT images. This is accomplished by developing boundary-constrained image reconstruction algorithm for OAT based on Bayesian image reconstruction theory. The computer-simulation studies demonstrate that the Bayesian approach can effectively reduce the artifact and noise levels and preserve the edges in reconstructed limited-view OAT images as compared to those produced by a conventional OAT reconstruction algorithm.

  6. Colored three-dimensional reconstruction of vehicular thermal infrared images

    NASA Astrophysics Data System (ADS)

    Sun, Shaoyuan; Leung, Henry; Shen, Zhenyi

    2015-06-01

    Enhancement of vehicular night vision thermal infrared images is an important problem in intelligent vehicles. We propose to create a colorful three-dimensional (3-D) display of infrared images for the vehicular night vision assistant driving system. We combine the plane parameter Markov random field (PP-MRF) model-based depth estimation with classification-based infrared image colorization to perform colored 3-D reconstruction of vehicular thermal infrared images. We first train the PP-MRF model to learn the relationship between superpixel features and plane parameters. The infrared images are then colorized and we perform superpixel segmentation and feature extraction on the colorized images. The PP-MRF model is used to estimate the superpixel plane parameter and to analyze the structure of the superpixels according to the characteristics of vehicular thermal infrared images. Finally, we estimate the depth of each pixel to perform 3-D reconstruction. Experimental results demonstrate that the proposed method can give a visually pleasing and daytime-like colorful 3-D display from a monochromatic vehicular thermal infrared image, which can help drivers to have a better understanding of the environment.

  7. Three-dimensional imaging reconstruction algorithm of gated-viewing laser imaging with compressive sensing.

    PubMed

    Li, Li; Xiao, Wei; Jian, Weijian

    2014-11-20

    Three-dimensional (3D) laser imaging combining compressive sensing (CS) has an advantage in lower power consumption and less imaging sensors; however, it brings enormous stress to subsequent calculation devices. In this paper we proposed a fast 3D imaging reconstruction algorithm to deal with time-slice images sampled by single-pixel detectors. The algorithm implements 3D imaging reconstruction before CS recovery, thus it saves plenty of runtime of CS recovery. Several experiments are conducted to verify the performance of the algorithm. Simulation results demonstrated that the proposed algorithm has better performance in terms of efficiency compared to an existing algorithm.

  8. Geometric validation of self-gating k-space-sorted 4D-MRI vs 4D-CT using a respiratory motion phantom

    SciTech Connect

    Yue, Yong Yang, Wensha; McKenzie, Elizabeth; Tuli, Richard; Wallace, Robert; Fraass, Benedick; Fan, Zhaoyang; Pang, Jianing; Deng, Zixin; Li, Debiao

    2015-10-15

    Purpose: MRI is increasingly being used for radiotherapy planning, simulation, and in-treatment-room motion monitoring. To provide more detailed temporal and spatial MR data for these tasks, we have recently developed a novel self-gated (SG) MRI technique with advantage of k-space phase sorting, high isotropic spatial resolution, and high temporal resolution. The current work describes the validation of this 4D-MRI technique using a MRI- and CT-compatible respiratory motion phantom and comparison to 4D-CT. Methods: The 4D-MRI sequence is based on a spoiled gradient echo-based 3D projection reconstruction sequence with self-gating for 4D-MRI at 3 T. Respiratory phase is resolved by using SG k-space lines as the motion surrogate. 4D-MRI images are reconstructed into ten temporal bins with spatial resolution 1.56 × 1.56 × 1.56 mm{sup 3}. A MRI-CT compatible phantom was designed to validate the performance of the 4D-MRI sequence and 4D-CT imaging. A spherical target (diameter 23 mm, volume 6.37 ml) filled with high-concentration gadolinium (Gd) gel is embedded into a plastic box (35 × 40 × 63 mm{sup 3}) and stabilized with low-concentration Gd gel. The phantom, driven by an air pump, is able to produce human-type breathing patterns between 4 and 30 respiratory cycles/min. 4D-CT of the phantom has been acquired in cine mode, and reconstructed into ten phases with slice thickness 1.25 mm. The 4D images sets were imported into a treatment planning software for target contouring. The geometrical accuracy of the 4D MRI and CT images has been quantified using target volume, flattening, and eccentricity. The target motion was measured by tracking the centroids of the spheres in each individual phase. Motion ground-truth was obtained from input signals and real-time video recordings. Results: The dynamic phantom has been operated in four respiratory rate (RR) settings, 6, 10, 15, and 20/min, and was scanned with 4D-MRI and 4D-CT. 4D-CT images have target

  9. Atmospheric isoplanatism and astronomical image reconstruction on Mauna Kea

    SciTech Connect

    Cowie, L.L.; Songaila, A.

    1988-07-01

    Atmospheric isoplanatism for visual wavelength image-reconstruction applications was measured on Mauna Kea in Hawaii. For most nights the correlation of the transform functions is substantially wider than the long-exposure transform function at separations up to 30 arcsec. Theoretical analysis shows that this is reasonable if the mean Fried parameter is approximately 30 cm at 5500 A. Reconstructed image quality may be described by a Gaussian with a FWHM of lambda/s/sub 0/. Under average conditions, s/sub 0/ (30 arcsec) exceeds 55 cm at 7000 A. The results show that visual image quality in the 0.1--0.2 arcsec range is obtainable over much of the sky with large ground-based telescopes on this site.

  10. Use of INSAT-3D sounder and imager radiances in the 4D-VAR data assimilation system and its implications in the analyses and forecasts

    NASA Astrophysics Data System (ADS)

    Indira Rani, S.; Taylor, Ruth; George, John P.; Rajagopal, E. N.

    2016-05-01

    INSAT-3D, the first Indian geostationary satellite with sounding capability, provides valuable information over India and the surrounding oceanic regions which are pivotal to Numerical Weather Prediction. In collaboration with UK Met Office, NCMRWF developed the assimilation capability of INSAT-3D Clear Sky Brightness Temperature (CSBT), both from the sounder and imager, in the 4D-Var assimilation system being used at NCMRWF. Out of the 18 sounder channels, radiances from 9 channels are selected for assimilation depending on relevance of the information in each channel. The first three high peaking channels, the CO2 absorption channels and the three water vapor channels (channel no. 10, 11, and 12) are assimilated both over land and Ocean, whereas the window channels (channel no. 6, 7, and 8) are assimilated only over the Ocean. Measured satellite radiances are compared with that from short range forecasts to monitor the data quality. This is based on the assumption that the observed satellite radiances are free from calibration errors and the short range forecast provided by NWP model is free from systematic errors. Innovations (Observation - Forecast) before and after the bias correction are indicative of how well the bias correction works. Since the biases vary with air-masses, time, scan angle and also due to instrument degradation, an accurate bias correction algorithm for the assimilation of INSAT-3D sounder radiance is important. This paper discusses the bias correction methods and other quality controls used for the selected INSAT-3D sounder channels and the impact of bias corrected radiance in the data assimilation system particularly over India and surrounding oceanic regions.

  11. Reconstruction of pulse noisy images via stochastic resonance.

    PubMed

    Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

    2015-01-01

    We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

  12. Reconstruction of pulse noisy images via stochastic resonance

    NASA Astrophysics Data System (ADS)

    Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

    2015-06-01

    We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications.

  13. The SRT reconstruction algorithm for semiquantification in PET imaging

    SciTech Connect

    Kastis, George A.; Gaitanis, Anastasios; Samartzis, Alexandros P.; Fokas, Athanasios S.

    2015-10-15

    Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT

  14. LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

    NASA Astrophysics Data System (ADS)

    Li, Yusheng; Matej, Samuel; Karp, Joel S.; Metzler, Scott D.

    2015-01-01

    Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which

  15. LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

    PubMed Central

    Li, Yusheng; Matej, Samuel; Karp, Joel S.; Metzler, Scott D.

    2015-01-01

    Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanner. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present an LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3-D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the nonnegative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which

  16. Improving 4D plan quality for PBS-based liver tumour treatments by combining online image guided beam gating with rescanning

    NASA Astrophysics Data System (ADS)

    Zhang, Ye; Knopf, Antje-Christin; Weber, Damien Charles; Lomax, Antony John

    2015-10-01

    Pencil beam scanned (PBS) proton therapy has many advantages over conventional radiotherapy, but its effectiveness for treating mobile tumours remains questionable. Gating dose delivery to the breathing pattern is a well-developed method in conventional radiotherapy for mitigating tumour-motion, but its clinical efficiency for PBS proton therapy is not yet well documented. In this study, the dosimetric benefits and the treatment efficiency of beam gating for PBS proton therapy has been comprehensively evaluated. A series of dedicated 4D dose calculations (4DDC) have been performed on 9 different 4DCT(MRI) liver data sets, which give realistic 4DCT extracting motion information from 4DMRI. The value of 4DCT(MRI) is its capability of providing not only patient geometries and deformable breathing characteristics, but also includes variations in the breathing patterns between breathing cycles. In order to monitor target motion and derive a gating signal, we simulate time-resolved beams’ eye view (BEV) x-ray images as an online motion surrogate. 4DDCs have been performed using three amplitude-based gating window sizes (10/5/3 mm) with motion surrogates derived from either pre-implanted fiducial markers or the diaphragm. In addition, gating has also been simulated in combination with up to 19 times rescanning using either volumetric or layered approaches. The quality of the resulting 4DDC plans has been quantified in terms of the plan homogeneity index (HI), total treatment time and duty cycle. Results show that neither beam gating nor rescanning alone can fully retrieve the plan homogeneity of the static reference plan. Especially for variable breathing patterns, reductions of the effective duty cycle to as low as 10% have been observed with the smallest gating rescanning window (3 mm), implying that gating on its own for such cases would result in much longer treatment times. In addition, when rescanning is applied on its own, large differences between volumetric

  17. 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.

  18. Tomographic image reconstruction and rendering with texture-mapping hardware

    SciTech Connect

    Azevedo, S.G.; Cabral, B.K.; Foran, J.

    1994-07-01

    The image reconstruction problem, also known as the inverse Radon transform, for x-ray computed tomography (CT) is found in numerous applications in medicine and industry. The most common algorithm used in these cases is filtered backprojection (FBP), which, while a simple procedure, is time-consuming for large images on any type of computational engine. Specially-designed, dedicated parallel processors are commonly used in medical CT scanners, whose results are then passed to graphics workstation for rendering and analysis. However, a fast direct FBP algorithm can be implemented on modern texture-mapping hardware in current high-end workstation platforms. This is done by casting the FBP algorithm as an image warping operation with summing. Texture-mapping hardware, such as that on the Silicon Graphics Reality Engine (TM), shows around 600 times speedup of backprojection over a CPU-based implementation (a 100 Mhz R4400 in this case). This technique has the further advantages of flexibility and rapid programming. In addition, the same hardware can be used for both image reconstruction and for volumetric rendering. The techniques can also be used to accelerate iterative reconstruction algorithms. The hardware architecture also allows more complex operations than straight-ray backprojection if they are required, including fan-beam, cone-beam, and curved ray paths, with little or no speed penalties.

  19. Tomographic image reconstruction and rendering with texture-mapping hardware

    NASA Astrophysics Data System (ADS)

    Azevedo, Stephen G.; Cabral, Brian K.; Foran, Jim

    1994-07-01

    The image reconstruction problem, also known as the inverse Radon transform, for x-ray computed tomography (CT) is found in numerous applications in medicine and industry. The most common algorithm used in these cases is filtered backprojection (FBP), which, while a simple procedure, is time-consuming for large images on any type of computational engine. Specially designed, dedicated parallel processors are commonly used in medical CT scanners, whose results are then passed to a graphics workstation for rendering and analysis. However, a fast direct FBP algorithm can be implemented on modern texture-mapping hardware in current high-end workstation platforms. This is done by casting the FBP algorithm as an image warping operation with summing. Texture- mapping hardware, such as that on the silicon Graphics Reality Engine, shows around 600 times speedup of backprojection over a CPU-based implementation (a 100 Mhz R4400 in our case). This technique has the further advantages of flexibility and rapid programming. In addition, the same hardware can be used for both image reconstruction and for volumetric rendering. Our technique can also be used to accelerate iterative reconstruction algorithms. The hardware architecture also allows more complex operations than straight-ray backprojection if they are required, including fan-beam, cone-beam, and curved ray paths, with little or no speed penalties.

  20. Complications of anterior cruciate ligament reconstruction: MR imaging.

    PubMed

    Papakonstantinou, Olympia; Chung, Christine B; Chanchairujira, Kullanuch; Resnick, Donald L

    2003-05-01

    Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation.

  1. Complications of anterior cruciate ligament reconstruction: MR imaging.

    PubMed

    Papakonstantinou, Olympia; Chung, Christine B; Chanchairujira, Kullanuch; Resnick, Donald L

    2003-05-01

    Arthroscopic reconstruction of the anterior cruciate ligament (ACL) using autografts or allografts is being performed with increasing frequency, particularly in young athletes. Although the procedure is generally well tolerated, with good success rates, early and late complications have been documented. As clinical manifestations of graft complications are often non-specific and plain radiographs cannot directly visualize the graft and the adjacent soft tissues, MR imaging has a definite role in the diagnosis of complications after ACL reconstruction and may direct subsequent therapeutic management. Our purpose is to review the normal MR imaging of the ACL graft and present the MR imaging findings of a wide spectrum of complications after ACL reconstruction, such as graft impingement, graft rupture, cystic degeneration of the graft, postoperative infection of the knee, diffuse and localized (i.e., cyclops lesion) arthrofibrosis, and associated donor site abnormalities. Awareness of the MR imaging findings of complications as well as the normal appearances of the normal ACL graft is essential for correct interpretation. PMID:12695835

  2. Performance validation of phase diversity image reconstruction techniques

    NASA Astrophysics Data System (ADS)

    Hirzberger, J.; Feller, A.; Riethmüller, T. L.; Gandorfer, A.; Solanki, S. K.

    2011-05-01

    We present a performance study of a phase diversity (PD) image reconstruction algorithm based on artificial solar images obtained from MHD simulations and on seeing-free data obtained with the SuFI instrument on the Sunrise balloon borne observatory. The artificial data were altered by applying different levels of degradation with synthesised wavefront errors and noise. The PD algorithm was modified by changing the number of fitted polynomials, the shape of the pupil and the applied noise filter. The obtained reconstructions are evaluated by means of the resulting rms intensity contrast and by the conspicuousness of appearing artifacts. The results show that PD is a robust method which consistently recovers the initial unaffected image contents. The efficiency of the reconstruction is, however, strongly dependent on the number of used fitting polynomials and the noise level of the images. If the maximum number of fitted polynomials is higher than 21, artifacts have to be accepted and for noise levels higher than 10-3 the commonly used noise filtering techniques are not able to avoid amplification of spurious structures.

  3. Missing data reconstruction using Gaussian mixture models for fingerprint images

    NASA Astrophysics Data System (ADS)

    Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

    2016-05-01

    Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

  4. Edge-Preserving PET Image Reconstruction Using Trust Optimization Transfer

    PubMed Central

    Wang, Guobao; Qi, Jinyi

    2014-01-01

    Iterative image reconstruction for positron emission tomography (PET) can improve image quality by using spatial regularization. The most commonly used quadratic penalty often over-smoothes sharp edges and fine features in reconstructed images, while non-quadratic penalties can preserve edges and achieve higher contrast recovery. Existing optimization algorithms such as the expectation maximization (EM) and preconditioned conjugate gradient (PCG) algorithms work well for the quadratic penalty, but are less efficient for high-curvature or non-smooth edge-preserving regularizations. This paper proposes a new algorithm to accelerate edge-preserving image reconstruction by using two strategies: trust surrogate and optimization transfer descent. Trust surrogate approximates the original penalty by a smoother function at each iteration, but guarantees the algorithm to descend monotonically; Optimization transfer descent accelerates a conventional optimization transfer algorithm by using conjugate gradient and line search. Results of computer simulations and real 3D data show that the proposed algorithm converges much faster than the conventional EM and PCG for smooth edge-preserving regularization and can also be more efficient than the current state-of-art algorithms for the non-smooth ℓ1 regularization. PMID:25438302

  5. Parallel expectation-maximization algorithms for PET image reconstruction

    NASA Astrophysics Data System (ADS)

    Jeng, Wei-Min

    1999-10-01

    Image reconstruction using Positron Emission Tomography (PET) involves estimating an unknown number of photon pairs emitted from the radiopharmaceuticals within the tissues of the patient's body. The generation of the photons can be described as a Poisson process, and the difficulty of image reconstruction involves approximating the parameter of the tissue density distribution function. A significant amount of artifactual noise exists in the reconstructed image with the convolution back projection method. Using the Maximum Likelihood (ML) formulation, a better estimate can be made for the unknown image information. Despite the better quality of images, the Expectation Maximization (EM) iterative algorithm is not being used in practice due to the tremendous processing time. This research proposes new techniques in designing parallel algorithms in order to speed the reconstruction process. Using the EM algorithm as an example, several general parallel techniques were studied for both distributed-memory architecture and message-passing programming paradigm. Both intra- and inter-iteration latency-hiding schemes were designed to effectively reduce the communication time. Dependencies that exist in and between iterations were rearranged by overlap communication and computation with MPI's non-blocking collective reduction operation. A performance model was established to estimate the processing time of the algorithms and was found to agree with the experimental results. A second strategy, the sparse matrix compaction technique, was developed to reduce the computational time of the computation-bound EM algorithm with better use of PET system geometry. The proposed techniques are generally applicable to many scientific computation problems that involve sparse matrix operations as well as iterative types, of algorithms.

  6. A dual oxygenation and fluorescence imaging platform for reconstructive surgery

    NASA Astrophysics Data System (ADS)

    Ashitate, Yoshitomo; Nguyen, John N.; Venugopal, Vivek; Stockdale, Alan; Neacsu, Florin; Kettenring, Frank; Lee, Bernard T.; Frangioni, John V.; Gioux, Sylvain

    2013-03-01

    There is a pressing clinical need to provide image guidance during surgery. Currently, assessment of tissue that needs to be resected or avoided is performed subjectively, leading to a large number of failures, patient morbidity, and increased healthcare costs. Because near-infrared (NIR) optical imaging is safe, noncontact, inexpensive, and can provide relatively deep information (several mm), it offers unparalleled capabilities for providing image guidance during surgery. These capabilities are well illustrated through the clinical translation of fluorescence imaging during oncologic surgery. In this work, we introduce a novel imaging platform that combines two complementary NIR optical modalities: oxygenation imaging and fluorescence imaging. We validated this platform during facial reconstructive surgery on large animals approaching the size of humans. We demonstrate that NIR fluorescence imaging provides identification of perforator arteries, assesses arterial perfusion, and can detect thrombosis, while oxygenation imaging permits the passive monitoring of tissue vital status, as well as the detection and origin of vascular compromise simultaneously. Together, the two methods provide a comprehensive approach to identifying problems and intervening in real time during surgery before irreparable damage occurs. Taken together, this novel platform provides fully integrated and clinically friendly endogenous and exogenous NIR optical imaging for improved image-guided intervention during surgery.

  7. An efficient simultaneous reconstruction technique for tomographic particle image velocimetry

    NASA Astrophysics Data System (ADS)

    Atkinson, Callum; Soria, Julio

    2009-10-01

    To date, Tomo-PIV has involved the use of the multiplicative algebraic reconstruction technique (MART), where the intensity of each 3D voxel is iteratively corrected to satisfy one recorded projection, or pixel intensity, at a time. This results in reconstruction times of multiple hours for each velocity field and requires considerable computer memory in order to store the associated weighting coefficients and intensity values for each point in the volume. In this paper, a rapid and less memory intensive reconstruction algorithm is presented based on a multiplicative line-of-sight (MLOS) estimation that determines possible particle locations in the volume, followed by simultaneous iterative correction. Reconstructions of simulated images are presented for two simultaneous algorithms (SART and SMART) as well as the now standard MART algorithm, which indicate that the same accuracy as MART can be achieved 5.5 times faster or 77 times faster with 15 times less memory if the processing and storage of the weighting matrix is considered. Application of MLOS-SMART and MART to a turbulent boundary layer at Re θ = 2200 using a 4 camera Tomo-PIV system with a volume of 1,000 × 1,000 × 160 voxels is discussed. Results indicate improvements in reconstruction speed of 15 times that of MART with precalculated weighting matrix, or 65 times if calculation of the weighting matrix is considered. Furthermore the memory needed to store a large weighting matrix and volume intensity is reduced by almost 40 times in this case.

  8. Research on image matching method of big data image of three-dimensional reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, Chunsen; Qiu, Zhenguo; Zhu, Shihuan; Wang, Xiqi; Xu, Xiaolei; Zhong, Sidong

    2015-12-01

    Image matching is the main flow of a three-dimensional reconstruction. With the development of computer processing technology, seeking the image to be matched from the large date image sets which acquired from different image formats, different scales and different locations has put forward a new request for image matching. To establish the three dimensional reconstruction based on image matching from big data images, this paper put forward a new effective matching method based on visual bag of words model. The main technologies include building the bag of words model and image matching. First, extracting the SIFT feature points from images in the database, and clustering the feature points to generate the bag of words model. We established the inverted files based on the bag of words. The inverted files can represent all images corresponding to each visual word. We performed images matching depending on the images under the same word to improve the efficiency of images matching. Finally, we took the three-dimensional model with those images. Experimental results indicate that this method is able to improve the matching efficiency, and is suitable for the requirements of large data reconstruction.

  9. Reconstruction of hyperspectral image using matting model for classification

    NASA Astrophysics Data System (ADS)

    Xie, Weiying; Li, Yunsong; Ge, Chiru

    2016-05-01

    Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.

  10. Limited Angle Reconstruction Method for Reconstructing Terrestrial Plasmaspheric Densities from EUV Images

    NASA Technical Reports Server (NTRS)

    Newman, Timothy; Santhanam, Naveen; Zhang, Huijuan; Gallagher, Dennis

    2003-01-01

    A new method for reconstructing the global 3D distribution of plasma densities in the plasmasphere from a limited number of 2D views is presented. The method is aimed at using data from the Extreme Ultra Violet (EUV) sensor on NASA s Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) satellite. Physical properties of the plasmasphere are exploited by the method to reduce the level of inaccuracy imposed by the limited number of views. The utility of the method is demonstrated on synthetic data.

  11. Improving thoracic four-dimensional cone-beam CT reconstruction with anatomical-adaptive image regularization (AAIR).

    PubMed

    Shieh, Chun-Chien; Kipritidis, John; O'Brien, Ricky T; Cooper, Benjamin J; Kuncic, Zdenka; Keall, Paul J

    2015-01-21

    Total-variation (TV) minimization reconstructions can significantly reduce noise and streaks in thoracic four-dimensional cone-beam computed tomography (4D CBCT) images compared to the Feldkamp-Davis-Kress (FDK) algorithm currently used in practice. TV minimization reconstructions are, however, prone to over-smoothing anatomical details and are also computationally inefficient. The aim of this study is to demonstrate a proof of concept that these disadvantages can be overcome by incorporating the general knowledge of the thoracic anatomy via anatomy segmentation into the reconstruction. The proposed method, referred as the anatomical-adaptive image regularization (AAIR) method, utilizes the adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS) framework, but introduces an additional anatomy segmentation step in every iteration. The anatomy segmentation information is implemented in the reconstruction using a heuristic approach to adaptively suppress over-smoothing at anatomical structures of interest. The performance of AAIR depends on parameters describing the weighting of the anatomy segmentation prior and segmentation threshold values. A sensitivity study revealed that the reconstruction outcome is not sensitive to these parameters as long as they are chosen within a suitable range. AAIR was validated using a digital phantom and a patient scan and was compared to FDK, ASD-POCS and the prior image constrained compressed sensing (PICCS) method. For the phantom case, AAIR reconstruction was quantitatively shown to be the most accurate as indicated by the mean absolute difference and the structural similarity index. For the patient case, AAIR resulted in the highest signal-to-noise ratio (i.e. the lowest level of noise and streaking) and the highest contrast-to-noise ratios for the tumor and the bony anatomy (i.e. the best visibility of anatomical details). Overall, AAIR was much less prone to over-smoothing anatomical details compared to ASD-POCS and did

  12. Improving thoracic four-dimensional cone-beam CT reconstruction with anatomical-adaptive image regularization (AAIR)

    NASA Astrophysics Data System (ADS)

    Shieh, Chun-Chien; Kipritidis, John; O'Brien, Ricky T.; Cooper, Benjamin J.; Kuncic, Zdenka; Keall, Paul J.

    2015-01-01

    Total-variation (TV) minimization reconstructions can significantly reduce noise and streaks in thoracic four-dimensional cone-beam computed tomography (4D CBCT) images compared to the Feldkamp-Davis-Kress (FDK) algorithm currently used in practice. TV minimization reconstructions are, however, prone to over-smoothing anatomical details and are also computationally inefficient. The aim of this study is to demonstrate a proof of concept that these disadvantages can be overcome by incorporating the general knowledge of the thoracic anatomy via anatomy segmentation into the reconstruction. The proposed method, referred as the anatomical-adaptive image regularization (AAIR) method, utilizes the adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS) framework, but introduces an additional anatomy segmentation step in every iteration. The anatomy segmentation information is implemented in the reconstruction using a heuristic approach to adaptively suppress over-smoothing at anatomical structures of interest. The performance of AAIR depends on parameters describing the weighting of the anatomy segmentation prior and segmentation threshold values. A sensitivity study revealed that the reconstruction outcome is not sensitive to these parameters as long as they are chosen within a suitable range. AAIR was validated using a digital phantom and a patient scan and was compared to FDK, ASD-POCS and the prior image constrained compressed sensing (PICCS) method. For the phantom case, AAIR reconstruction was quantitatively shown to be the most accurate as indicated by the mean absolute difference and the structural similarity index. For the patient case, AAIR resulted in the highest signal-to-noise ratio (i.e. the lowest level of noise and streaking) and the highest contrast-to-noise ratios for the tumor and the bony anatomy (i.e. the best visibility of anatomical details). Overall, AAIR was much less prone to over-smoothing anatomical details compared to ASD-POCS and did

  13. Improving thoracic four-dimensional cone-beam CT reconstruction with anatomical-adaptive image regularization (AAIR)

    PubMed Central

    Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T; Cooper, Benjamin J; Kuncic, Zdenka; Keall, Paul J

    2015-01-01

    Total-variation (TV) minimization reconstructions can significantly reduce noise and streaks in thoracic four-dimensional cone-beam computed tomography (4D CBCT) images compared to the Feldkamp-Davis-Kress (FDK) algorithm currently used in practice. TV minimization reconstructions are, however, prone to over-smoothing anatomical details and are also computationally inefficient. The aim of this study is to demonstrate a proof of concept that these disadvantages can be overcome by incorporating the general knowledge of the thoracic anatomy via anatomy segmentation into the reconstruction. The proposed method, referred as the anatomical-adaptive image regularization (AAIR) method, utilizes the adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS) framework, but introduces an additional anatomy segmentation step in every iteration. The anatomy segmentation information is implemented in the reconstruction using a heuristic approach to adaptively suppress over-smoothing at anatomical structures of interest. The performance of AAIR depends on parameters describing the weighting of the anatomy segmentation prior and segmentation threshold values. A sensitivity study revealed that the reconstruction outcome is not sensitive to these parameters as long as they are chosen within a suitable range. AAIR was validated using a digital phantom and a patient scan, and was compared to FDK, ASD-POCS, and the prior image constrained compressed sensing (PICCS) method. For the phantom case, AAIR reconstruction was quantitatively shown to be the most accurate as indicated by the mean absolute difference and the structural similarity index. For the patient case, AAIR resulted in the highest signal-to-noise ratio (i.e. the lowest level of noise and streaking) and the highest contrast-to-noise ratios for the tumor and the bony anatomy (i.e. the best visibility of anatomical details). Overall, AAIR was much less prone to over-smoothing anatomical details compared to ASD-POCS, and

  14. Stokes image reconstruction for two-color microgrid polarization imaging systems.

    PubMed

    Lemaster, Daniel A

    2011-07-18

    The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided. PMID:21934823

  15. Optimizing modelling in iterative image reconstruction for preclinical pinhole PET

    NASA Astrophysics Data System (ADS)

    Goorden, Marlies C.; van Roosmalen, Jarno; van der Have, Frans; Beekman, Freek J.

    2016-05-01

    The recently developed versatile emission computed tomography (VECTor) technology enables high-energy SPECT and simultaneous SPECT and PET of small animals at sub-mm resolutions. VECTor uses dedicated clustered pinhole collimators mounted in a scanner with three stationary large-area NaI(Tl) gamma detectors. Here, we develop and validate dedicated image reconstruction methods that compensate for image degradation by incorporating accurate models for the transport of high-energy annihilation gamma photons. Ray tracing software was used to calculate photon transport through the collimator structures and into the gamma detector. Input to this code are several geometric parameters estimated from system calibration with a scanning 99mTc point source. Effects on reconstructed images of (i) modelling variable depth-of-interaction (DOI) in the detector, (ii) incorporating photon paths that go through multiple pinholes (‘multiple-pinhole paths’ (MPP)), and (iii) including various amounts of point spread function (PSF) tail were evaluated. Imaging 18F in resolution and uniformity phantoms showed that including large parts of PSFs is essential to obtain good contrast-noise characteristics and that DOI modelling is highly effective in removing deformations of small structures, together leading to 0.75 mm resolution PET images of a hot-rod Derenzo phantom. Moreover, MPP modelling reduced the level of background noise. These improvements were also clearly visible in mouse images. Performance of VECTor can thus be significantly improved by accurately modelling annihilation gamma photon transport.

  16. Optimizing modelling in iterative image reconstruction for preclinical pinhole PET.

    PubMed

    Goorden, Marlies C; van Roosmalen, Jarno; van der Have, Frans; Beekman, Freek J

    2016-05-21

    The recently developed versatile emission computed tomography (VECTor) technology enables high-energy SPECT and simultaneous SPECT and PET of small animals at sub-mm resolutions. VECTor uses dedicated clustered pinhole collimators mounted in a scanner with three stationary large-area NaI(Tl) gamma detectors. Here, we develop and validate dedicated image reconstruction methods that compensate for image degradation by incorporating accurate models for the transport of high-energy annihilation gamma photons. Ray tracing software was used to calculate photon transport through the collimator structures and into the gamma detector. Input to this code are several geometric parameters estimated from system calibration with a scanning (99m)Tc point source. Effects on reconstructed images of (i) modelling variable depth-of-interaction (DOI) in the detector, (ii) incorporating photon paths that go through multiple pinholes ('multiple-pinhole paths' (MPP)), and (iii) including various amounts of point spread function (PSF) tail were evaluated. Imaging (18)F in resolution and uniformity phantoms showed that including large parts of PSFs is essential to obtain good contrast-noise characteristics and that DOI modelling is highly effective in removing deformations of small structures, together leading to 0.75 mm resolution PET images of a hot-rod Derenzo phantom. Moreover, MPP modelling reduced the level of background noise. These improvements were also clearly visible in mouse images. Performance of VECTor can thus be significantly improved by accurately modelling annihilation gamma photon transport. PMID:27082049

  17. Boundary conditions in photoacoustic tomography and image reconstruction.

    PubMed

    Wang, Lihong V; Yang, Xinmai

    2007-01-01

    Recently, the field of photoacoustic tomography has experienced considerable growth. Although several commercially available pure optical imaging modalities, including confocal microscopy, two-photon microscopy, and optical coherence tomography, have been highly successful, none of these technologies can penetrate beyond approximately 1 mm into scattering biological tissues because all of them are based on ballistic and quasiballistic photons. Consequently, heretofore there has been a void in high-resolution optical imaging beyond this depth limit. Photoacoustic tomography has filled this void by combining high ultrasonic resolution and strong optical contrast in a single modality. However, it has been assumed in reconstruction of photoacoustic tomography until now that ultrasound propagates in a boundary-free infinite medium. We present the boundary conditions that must be considered in certain imaging configurations; the associated inverse solutions for image reconstruction are provided and validated by numerical simulation and experiment. Partial planar, cylindrical, and spherical detection configurations with a planar boundary are covered, where the boundary can be either hard or soft. Analogously to the method of images of sources, which is commonly used in forward problems, the ultrasonic detectors are imaged about the boundary to satisfy the boundary condition in the inverse problem. PMID:17343502

  18. POCSENSE: POCS-based reconstruction for sensitivity encoded magnetic resonance imaging.

    PubMed

    Samsonov, Alexei A; Kholmovski, Eugene G; Parker, Dennis L; Johnson, Chris R

    2004-12-01

    A novel method for iterative reconstruction of images from undersampled MRI data acquired by multiple receiver coil systems is presented. Based on Projection onto Convex Sets (POCS) formalism, the method for SENSitivity Encoded data reconstruction (POCSENSE) can be readily modified to include various linear and nonlinear reconstruction constraints. Such constraints may be beneficial for reconstructing highly and overcritically undersampled data sets to improve image quality. POCSENSE is conceptually simple and numerically efficient and can reconstruct images from data sampled on arbitrary k-space trajectories. The applicability of POCSENSE for image reconstruction with nonlinear constraining was demonstrated using a wide range of simulated and real MRI data.

  19. Image reconstruction and optimization using a terahertz scanned imaging system

    NASA Astrophysics Data System (ADS)

    Yıldırım, İhsan Ozan; Özkan, Vedat A.; Idikut, Fırat; Takan, Taylan; Şahin, Asaf B.; Altan, Hakan

    2014-10-01

    Due to the limited number of array detection architectures in the millimeter wave to terahertz region of the electromagnetic spectrum, imaging schemes with scan architectures are typically employed. In these configurations the interplay between the frequencies used to illuminate the scene and the optics used play an important role in the quality of the formed image. Using a multiplied Schottky-diode based terahertz transceiver operating at 340 GHz, in a stand-off detection scheme; the effect of image quality of a metal target was assessed based on the scanning speed of the galvanometer mirrors as well as the optical system that was constructed. Background effects such as leakage on the receiver were minimized by conditioning the signal at the output of the transceiver. Then, the image of the target was simulated based on known parameters of the optical system and the measured images were compared to the simulation. By using an image quality index based on χ2 algorithm the simulated and measured images were found to be in good agreement with a value of χ2 = 0 .14. The measurements as shown here will aid in the future development of larger stand-off imaging systems that work in the terahertz frequency range.

  20. Model-based microwave image reconstruction: simulations and experiments

    SciTech Connect

    Ciocan, Razvan; Jiang Huabei

    2004-12-01

    We describe an integrated microwave imaging system that can provide spatial maps of dielectric properties of heterogeneous media with tomographically collected data. The hardware system (800-1200 MHz) was built based on a lock-in amplifier with 16 fixed antennas. The reconstruction algorithm was implemented using a Newton iterative method with combined Marquardt-Tikhonov regularizations. System performance was evaluated using heterogeneous media mimicking human breast tissue. Finite element method coupled with the Bayliss and Turkel radiation boundary conditions were applied to compute the electric field distribution in the heterogeneous media of interest. The results show that inclusions embedded in a 76-diameter background medium can be quantitatively reconstructed from both simulated and experimental data. Quantitative analysis of the microwave images obtained suggests that an inclusion of 14 mm in diameter is the smallest object that can be fully characterized presently using experimental data, while objects as small as 10 mm in diameter can be quantitatively resolved with simulated data.

  1. PET image reconstruction with anatomical edge guided level set prior

    NASA Astrophysics Data System (ADS)

    Cheng-Liao, Jinxiu; Qi, Jinyi

    2011-11-01

    Acquiring both anatomical and functional images during one scan, PET/CT systems improve the ability to detect and localize abnormal uptakes. In addition, CT images provide anatomical boundary information that can be used to regularize positron emission tomography (PET) images. Here we propose a new approach to maximum a posteriori reconstruction of PET images with a level set prior guided by anatomical edges. The image prior models both the smoothness of PET images and the similarity between functional boundaries in PET and anatomical boundaries in CT. Level set functions (LSFs) are used to represent smooth and closed functional boundaries. The proposed method does not assume an exact match between PET and CT boundaries. Instead, it encourages similarity between the two boundaries, while allowing different region definition in PET images to accommodate possible signal and position mismatch between functional and anatomical images. While the functional boundaries are guaranteed to be closed by the LSFs, the proposed method does not require closed anatomical boundaries and can utilize incomplete edges obtained from an automatic edge detection algorithm. We conducted computer simulations to evaluate the performance of the proposed method. Two digital phantoms were constructed based on the Digimouse data and a human CT image, respectively. Anatomical edges were extracted automatically from the CT images. Tumors were simulated in the PET phantoms with different mismatched anatomical boundaries. Compared with existing methods, the new method achieved better bias-variance performance. The proposed method was also applied to real mouse data and achieved higher contrast than other methods.

  2. Three-dimensional image reconstruction in object space

    SciTech Connect

    Kinahan, P.E.; Rogers, J.G.; Harrop, R.; Johnson, R.R.

    1988-02-01

    An analytic three-dimensional image reconstruction algorithm which can utilize the cross-plane gamma rays detected by a wide solid-angle PET system is presented. Unlike current analytic algorithms it does not use Fourier transform methods, although mathematical equivalence to Fourier transform methods is proven. Results of implementing the algorithm are briefly discussed. An extension of the algorithm to utilize all measured cross-plane gamma rays is discussed.

  3. LIRA: Low-counts Image Reconstruction and Analysis

    NASA Astrophysics Data System (ADS)

    Connors, Alanna; Kashyap, Vinay; Siemiginowska, Aneta; van Dyk, David; Stein, Nathan M.

    2016-01-01

    LIRA (Low-counts Image Reconstruction and Analysis) deconvolves any unknown sky components, provides a fully Poisson 'goodness-of-fit' for any best-fit model, and quantifies uncertainties on the existence and shape of unknown sky. It does this without resorting to χ2 or rebinning, which can lose high-resolution information. It is written in R and requires the FITSio package.

  4. Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

    SciTech Connect

    Sidky, Emil Y.; Pan Xiaochuan; Reiser, Ingrid S.; Nishikawa, Robert M.; Moore, Richard H.; Kopans, Daniel B.

    2009-11-15

    Purpose: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). Methods: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p=1.0 or the image roughness when p=2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. Results: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. Conclusions: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging.

  5. Enhanced imaging of microcalcifications in digital breast tomosynthesis through improved image-reconstruction algorithms

    PubMed Central

    Sidky, Emil Y.; Pan, Xiaochuan; Reiser, Ingrid S.; Nishikawa, Robert M.; Moore, Richard H.; Kopans, Daniel B.

    2009-01-01

    Purpose: The authors develop a practical, iterative algorithm for image-reconstruction in undersampled tomographic systems, such as digital breast tomosynthesis (DBT). Methods: The algorithm controls image regularity by minimizing the image total p variation (TpV), a function that reduces to the total variation when p=1.0 or the image roughness whenp=2.0. Constraints on the image, such as image positivity and estimated projection-data tolerance, are enforced by projection onto convex sets. The fact that the tomographic system is undersampled translates to the mathematical property that many widely varied resultant volumes may correspond to a given data tolerance. Thus the application of image regularity serves two purposes: (1) Reduction in the number of resultant volumes out of those allowed by fixing the data tolerance, finding the minimum image TpV for fixed data tolerance, and (2) traditional regularization, sacrificing data fidelity for higher image regularity. The present algorithm allows for this dual role of image regularity in undersampled tomography. Results: The proposed image-reconstruction algorithm is applied to three clinical DBT data sets. The DBT cases include one with microcalcifications and two with masses. Conclusions: Results indicate that there may be a substantial advantage in using the present image-reconstruction algorithm for microcalcification imaging. PMID:19994501

  6. Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means

    SciTech Connect

    Zhang Yu; Yap, Pew-Thian; Wu Guorong; Feng Qianjin; Chen Wufan; Lian Jun; Shen Dinggang

    2013-05-15

    Purpose: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. Methods: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. Results: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors' algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors' algorithm increases peak signal-to-noise ratio by 3-4 dB and the structural similarity index by 3%-5% when compared with the standard interpolation-based algorithms. Conclusions: The authors have developed a new algorithm to improve the resolution of 4D-CT. It outperforms

  7. Is a Clinical Target Volume (CTV) Necessary in the Treatment of Lung Cancer in the Modern Era Combining 4-D Imaging and Image-guided Radiotherapy (IGRT)?

    PubMed Central

    Kilburn, Jeremy M; Lucas, John T; Soike, Michael H; Ayala-Peacock, Diandra N; Blackstock, Arthur W; Hinson, William H; Munley, Michael T; Petty, William J

    2016-01-01

    Objective: We hypothesized that omission of clinical target volumes (CTV) in lung cancer radiotherapy would not compromise control by determining retrospectively if the addition of a CTV would encompass the site of failure. Methods: Stage II-III patients were treated from 2009-2012 with daily cone-beam imaging and a 5 mm planning target volume (PTV) without a CTV. PTVs were expanded 1 cm and termed CTVretro. Recurrences were scored as 1) within the PTV, 2) within CTVretro, or 3) outside the PTV. Locoregional control (LRC), distant control (DC), progression-free survival (PFS), and overall survival (OS) were estimated. Result: Among 110 patients, Stage IIIA 57%, IIIB 32%, IIA 4%, and IIB 7%. Eighty-six percent of Stage III patients received chemotherapy. Median dose was 70 Gy (45-74 Gy) and fraction size ranged from 1.5-2.7 Gy. Median follow-up was 12 months, median OS was 22 months (95% CI 19-30 months), and LRC at two years was 69%. Fourteen local and eight regional events were scored with two CTVretro failures equating to a two-year CTV failure-free survival of 98%. Conclusion: Omission of a 1 cm CTV expansion appears feasible based on only two events among 110 patients and should be considered in radiation planning. PMID:26929893

  8. Reconstruction of three-dimensional occluded object using optical flow and triangular mesh reconstruction in integral imaging.

    PubMed

    Jung, Jae-Hyun; Hong, Keehoon; Park, Gilbae; Chung, Indeok; Park, Jae-Hyeung; Lee, Byoungho

    2010-12-01

    We proposed a reconstruction method for the occluded region of three-dimensional (3D) object using the depth extraction based on the optical flow and triangular mesh reconstruction in integral imaging. The depth information of sub-images from the acquired elemental image set is extracted using the optical flow with sub-pixel accuracy, which alleviates the depth quantization problem. The extracted depth maps of sub-image array are segmented by the depth threshold from the histogram based segmentation, which is represented as the point clouds. The point clouds are projected to the viewpoint of center sub-image and reconstructed by the triangular mesh reconstruction. The experimental results support the validity of the proposed method with high accuracy of peak signal-to-noise ratio and normalized cross-correlation in 3D image recognition.

  9. Impact of measurement precision and noise on superresolution image reconstruction.

    PubMed

    Wood, Sally L; Lee, Shu-Ting; Yang, Gao; Christensen, Marc P; Rajan, Dinesh

    2008-04-01

    The performance of uniform and nonuniform detector arrays for application to the PANOPTES (processing arrays of Nyquist-limited observations to produce a thin electro-optic sensor) flat camera design is analyzed for measurement noise environments including quantization noise and Gaussian and Poisson processes. Image data acquired from a commercial camera with 8 bit and 14 bit output options are analyzed, and estimated noise levels are computed. Noise variances estimated from the measurement values are used in the optimal linear estimators for superresolution image reconstruction.

  10. Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope

    NASA Astrophysics Data System (ADS)

    Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau

    2012-05-01

    This study investiga