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Sample records for standardized reconstruction images

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

    Science.gov (United States)

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

    2014-12-01

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

  2. Optimization, evaluation, and comparison of standard algorithms for image reconstruction with the VIP-PET

    Science.gov (United States)

    Mikhaylova, E.; Kolstein, M.; De Lorenzo, G.; Chmeissani, M.

    2014-01-01

    A novel positron emission tomography (PET) scanner design based on a room-temperature pixelated CdTe solid-state detector is being developed within the framework of the Voxel Imaging PET (VIP) Pathfinder project [1]. The simulation results show a great potential of the VIP to produce high-resolution images even in extremely challenging conditions such as the screening of a human head [2]. With unprecedented high channel density (450 channels/cm3) image reconstruction is a challenge. Therefore optimization is needed to find the best algorithm in order to exploit correctly the promising detector potential. The following reconstruction algorithms are evaluated: 2-D Filtered Backprojection (FBP), Ordered Subset Expectation Maximization (OSEM), List-Mode OSEM (LM-OSEM), and the Origin Ensemble (OE) algorithm. The evaluation is based on the comparison of a true image phantom with a set of reconstructed images obtained by each algorithm. This is achieved by calculation of image quality merit parameters such as the bias, the variance and the mean square error (MSE). A systematic optimization of each algorithm is performed by varying the reconstruction parameters, such as the cutoff frequency of the noise filters and the number of iterations. The region of interest (ROI) analysis of the reconstructed phantom is also performed for each algorithm and the results are compared. Additionally, the performance of the image reconstruction methods is compared by calculating the modulation transfer function (MTF). The reconstruction time is also taken into account to choose the optimal algorithm. The analysis is based on GAMOS [3] simulation including the expected CdTe and electronic specifics. PMID:25018777

  3. Ultra-low-dose computed tomographic angiography with model-based iterative reconstruction compared with standard-dose imaging after endovascular aneurysm repair: a prospective pilot study.

    Science.gov (United States)

    Naidu, Sailen G; Kriegshauser, J Scott; Paden, Robert G; He, Miao; Wu, Qing; Hara, Amy K

    2014-12-01

    An ultra-low-dose radiation protocol reconstructed with model-based iterative reconstruction was compared with our standard-dose protocol. This prospective study evaluated 20 men undergoing surveillance-enhanced computed tomography after endovascular aneurysm repair. All patients underwent standard-dose and ultra-low-dose venous phase imaging; images were compared after reconstruction with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Objective measures of aortic contrast attenuation and image noise were averaged. Images were subjectively assessed (1 = worst, 5 = best) for diagnostic confidence, image noise, and vessel sharpness. Aneurysm sac diameter and endoleak detection were compared. Quantitative image noise was 26% less with ultra-low-dose model-based iterative reconstruction than with standard-dose adaptive statistical iterative reconstruction and 58% less than with ultra-low-dose adaptive statistical iterative reconstruction. Average subjective noise scores were not different between ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction (3.8 vs. 4.0, P = .25). Subjective scores for diagnostic confidence were better with standard-dose adaptive statistical iterative reconstruction than with ultra-low-dose model-based iterative reconstruction (4.4 vs. 4.0, P = .002). Vessel sharpness was decreased with ultra-low-dose model-based iterative reconstruction compared with standard-dose adaptive statistical iterative reconstruction (3.3 vs. 4.1, P model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction aneurysm sac diameters were not significantly different (4.9 vs. 4.9 cm); concordance for the presence of endoleak was 100% (P standard-dose technique, an ultra-low-dose model-based iterative reconstruction protocol provides comparable image quality and diagnostic assessment at a 73

  4. Dose reduction in abdominal computed tomography: intraindividual comparison of image quality of full-dose standard and half-dose iterative reconstructions with dual-source computed tomography.

    Science.gov (United States)

    May, Matthias S; Wüst, Wolfgang; Brand, Michael; Stahl, Christian; Allmendinger, Thomas; Schmidt, Bernhard; Uder, Michael; Lell, Michael M

    2011-07-01

    We sought to evaluate the image quality of iterative reconstruction in image space (IRIS) in half-dose (HD) datasets compared with full-dose (FD) and HD filtered back projection (FBP) reconstruction in abdominal computed tomography (CT). To acquire data with FD and HD simultaneously, contrast-enhanced abdominal CT was performed with a dual-source CT system, both tubes operating at 120 kV, 100 ref.mAs, and pitch 0.8. Three different image datasets were reconstructed from the raw data: Standard FD images applying FBP which served as reference, HD images applying FBP and HD images applying IRIS. For the HD data sets, only data from 1 tube detector-system was used. Quantitative image quality analysis was performed by measuring image noise in tissue and air. Qualitative image quality was evaluated according to the European Guidelines on Quality criteria for CT. Additional assessment of artifacts, lesion conspicuity, and edge sharpness was performed. : Image noise in soft tissue was substantially decreased in HD-IRIS (-3.4 HU, -22%) and increased in HD-FBP (+6.2 HU, +39%) images when compared with the reference (mean noise, 15.9 HU). No significant differences between the FD-FBP and HD-IRIS images were found for the visually sharp anatomic reproduction, overall diagnostic acceptability (P = 0.923), lesion conspicuity (P = 0.592), and edge sharpness (P = 0.589), while HD-FBP was rated inferior. Streak artifacts and beam hardening was significantly more prominent in HD-FBP while HD-IRIS images exhibited a slightly different noise pattern. Direct intrapatient comparison of standard FD body protocols and HD-IRIS reconstruction suggest that the latest iterative reconstruction algorithms allow for approximately 50% dose reduction without deterioration of the high image quality necessary for confident diagnosis.

  5. Abdominal CT with model-based iterative reconstruction (MBIR): initial results of a prospective trial comparing ultralow-dose with standard-dose imaging.

    Science.gov (United States)

    Pickhardt, Perry J; Lubner, Meghan G; Kim, David H; Tang, Jie; Ruma, Julie A; del Rio, Alejandro Muñoz; Chen, Guang-Hong

    2012-12-01

    The purpose of this study was to report preliminary results of an ongoing prospective trial of ultralow-dose abdominal MDCT. Imaging with standard-dose contrast-enhanced (n = 21) and unenhanced (n = 24) clinical abdominal MDCT protocols was immediately followed by ultralow-dose imaging of a matched series of 45 consecutively registered adults (mean age, 57.9 years; mean body mass index, 28.5). The ultralow-dose images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Standard-dose series were reconstructed with FBP (reference standard). Image noise was measured at multiple predefined sites. Two blinded abdominal radiologists interpreted randomly presented ultralow-dose images for multilevel subjective image quality (5-point scale) and depiction of organ-based focal lesions. Mean dose reduction relative to the standard series was 74% (median, 78%; range, 57-88%; mean effective dose, 1.90 mSv). Mean multiorgan image noise for low-dose MBIR was 14.7 ± 2.6 HU, significantly lower than standard-dose FBP (28.9 ± 9.9 HU), low-dose FBP (59.2 ± 23.3 HU), and ASIR (45.6 ± 14.1 HU) (p standard-dose FBP. Pooled lesion detection was higher for low-dose MBIR (79.3% [169/213]) compared with low-dose FBP (66.2% [141/213]) and ASIR (62.0% [132/213]) (p < 0.05). MBIR shows great potential for substantially reducing radiation doses at routine abdominal CT. Both FBP and ASIR are limited in this regard owing to reduced image quality and diagnostic capability. Further investigation is needed to determine the optimal dose level for MBIR that maintains adequate diagnostic performance. In general, objective and subjective image quality measurements do not necessarily correlate with diagnostic performance at ultralow-dose CT.

  6. Abdominal CT With Model-Based Iterative Reconstruction (MBIR): Initial Results of a Prospective Trial Comparing Ultralow-Dose With Standard-Dose Imaging

    Science.gov (United States)

    Pickhardt, Perry J.; Lubner, Meghan G.; Kim, David H.; Tang, Jie; Ruma, Julie A.; del Rio, Alejandro Muñoz; Chen, Guang-Hong

    2013-01-01

    OBJECTIVE The purpose of this study was to report preliminary results of an ongoing prospective trial of ultralow-dose abdominal MDCT. SUBJECTS AND METHODS Imaging with standard-dose contrast-enhanced (n = 21) and unenhanced (n = 24) clinical abdominal MDCT protocols was immediately followed by ultralow-dose imaging of a matched series of 45 consecutively registered adults (mean age, 57.9 years; mean body mass index, 28.5). The ultralow-dose images were reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model-based iterative reconstruction (MBIR). Standard-dose series were reconstructed with FBP (reference standard). Image noise was measured at multiple predefined sites. Two blinded abdominal radiologists interpreted randomly presented ultralow-dose images for multilevel subjective image quality (5-point scale) and depiction of organ-based focal lesions. RESULTS Mean dose reduction relative to the standard series was 74% (median, 78%; range, 57–88%; mean effective dose, 1.90 mSv). Mean multiorgan image noise for low-dose MBIR was 14.7 ± 2.6 HU, significantly lower than standard-dose FBP (28.9 ± 9.9 HU), low-dose FBP (59.2 ± 23.3 HU), and ASIR (45.6 ± 14.1 HU) (p ASIR (1.8 ± 0.7) (p ASIR (62.0% [132/213]) (p ASIR are limited in this regard owing to reduced image quality and diagnostic capability. Further investigation is needed to determine the optimal dose level for MBIR that maintains adequate diagnostic performance. In general, objective and subjective image quality measurements do not necessarily correlate with diagnostic performance at ultralow-dose CT. PMID:23169718

  7. Phase-constrained parallel MR image reconstruction.

    Science.gov (United States)

    Willig-Onwuachi, Jacob D; Yeh, Ernest N; Grant, Aaron K; Ohliger, Michael A; McKenzie, Charles A; Sodickson, Daniel K

    2005-10-01

    A generalized method for phase-constrained parallel MR image reconstruction is presented that combines and extends the concepts of partial-Fourier reconstruction and parallel imaging. It provides a framework for reconstructing images employing either or both techniques and for comparing image quality achieved by varying k-space sampling schemes. The method can be used as a parallel image reconstruction with a partial-Fourier reconstruction built in. It can also be used with trajectories not readily handled by straightforward combinations of partial-Fourier and SENSE-like parallel reconstructions, including variable-density, and non-Cartesian trajectories. The phase constraint specifies a better-conditioned inverse problem compared to unconstrained parallel MR reconstruction alone. This phase-constrained parallel MRI reconstruction offers a one-step alternative to the standard combination of homodyne and SENSE reconstructions with the added benefit of flexibility of sampling trajectory. The theory of the phase-constrained approach is outlined, and its calibration requirements and limitations are discussed. Simulations, phantom experiments, and in vivo experiments are presented.

  8. Improved visualization of collateral ligaments of the ankle: multiplanar reconstructions based on standard 2D turbo spin-echo MR images

    Energy Technology Data Exchange (ETDEWEB)

    Duc, Sylvain R.; Mengiardi, Bernard; Pfirrmann, Christian W.A.; Hodler, Juerg; Zanetti, Marco [University Hospital, Balgrist, From the Departments of Radiology, Zurich (Switzerland)

    2007-05-15

    The purpose of the study was to evaluate the visualization of the collateral ankle ligaments on multiplanar reconstructions (MPR) based on standard 2D turbo spin-echo images. Coronal and axial T2-weighted turbo spin-echo and MPR angled parallel to the course of the ligaments of 15 asymptomatic and 15 symptomatic ankles were separately analyzed by two musculoskeletal radiologists. Image quality was assessed in the asymptomatic ankles qualitatively. In the symptomatic ankles interobserver agreement and reader confidence was determined for each ligament. On MPR the tibionavicular and calcaneofibular ligaments were more commonly demonstrated on a single image than on standard MR images (reader 1: 13 versus 0, P=0.002; reader 2: 14 versus 1, P=0.001 and reader 1: 13 versus 2, P=0.001; reader 2: 14 versus 0, P<0.001). The tibionavicular ligament was considered to be better delineated on MPR by reader 1 (12 versus 3, P=0.031). In the symptomatic ankles, reader confidence was greater with MPR for all ligaments except for the tibiocalcanear ligament (both readers) and the anterior and posterior talofibular ligaments (for reader 2). Interobserver agreement was increased with MPR for the tibionavicular ligament. Multiplanar reconstructions of 2D turbo spin-echo images improve the visualization of the tibionavicular and calcaneofibular ligaments and strengthen diagnostic confidence for these ligaments. (orig.)

  9. TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

    Energy Technology Data Exchange (ETDEWEB)

    Nyflot, MJ; Yang, F; Byrd, D; Bowen, SR; Sandison, GA; Kinahan, PE [University of Washington, Seattle, WA (United States)

    2015-06-15

    Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials

  10. Tomographic image reconstruction using training images

    DEFF Research Database (Denmark)

    Soltani, Sara; Andersen, Martin Skovgaard; Hansen, Per Christian

    2017-01-01

    We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a non-negative dictionary based on prototype elements from the training images; this problem is formulated within...

  11. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    DEFF Research Database (Denmark)

    Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell

    2007-01-01

    in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method...... applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR), (2) reconstruction...

  12. Trajectory Auto-Corrected image reconstruction.

    Science.gov (United States)

    Ianni, Julianna D; Grissom, William A

    2016-09-01

    To estimate k-space trajectory errors in non-Cartesian acquisitions and reconstruct distortion-free images, without trajectory measurements or gradient calibrations. The Trajectory Auto-Corrected image Reconstruction method jointly estimates k-space trajectory errors and images, based on SENSE and SPIRiT parallel imaging reconstruction. The underlying idea is that parallel imaging and oversampling in the center of k-space provides data redundancy that can be exploited to simultaneously reconstruct images and correct trajectory errors. Trajectory errors are represented as weighted sums of trajectory-dependent error basis functions, the coefficients of which are estimated using gradient-based optimization. Trajectory Auto-Corrected image Reconstruction was applied to reconstruct images and errors in golden angle radial, center-out radial, and spiral in vivo 7 Tesla brain acquisitions in five subjects. Compared to reconstructions using nominal trajectories, Trajectory auto-corrected image reconstructions contained considerably less blurring and streaking and were of similar quality to images reconstructed using measured k-space trajectories in the center-out radial and spiral cases. Reconstruction cost function reductions and improvements in normalized image gradient squared were also similar to those for images reconstructed using measured trajectories. Trajectory Auto-Corrected image Reconstruction enables non-Cartesian image reconstructions free from trajectory errors without the need for separate gradient calibrations or trajectory measurements. Magn Reson Med 76:757-768, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  13. Method for position emission mammography image reconstruction

    Science.gov (United States)

    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.

  14. Building Reconstruction Using DSM and Orthorectified Images

    Directory of Open Access Journals (Sweden)

    Peter Reinartz

    2013-04-01

    Full Text Available High resolution Digital Surface Models (DSMs produced from airborne laser-scanning or stereo satellite images provide a very useful source of information for automated 3D building reconstruction. In this paper an investigation is reported about extraction of 3D building models from high resolution DSMs and orthorectified images produced from Worldview-2 stereo satellite imagery. The focus is on the generation of 3D models of parametric building roofs, which is the basis for creating Level Of Detail 2 (LOD2 according to the CityGML standard. In particular the building blocks containing several connected buildings with tilted roofs are investigated and the potentials and limitations of the modeling approach are discussed. The edge information extracted from orthorectified image has been employed as additional source of information in 3D reconstruction algorithm. A model driven approach based on the analysis of the 3D points of DSMs in a 2D projection plane is proposed. Accordingly, a building block is divided into smaller parts according to the direction and number of existing ridge lines for parametric building reconstruction. The 3D model is derived for each building part, and finally, a complete parametric model is formed by merging the 3D models of the individual building parts and adjusting the nodes after the merging step. For the remaining building parts that do not contain ridge lines, a prismatic model using polygon approximation of the corresponding boundary pixels is derived and merged to the parametric models to shape the final model of the building. A qualitative and quantitative assessment of the proposed method for the automatic reconstruction of buildings with parametric roofs is then provided by comparing the final model with the existing surface model as well as some field measurements.

  15. Simultaneous maximum a posteriori longitudinal PET image reconstruction

    Science.gov (United States)

    Ellis, Sam; Reader, Andrew J.

    2017-09-01

    Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.

  16. Sparse Image Reconstruction in Computed Tomography

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Sauer

    (CS), have shown significant empirical potential for this purpose. For example, total variation regularized image reconstruction has been shown in some cases to allow reducing x-ray exposure by a factor of 10 or more, while maintaining or even improving image quality compared to conventional...... and limitations of sparse reconstruction methods in CT, in particular in a quantitative sense. For example, relations between image properties such as contrast, structure and sparsity, tolerable noise levels, suficient sampling levels, the choice of sparse reconstruction formulation and the achievable image...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...

  17. Reduced dose CT with model-based iterative reconstruction compared to standard dose CT of the chest, abdomen, and pelvis in oncology patients: intra-individual comparison study on image quality and lesion conspicuity.

    Science.gov (United States)

    Morimoto, Linda Nayeli; Kamaya, Aya; Boulay-Coletta, Isabelle; Fleischmann, Dominik; Molvin, Lior; Tian, Lu; Fisher, George; Wang, Jia; Willmann, Jürgen K

    2017-04-17

    To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging. Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales. Median radiation dose reduction was 46% using RD CT (P image noise across all measured tissue types was lower (P image quality for RD CT was higher (P image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.

  18. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    Energy Technology Data Exchange (ETDEWEB)

    Hellebust, Taran Paulsen [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Tanderup, Kari [Department of Oncology, Aarhus University Hospital, Aarhus (Denmark); Bergstrand, Eva Stabell [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Knutsen, Bjoern Helge [Department of Medical Physics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Roeislien, Jo [Section of Biostatistics, Rikshospital-Radiumhospital Medical Center, Oslo (Norway); Olsen, Dag Rune [Institute for Cancer Research, Rikshospital-Radiumhospital Medical Center, Oslo (Norway)

    2007-08-21

    The purpose of this study is to investigate whether the method of applicator reconstruction and/or the applicator orientation influence the dose calculation to points around the applicator for brachytherapy of cervical cancer with CT-based treatment planning. A phantom, containing a fixed ring applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR) (2) reconstruction in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method was significantly lower (p < 0.05) than for the DR and MPR methods for all but two points. All applicator orientations had similar dose calculation reproducibility. Using library plans for applicator reconstruction gives the most reproducible dose calculation. However, with restrictive guidelines for applicator reconstruction the uncertainties for all methods are low compared to other factors influencing the accuracy of brachytherapy.

  19. Thermographic image reconstruction using ultrasound reconstruction from virtual waves

    CERN Document Server

    Burgholzer, Peter; Gruber, Jürgen; Mayr, Günther

    2016-01-01

    Reconstruction of subsurface features from ultrasound signals measured on the surface is widely used in medicine and non-destructive testing. In this work, we introduce a concept how to use image reconstruction methods known from ultrasonic imaging for thermographic signals, i.e. on the measured temperature evolution on a sample surface. Before using these imaging methods a virtual signal is calculated by applying a transformation to the measured temperature evolution. The virtual signal is calculated locally for every detection point and has the same initial temperature distribution as the measured signal, but is a solution of the wave equation. The introduced transformation can be used for every shape of the detection surface and in every dimension. It describes all the irreversibility of the heat diffusion, which is responsible that the spatial resolution gets worse with increasing depth. Up to now, for thermographic imaging mostly one-dimensional methods, e.g., for depth-profiling were used, which are sui...

  20. Robust sparse image reconstruction of radio interferometric observations with PURIFY

    Science.gov (United States)

    Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves

    2018-01-01

    Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.

  1. Speeding up image reconstruction in computed tomography

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industria...

  2. Building Reconstruction Using DSM and Orthorectified Images

    National Research Council Canada - National Science Library

    Hossein Arefi; Peter Reinartz

    2013-01-01

      High resolution Digital Surface Models (DSMs) produced from airborne laser-scanning or stereo satellite images provide a very useful source of information for automated 3D building reconstruction...

  3. Image Quality of 3rd Generation Spiral Cranial Dual-Source CT in Combination with an Advanced Model Iterative Reconstruction Technique: A Prospective Intra-Individual Comparison Study to Standard Sequential Cranial CT Using Identical Radiation Dose.

    Directory of Open Access Journals (Sweden)

    Holger Wenz

    Full Text Available To prospectively intra-individually compare image quality of a 3rd generation Dual-Source-CT (DSCT spiral cranial CT (cCT to a sequential 4-slice Multi-Slice-CT (MSCT while maintaining identical intra-individual radiation dose levels.35 patients, who had a non-contrast enhanced sequential cCT examination on a 4-slice MDCT within the past 12 months, underwent a spiral cCT scan on a 3rd generation DSCT. CTDIvol identical to initial 4-slice MDCT was applied. Data was reconstructed using filtered backward projection (FBP and 3rd-generation iterative reconstruction (IR algorithm at 5 different IR strength levels. Two neuroradiologists independently evaluated subjective image quality using a 4-point Likert-scale and objective image quality was assessed in white matter and nucleus caudatus with signal-to-noise ratios (SNR being subsequently calculated.Subjective image quality of all spiral cCT datasets was rated significantly higher compared to the 4-slice MDCT sequential acquisitions (p<0.05. Mean SNR was significantly higher in all spiral compared to sequential cCT datasets with mean SNR improvement of 61.65% (p*Bonferroni0.05<0.0024. Subjective image quality improved with increasing IR levels.Combination of 3rd-generation DSCT spiral cCT with an advanced model IR technique significantly improves subjective and objective image quality compared to a standard sequential cCT acquisition acquired at identical dose levels.

  4. Image Reconstruction for Prostate Specific Nuclear Medicine imagers

    Energy Technology Data Exchange (ETDEWEB)

    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.

  5. Variable Weighted Ordered Subset Image Reconstruction Algorithm

    Directory of Open Access Journals (Sweden)

    Jinxiao Pan

    2006-01-01

    Full Text Available We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART to improve the algebraic reconstruction technique (ART and simultaneous algebraic reconstruction technique (SART and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively.

  6. 3D Reconstruction of NMR Images

    Directory of Open Access Journals (Sweden)

    Peter Izak

    2007-01-01

    Full Text Available This paper introduces experiment of 3D reconstruction NMR images scanned from magnetic resonance device. There are described methods which can be used for 3D reconstruction magnetic resonance images in biomedical application. The main idea is based on marching cubes algorithm. For this task was chosen sophistication method by program Vision Assistant, which is a part of program LabVIEW.

  7. Bayesian image reconstruction: Application to emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    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.

  8. Homotopy Based Reconstruction from Acoustic Images

    DEFF Research Database (Denmark)

    Sharma, Ojaswa

    with known geometry. The results of the methods shown here can be used to gain objective knowledge about the reconstructed features. It is envisioned that due to the generic nature of the algorithms developed in this research, domains other than fisheries research can benefit from the reconstruction...... are reconstruction from an organised set of linear cross sections and reconstruction from an arbitrary set of linear cross sections. The first problem is looked upon in the context of acoustic signals wherein the cross sections show a definite geometric arrangement. A reconstruction in this case can take advantage...... of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...

  9. Comparison of applied dose and image quality in staging CT of neuroendocrine tumor patients using standard filtered back projection and adaptive statistical iterative reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Böning, G., E-mail: georg.boening@charite.de [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Schäfer, M.; Grupp, U. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kaul, D. [Department of Radiation Oncology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Kahn, J. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Pavel, M. [Department of Gastroenterology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany); Maurer, M.; Denecke, T.; Hamm, B.; Streitparth, F. [Department of Radiology, Charité, Humboldt-University Medical School, Charitéplatz 1, 10117 Berlin (Germany)

    2015-08-15

    Highlights: • Iterative reconstruction (IR) in staging CT provides equal objective image quality compared to filtered back projection (FBP). • IR delivers excellent subjective quality and reduces effective dose compared to FBP. • In patients with neuroendocrine tumor (NET) or may other hypervascular abdominal tumors IR can be used without scarifying diagnostic confidence. - Abstract: Objective: To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. Methods: A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDI{sub vol}) of each scan was taken from the dose report. Results: ASIR 40% significantly reduced CTDI{sub vol} (10.17 ± 3.06 mGy [FBP], 6.34 ± 2.25 mGy [ASIR] (p < 0.001) by 37.6% and significantly increased CNRs (complete tumor-to-liver, 2.76 ± 1.87 [FBP], 3.2 ± 2.32 [ASIR]) (p < 0.05) (complete tumor-to-muscle, 2.74 ± 2.67 [FBP], 4.31 ± 4.61 [ASIR]) (p < 0.05) compared to FBP. Subjective scoring revealed no significant changes for diagnostic confidence (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]), visibility of suspicious lesion (4.8 ± 0.5 [FBP], 4.8 ± 0.5 [ASIR]) and artifacts (5.0 ± 0 [FBP], 5.0 ± 0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3 ± 0.6 [FBP], 4.0 ± 0.8 [ASIR]) (p < 0.05), contrast (4.4 ± 0.6 [FBP], 4.1 ± 0.8 [ASIR]) (p < 0.001) and visibility of small structures (4.5 ± 0.7 [FBP], 4.3 ± 0.8 [ASIR]) (p < 0

  10. Image reconstruction under non-Gaussian noise

    DEFF Research Database (Denmark)

    Sciacchitano, Federica

    During acquisition and transmission, images are often blurred and corrupted by noise. One of the fundamental tasks of image processing is to reconstruct the clean image from a degraded version. The process of recovering the original image from the data is an example of inverse problem. Due...... in analogue-to-digital conversion, faulty memory locations in hardware. Cauchy noise is characterized by a very impulsive behaviour and it is mainly used to simulate atmospheric and underwater acoustic noise, in radar and sonar applications, biomedical images and synthetic aperture radar images. For both...... that the CM estimate outperforms the MAP estimate, when the error depends on Bregman distances. This PhD project can have many applications in the modern society, in fact the reconstruction of high quality images with less noise and more details enhances the image processing operations, such as edge detection...

  11. Imaging, Reconstruction, And Display Of Corneal Topography

    Science.gov (United States)

    Klyce, Stephen D.; Wilson, Steven E.

    1989-12-01

    The cornea is the major refractive element in the eye; even minor surface distortions can produce a significant reduction in visual acuity. Standard clinical methods used to evaluate corneal shape include keratometry, which assumes the cornea is ellipsoidal in shape, and photokeratoscopy, which images a series of concentric light rings on the corneal surface. These methods fail to document many of the corneal distortions that can degrade visual acuity. Algorithms have been developed to reconstruct the three dimensional shape of the cornea from keratoscope images, and to present these data in the clinically useful display of color-coded contour maps of corneal surface power. This approach has been implemented on a new generation video keratoscope system (Computed Anatomy, Inc.) with rapid automatic digitization of the image rings by a rule-based approach. The system has found clinical use in the early diagnosis of corneal shape anomalies such as keratoconus and contact lens-induced corneal warpage, in the evaluation of cataract and corneal transplant procedures, and in the assessment of corneal refractive surgical procedures. Currently, ray tracing techniques are being used to correlate corneal surface topography with potential visual acuity in an effort to more fully understand the tolerances of corneal shape consistent with good vision and to help determine the site of dysfunction in the visually impaired.

  12. Comparison of applied dose and image quality in staging CT of neuroendocrine tumor patients using standard filtered back projection and adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Böning, G; Schäfer, M; Grupp, U; Kaul, D; Kahn, J; Pavel, M; Maurer, M; Denecke, T; Hamm, B; Streitparth, F

    2015-08-01

    To investigate whether dose reduction via adaptive statistical iterative reconstruction (ASIR) affects image quality and diagnostic accuracy in neuroendocrine tumor (NET) staging. A total of 28 NET patients were enrolled in the study. Inclusion criteria were histologically proven NET and visible tumor in abdominal computed tomography (CT). In an intraindividual study design, the patients underwent a baseline CT (filtered back projection, FBP) and follow-up CT (ASIR 40%) using matched scan parameters. Image quality was assessed subjectively using a 5-grade scoring system and objectively by determining signal-to-noise ratio (SNR) and contrast-to-noise ratios (CNRs). Applied volume computed tomography dose index (CTDIvol) of each scan was taken from the dose report. ASIR 40% significantly reduced CTDIvol (10.17±3.06mGy [FBP], 6.34±2.25mGy [ASIR] (pASIR]) (pASIR]) (pASIR]), visibility of suspicious lesion (4.8±0.5 [FBP], 4.8±0.5 [ASIR]) and artifacts (5.0±0 [FBP], 5.0±0 [ASIR]). ASIR 40% significantly decreased scores for noise (4.3±0.6 [FBP], 4.0±0.8 [ASIR]) (pASIR]) (pASIR]) (pASIR can be used to reduce radiation dose without sacrificing image quality and diagnostic confidence in staging CT of NET patients. This may be beneficial for patients with frequent follow-up and significant cumulative radiation exposure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  13. Imaging standards for smart cards

    Science.gov (United States)

    Ellson, Richard N.; Ray, Lawrence A.

    1996-01-01

    'Smart cards' are plastic cards the size of credit cards which contain integrated circuits for the storage of digital information. The applications of these cards for image storage has been growing as card data capacities have moved from tens of bytes to thousands of bytes. This has prompted the recommendation of standards by the X3B10 committee of ANSI for inclusion in ISO standards for card image storage of a variety of image data types including digitized signatures and color portrait images. This paper reviews imaging requirements of the smart card industry, challenges of image storage for small memory devices, card image communications, and the present status of standards. The paper concludes with recommendations for the evolution of smart card image standards towards image formats customized to the image content and more optimized for smart card memory constraints.

  14. Iterative Reconstruction for Differential Phase Contrast Imaging

    NARCIS (Netherlands)

    Koehler, T.; Brendel, B.; Roessl, E.

    2011-01-01

    Purpose: The purpose of this work is to combine two areas of active research in tomographic x-ray imaging. The first one is the use of iterative reconstruction techniques. The second one is differential phase contrast imaging (DPCI). Method: We derive an SPS type maximum likelihood (ML)

  15. Reconstruction Algorithms in Undersampled AFM Imaging

    DEFF Research Database (Denmark)

    Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen

    2016-01-01

    This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby the s...

  16. Focusing criterion in DHM image reconstruction

    Science.gov (United States)

    Mihailescu, M.; Mihale, N.; Popescu, R. C.; Acasandrei, A.; Paun, I. A.; Dinescu, M.; Scarlat, E.

    2015-02-01

    This study is presenting the theoretical approach and the practical results of a precise activity involved in the hologram reconstruction in order to find the optimally focused image of MG63 osteoblast-like cells cultivated on polymeric flat substrates. The morphology and dynamic of the cell is investigated by digital holographic microscopy (DHM) technique. The reconstruction is digitally performed using an algorithm based on the scalar theory of diffraction in the Fresnel approximation. The quality of the 3D images of the cells is crucially depending on the focusing capability of the reconstruction chain to fit the parameters of the optical recorder, particularly the focusing value. Our proposal to find the focused image is based on the images decomposition on gray levels and their histogram analysis. More precisely the focusing criterion is based on the evaluation of the form of this distribution.

  17. Techniques in Iterative Proton CT Image Reconstruction

    CERN Document Server

    Penfold, Scott

    2015-01-01

    This is a review paper on some of the physics, modeling, and iterative algorithms in proton computed tomography (pCT) image reconstruction. The primary challenge in pCT image reconstruction lies in the degraded spatial resolution resulting from multiple Coulomb scattering within the imaged object. Analytical models such as the most likely path (MLP) have been proposed to predict the scattered trajectory from measurements of individual proton location and direction before and after the object. Iterative algorithms provide a flexible tool with which to incorporate these models into image reconstruction. The modeling leads to a large and sparse linear system of equations that can efficiently be solved by projection methods-based iterative algorithms. Such algorithms perform projections of the iterates onto the hyperlanes that are represented by the linear equations of the system. They perform these projections in possibly various algorithmic structures, such as block-iterative projections (BIP), string-averaging...

  18. Proton computed tomography images with algebraic reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Bruzzi, M. [Physics and Astronomy Department, University of Florence, Florence (Italy); Civinini, C.; Scaringella, M. [INFN - Florence Division, Florence (Italy); Bonanno, D. [INFN - Catania Division, Catania (Italy); Brianzi, M. [INFN - Florence Division, Florence (Italy); Carpinelli, M. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Cirrone, G.A.P.; Cuttone, G. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Presti, D. Lo [INFN - Catania Division, Catania (Italy); Physics and Astronomy Department, University of Catania, Catania (Italy); Maccioni, G. [INFN – Cagliari Division, Cagliari (Italy); Pallotta, S. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Randazzo, N. [INFN - Catania Division, Catania (Italy); Romano, F. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Sipala, V. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Talamonti, C. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Vanzi, E. [Fisica Sanitaria, Azienda Ospedaliero-Universitaria Senese, Siena (Italy)

    2017-02-11

    A prototype of proton Computed Tomography (pCT) system for hadron-therapy has been manufactured and tested in a 175 MeV proton beam with a non-homogeneous phantom designed to simulate high-contrast material. BI-SART reconstruction algorithms have been implemented with GPU parallelism, taking into account of most likely paths of protons in matter. Reconstructed tomography images with density resolutions r.m.s. down to ~1% and spatial resolutions <1 mm, achieved within processing times of ~15′ for a 512×512 pixels image prove that this technique will be beneficial if used instead of X-CT in hadron-therapy.

  19. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    The aim of this project has been to implement a software system, that is able to create a 3-D reconstruction from two or more 2-D photographic images made from different positions. The height is determined from the disparity difference of the images. The general purpose of the system is mapping o......, where various methods have been tested in order to optimize the performance. The match results are used in the reconstruction part to establish a 3-D digital representation and finally, different presentation forms are discussed....

  20. Image Reconstruction Image reconstruction by using local inverse for full field of view

    CERN Document Server

    Yang, Kang; Yang, Xintie; Zhao, Shuang-Ren

    2015-01-01

    The iterative refinement method (IRM) has been very successfully applied in many different fields for examples the modern quantum chemical calculation and CT image reconstruction. It is proved that the refinement method can create an exact inverse from an approximate inverse with a few iterations. The IRM has been used in CT image reconstruction to lower the radiation dose. The IRM utilize the errors between the original measured data and the recalculated data to correct the reconstructed images. However if it is not smooth inside the object, there often is an over-correction along the boundary of the organs in the reconstructed images. The over-correction increase the noises especially on the edges inside the image. One solution to reduce the above mentioned noises is using some kind of filters. Filtering the noise before/after/between the image reconstruction processing. However filtering the noises also means reduce the resolution of the reconstructed images. The filtered image is often applied to the imag...

  1. Image Superresolution Reconstruction via Granular Computing Clustering

    Directory of Open Access Journals (Sweden)

    Hongbing Liu

    2014-01-01

    Full Text Available The problem of generating a superresolution (SR image from a single low-resolution (LR input image is addressed via granular computing clustering in the paper. Firstly, and the training images are regarded as SR image and partitioned into some SR patches, which are resized into LS patches, the training set is composed of the SR patches and the corresponding LR patches. Secondly, the granular computing (GrC clustering is proposed by the hypersphere representation of granule and the fuzzy inclusion measure compounded by the operation between two granules. Thirdly, the granule set (GS including hypersphere granules with different granularities is induced by GrC and used to form the relation between the LR image and the SR image by lasso. Experimental results showed that GrC achieved the least root mean square errors between the reconstructed SR image and the original image compared with bicubic interpolation, sparse representation, and NNLasso.

  2. Quantitative thermoacoustic image reconstruction of conductivity profiles

    Science.gov (United States)

    Ogunlade, Olumide; Cox, Ben; Beard, Paul

    2012-02-01

    A numerical inversion scheme for recovering a map of the absolute conductivity from the absorbed power density map that is conventionally reconstructed in thermacoustic imaging is described. This offers the prospect of obtaining an image that is more closely related to the underlying tissue structure and physiology. The inversion scheme employs a full 3D full wave model of electromagnetic propagation in tissue which is iteratively fitted to the measured absorbed power density map using a simple recursive method. The reconstruction is demonstrated numerically using three examples of absorbers of varying geometries, tissue realistic complex permittivity values and noise. In these examples, the reconstruction is shown to rapidly converge to within good estimates of the true conductivity in less than 20 iterations.

  3. Point spread function based image reconstruction in optical projection tomography

    Science.gov (United States)

    Trull, Anna K.; van der Horst, Jelle; Palenstijn, Willem Jan; van Vliet, Lucas J.; van Leeuwen, Tristan; Kalkman, Jeroen

    2017-10-01

    As a result of the shallow depth of focus of the optical imaging system, the use of standard filtered back projection in optical projection tomography causes space-variant tangential blurring that increases with the distance to the rotation axis. We present a novel optical tomographic image reconstruction technique that incorporates the point spread function of the imaging lens in an iterative reconstruction. The technique is demonstrated using numerical simulations, tested on experimental optical projection tomography data of single fluorescent beads, and applied to high-resolution emission optical projection tomography imaging of an entire zebrafish larva. Compared to filtered back projection our results show greatly reduced radial and tangential blurring over the entire 5.2×5.2 mm2 field of view, and a significantly improved signal to noise ratio.

  4. Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

    Science.gov (United States)

    Qiu, W; Titley-Peloquin, D; Soleimani, M

    2012-11-01

    Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  5. Image reconstruction for bioluminescence tomography

    Science.gov (United States)

    Jiang, Ming; Wang, Ge

    2004-10-01

    Motivated by bioluminescent imaging needs for studies on gene therapy and other applications in the mouse models, a bioluminescence tomography (BLT) system is being developed by our group. While the forward imaging model is described by the diffusion approximation, BLT is the inverse problem to recover an internal bioluminescent source distribution subject to Cauchy data for the diffusion equation. This inverse source problem is ill-posed and does not yield the unique solution in the general case. The uniqueness problem under practical constraints was recently studied by our group. It was found that all the inverse source solutions can be expressed as the unique minimal energy source solution plus a nonradiating source. We demonstrate that the minimal energy source solution is not physically favorable for bioluminescence tomography, although the minimal energy constraint is utilized in other applications. To find a physically meaningful unique solution, adequate prior knowledge must be utilized. Here we propose two iterative approaches in this work. The first one is a variant of the well-known EM algorithm. The second one is based on the Landweber scheme. Either of the methods is suitable for incorporating knowledge-based constraints. We discuss several issues related to the implementation of these methods, including the initial guess and stopping criteria. Also, we report our numerical simulation results to demonstrate the feasibility of bioluminescence tomography.

  6. Undersampled MR Image Reconstruction with Data-Driven Tight Frame

    National Research Council Canada - National Science Library

    Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong

    2015-01-01

    .... With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method...

  7. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR).

    Science.gov (United States)

    Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S

    2015-01-01

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

  8. Reconstruction of Undersampled Atomic Force Microscopy Images

    DEFF Research Database (Denmark)

    Jensen, Tobias Lindstrøm; Arildsen, Thomas; Østergaard, Jan

    2013-01-01

    Atomic force microscopy (AFM) is one of the most advanced tools for high-resolution imaging and manipulation of nanoscale matter. Unfortunately, standard AFM imaging requires a timescale on the order of seconds to minutes to acquire an image which makes it complicated to observe dynamic processes...

  9. Performance-based assessment of reconstructed images

    Energy Technology Data Exchange (ETDEWEB)

    Hanson, Kenneth [Los Alamos National Laboratory

    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.

  10. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei

    2015-07-26

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.

  11. Real-time cardiac magnetic resonance cine imaging with sparse sampling and iterative reconstruction for left-ventricular measures: Comparison with gold-standard segmented steady-state free precession.

    Science.gov (United States)

    Camargo, Gabriel C; Erthal, Fernanda; Sabioni, Leticia; Penna, Filipe; Strecker, Ralph; Schmidt, Michaela; Zenge, Michael O; Lima, Ronaldo de S L; Gottlieb, Ilan

    2017-05-01

    Segmented cine imaging with a steady-state free-precession sequence (Cine-SSFP) is currently the gold standard technique for measuring ventricular volumes and mass, but due to multi breath-hold (BH) requirements, it is prone to misalignment of consecutive slices, time consuming and dependent on respiratory capacity. Real-time cine avoids those limitations, but poor spatial and temporal resolution of conventional sequences has prevented its routine application. We sought to examine the accuracy and feasibility of a newly developed real-time sequence with aggressive under-sampling of k-space using sparse sampling and iterative reconstruction (Cine-RT). Stacks of short-axis cines were acquired covering both ventricles in a 1.5T system using gold standard Cine-SSFP and Cine-RT. Acquisition parameters for Cine-SSFP were: acquisition matrix of 224×196, temporal resolution of 39ms, retrospective gating, with an average of 8 heartbeats per slice and 1-2 slices/BH. For Cine-RT: acquisition matrix of 224×196, sparse sampling net acceleration factor of 11.3, temporal resolution of 41ms, prospective gating, real-time acquisition of 1 heart-beat/slice and all slices in one BH. LV contours were drawn at end diastole and systole to derive LV volumes and mass. Forty-one consecutive patients (15 male; 41±17years) in sinus rhythm were successfully included. All images from Cine-SSFP and Cine-RT were considered to have excellent quality. Cine-RT-derived LV volumes and mass were slightly underestimated but strongly correlated with gold standard Cine-SSFP. Inter- and intra-observer analysis presented similar results between both sequences. Cine-RT featuring sparse sampling and iterative reconstruction can achieve spatial and temporal resolution equivalent to Cine-SSFP, providing excellent image quality, with similar precision measurements and highly correlated and only slightly underestimated volume and mass values. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Image-reconstruction methods in positron tomography

    CERN Document Server

    Townsend, David W; CERN. Geneva

    1993-01-01

    Physics and mathematics for medical imaging In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-rays but also for studies which explore the functional status of the body using positron-emitting radioisotopes and nuclear magnetic resonance. Mathematical methods which enable three-dimentional distributions to be reconstructed from projection data acquired by radiation detectors suitably positioned around the patient will be described in detail. The lectures will trace the development of medical imaging from simpleradiographs to the present-day non-invasive measurement of in vivo boichemistry. Powerful techniques to correlate anatomy and function that are cur...

  13. Image reconstruction for optical tomography using photon density waves

    Energy Technology Data Exchange (ETDEWEB)

    Khalaf, R

    1999-08-01

    Diagnostic imaging makes use of different kinds of radiation. A recent type of imaging using near-infrared light is thought to be a safer and less-expensive method of in-vivo imaging. Near infra-red light can penetrate biological tissue to certain depths. The problem of using near infrared light for imaging, is that the scattering of the photons dominates absorption, causing difficulties in the reconstruction model on which biomedical optical imaging depends crucially. The aim of this thesis is to develop and investigate the performance of a reconstruction algorithm in the frequency domain which allows fast and efficient reconstruction of the image of a limb, or an optical phantom. The forward problem of the propagation of photons inside biological tissue is modelled using the Diffusion Approximation theory solved by the finite element method. Values of DC intensity, phase shift and modulation depth at the boundary as functions of the diffusion and absorption coefficients are given. The inverse model is formulated as a nonlinear least-squares optimisation problem. The Truncated Newton method with Trust region is used to determine the optical properties. Reverse differentiation is used to calculate the error function because of its speed advantage over forward differentiation. A sensitivity analysis is performed to investigate the simultaneous reconstruction of the diffusion and absorption coefficients. The use of a combined error function of DC intensity, phase and modulation prove to be the most successful at recovering the optical parameters. The ability to distinguish between object size and size of optical parameter is also investigated. Contrast, mean and standard deviation are used as measures of the performance of the reconstruction algorithm. A Tikhonov regularisation method was used to improve ill-conditioning and behaviour in the presence of noise. An investigation of the optimal regularisation parameter is undertaken with the addition of noise to the

  14. Lobe based image reconstruction in Electrical Impedance Tomography.

    Science.gov (United States)

    Schullcke, Benjamin; Gong, Bo; Krueger-Ziolek, Sabine; Tawhai, Merryn; Adler, Andy; Mueller-Lisse, Ullrich; Moeller, Knut

    2017-02-01

    Electrical Impedance Tomography (EIT) is an imaging modality used to generate two-dimensional cross-sectional images representing impedance change in the thorax. The impedance of lung tissue changes with change in air content of the lungs; hence, EIT can be used to examine regional lung ventilation in patients with abnormal lungs. In lung EIT, electrodes are attached around the circumference of the thorax to inject small alternating currents and measure resulting voltages. In contrast to X-ray computed tomography (CT), EIT images do not depict a thorax slice of well defined thickness, but instead visualize a lens-shaped region around the electrode plane, which results from diffuse current propagation in the thorax. Usually, this is considered a drawback, since image interpretation is impeded if 'off-plane' conductivity changes are projected onto the reconstructed two-dimensional image. In this paper we describe an approach that takes advantage of current propagation below and above the electrode plane. The approach enables estimation of the individual conductivity change in each lung lobe from boundary voltage measurements. This could be used to monitor disease progression in patients with obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF) and to obtain a more comprehensive insight into the pathophysiology of the lung. Electrode voltages resulting from different conductivities in each lung lobe were simulated utilizing a realistic 3D finite element model (FEM) of the human thorax and the lungs. Overall 200 different patterns of conductivity change were simulated. A 'lobe reconstruction' algorithm was developed, applying patient-specific anatomical information in the reconstruction process. A standard EIT image reconstruction algorithm and the proposed 'lobe reconstruction' algorithm were used to estimate conductivity change in the lobes. The agreement between simulated and reconstructed conductivity change in

  15. Improved Liver Lesion Conspicuity With Iterative Reconstruction in Computed Tomography Imaging.

    Science.gov (United States)

    Jensen, Kristin; Andersen, Hilde Kjernlie; Tingberg, Anders; Reisse, Claudius; Fosse, Erik; Martinsen, Anne Catrine T

    2016-01-01

    Studies on iterative reconstruction techniques on computed tomographic (CT) scanners show reduced noise and changed image texture. The purpose of this study was to address the possibility of dose reduction and improved conspicuity of lesions in a liver phantom for different iterative reconstruction algorithms. An anthropomorphic upper abdomen phantom, specially designed for receiver operating characteristic analysis was scanned with 2 different CT models from the same vendor, GE CT750 HD and GE Lightspeed VCT. Images were obtained at 3 dose levels, 5, 10, and 15mGy, and reconstructed with filtered back projection (FBP), and 2 different iterative reconstruction algorithms; adaptive statistical iterative reconstruction and Veo. Overall, 5 interpreters evaluated the images and receiver operating characteristic analysis was performed. Standard deviation and the contrast to noise ratio were measured. Veo image reconstruction resulted in larger area under curves compared with those adaptive statistical iterative reconstruction and FBP image reconstruction for given dose levels. For the CT750 HD, iterative reconstruction at the 10mGy dose level resulted in larger or similar area under curves compared with FBP at the 15mGy dose level (0.88-0.95 vs 0.90). This was not shown for the Lightspeed VCT (0.83-0.85 vs 0.92). The results in this study indicate that the possibility for radiation dose reduction using iterative reconstruction techniques depends on both reconstruction technique and the CT scanner model used. Copyright © 2016 Elsevier Inc. All rights reserved.

  16. Structure Assisted Compressed Sensing Reconstruction of Undersampled AFM Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Arildsen, Thomas; Larsen, Torben

    2017-01-01

    of the full image of it, and then use advanced computational techniques to reconstruct the remaining part of the image whenever this is possible. Our initial experiments have shown that it is possible to leverage inherent structure in acquired AFM images to improve image reconstruction. Thus, we have studied...... structure in the discrete cosine transform coefficients of typical AFM images. Based on this study, we propose a generic support structure model that may be used to improve the quality of the reconstructed AFM images. Furthermore, we propose a modification to the established iterative thresholding...... reconstruction algorithms that enables the use of our proposed structure model in the reconstruction process. Through a large set of reconstructions, the general reconstruction capability improvement achievable using our structured model is shown both quantitatively and qualitatively. Specifically, our...

  17. Comparison of power spectra for tomosynthesis projections and reconstructed images

    Energy Technology Data Exchange (ETDEWEB)

    Engstrom, Emma; Reiser, Ingrid; Nishikawa, Robert [Royal Institute of Technology, 11231 Stockholm (Sweden); Department of Radiology, University of Chicago, Chicago 60637 (United States)

    2009-05-15

    Burgess et al. [Med. Phys. 28, 419-437 (2001)] showed that the power spectrum of mammographic breast background follows a power law and that lesion detectability is affected by the power-law exponent {beta} which measures the amount of structure in the background. Following the study of Burgess et al., the authors measured and compared the power-law exponent of mammographic backgrounds in tomosynthesis projections and reconstructed slices to investigate the effect of tomosynthesis imaging on background structure. Our data set consisted of 55 patient cases. For each case, regions of interest (ROIs) were extracted from both projection images and reconstructed slices. The periodogram of each ROI was computed by taking the squared modulus of the Fourier transform of the ROI. The power-law exponent was determined for each periodogram and averaged across all ROIs extracted from all projections or reconstructed slices for each patient data set. For the projections, the mean {beta} averaged across the 55 cases was 3.06 (standard deviation of 0.21), while it was 2.87 (0.24) for the corresponding reconstructions. The difference in {beta} for a given patient between the projection ROIs and the reconstructed ROIs averaged across the 55 cases was 0.194, which was statistically significant (p<0.001). The 95% CI for the difference between the mean value of {beta} for the projections and reconstructions was [0.170, 0.218]. The results are consistent with the observation that the amount of breast structure in the tomosynthesis slice is reduced compared to projection mammography and that this may lead to improved lesion detectability.

  18. Real-time SPARSE-SENSE cardiac cine MR imaging: optimization of image reconstruction and sequence validation.

    Science.gov (United States)

    Goebel, Juliane; Nensa, Felix; Bomas, Bettina; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai

    2016-12-01

    Improved real-time cardiac magnetic resonance (CMR) sequences have currently been introduced, but so far only limited practical experience exists. This study aimed at image reconstruction optimization and clinical validation of a new highly accelerated real-time cine SPARSE-SENSE sequence. Left ventricular (LV) short-axis stacks of a real-time free-breathing SPARSE-SENSE sequence with high spatiotemporal resolution and of a standard segmented cine SSFP sequence were acquired at 1.5 T in 11 volunteers and 15 patients. To determine the optimal iterations, all volunteers' SPARSE-SENSE images were reconstructed using 10-200 iterations, and contrast ratios, image entropies, and reconstruction times were assessed. Subsequently, the patients' SPARSE-SENSE images were reconstructed with the clinically optimal iterations. LV volumetric values were evaluated and compared between both sequences. Sufficient image quality and acceptable reconstruction times were achieved when using 80 iterations. Bland-Altman plots and Passing-Bablok regression showed good agreement for all volumetric parameters. 80 iterations are recommended for iterative SPARSE-SENSE image reconstruction in clinical routine. Real-time cine SPARSE-SENSE yielded comparable volumetric results as the current standard SSFP sequence. Due to its intrinsic low image acquisition times, real-time cine SPARSE-SENSE imaging with iterative image reconstruction seems to be an attractive alternative for LV function analysis. • A highly accelerated real-time CMR sequence using SPARSE-SENSE was evaluated. • SPARSE-SENSE allows free breathing in real-time cardiac cine imaging. • For clinically optimal SPARSE-SENSE image reconstruction, 80 iterations are recommended. • Real-time SPARSE-SENSE imaging yielded comparable volumetric results as the reference SSFP sequence. • The fast SPARSE-SENSE sequence is an attractive alternative to standard SSFP sequences.

  19. Iterative Self-Dual Reconstruction on Radar Image Recovery

    Energy Technology Data Exchange (ETDEWEB)

    Martins, Charles; Medeiros, Fatima; Ushizima, Daniela; Bezerra, Francisco; Marques, Regis; Mascarenhas, Nelson

    2010-05-21

    Imaging systems as ultrasound, sonar, laser and synthetic aperture radar (SAR) are subjected to speckle noise during image acquisition. Before analyzing these images, it is often necessary to remove the speckle noise using filters. We combine properties of two mathematical morphology filters with speckle statistics to propose a signal-dependent noise filter to multiplicative noise. We describe a multiscale scheme that preserves sharp edges while it smooths homogeneous areas, by combining local statistics with two mathematical morphology filters: the alternating sequential and the self-dual reconstruction algorithms. The experimental results show that the proposed approach is less sensitive to varying window sizes when applied to simulated and real SAR images in comparison with standard filters.

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

    Science.gov (United States)

    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

  1. Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality.

    Science.gov (United States)

    Yanagawa, Masahiro; Gyobu, Tomoko; Leung, Ann N; Kawai, Misa; Kawata, Yutaka; Sumikawa, Hiromitsu; Honda, Osamu; Tomiyama, Noriyuki

    2014-06-01

    To compare quality of ultra-low-dose thin-section computed tomography (CT) images of the lung reconstructed using model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASIR) to filtered back projection (FBP) and to determine the minimum tube current-time product on MBIR images by comparing to standard-dose FBP images. Ten cadaveric lungs were scanned using 120 kVp and four different tube current-time products (8, 16, 32, and 80 mAs). Thin-section images were reconstructed using MBIR, three ASIR blends (30%, 60%, and 90%), and FBP. Using the 8-mAs data, side-to-side comparison of the four iterative reconstruction image sets to FBP was performed by two independent observers who evaluated normal and abnormal findings, subjective image noise, streak artifact, and overall image quality. Image noise was also measured quantitatively. Subsequently, 8-, 16-, and 32-mAs MBIR images were compared to standard-dose FBP images. Comparisons of image sets were analyzed using the Wilcoxon signed rank test with Bonferroni correction. At 8 mAs, MBIR images were significantly better (P reconstruction techniques except in evaluation of interlobular septal thickening. Each set of low-dose MBIR images had significantly lower (P < .001) subjective and objective noise and streak artifacts than standard-dose FBP images. Conspicuity and visibility of normal and abnormal findings were not significantly different between 16-mAs MBIR and 80-mAs FBP images except in identification of intralobular reticular opacities. MBIR imaging shows higher overall quality with lower noise and streak artifacts than ASIR or FBP imaging, resulting in nearly 80% dose reduction without any degradations of overall image quality. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  2. Cardiac Image Reconstruction via Nonlinear Motion Correction Based on Partial Angle Reconstructed Images.

    Science.gov (United States)

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

    2017-05-01

    Even though the X-ray Computed Tomography (CT) scan is considered suitable for fast imaging, motion-artifact-free cardiac imaging is still an important issue, because the gantry rotation speed is not fast enough compared with the heart motion. To obtain a heart image with less motion artifacts, a motion estimation (ME) and motion compensation (MC) approach is usually adopted. In this paper, we propose an ME/MC algorithm that can estimate a nonlinear heart motion model from a sinogram with a rotation angle of less than 360°. In this algorithm, we first assume the heart motion to be nonrigid but linear, and thereby estimate an initial 4-D motion vector field (MVF) during a half rotation by using conjugate partial angle reconstructed images, as in our previous ME/MC algorithm. We then refine the MVF to determine a more accurate nonlinear MVF by maximizing the information potential of a motion-compensated image. Finally, MC is performed by incorporating the determined MVF into the image reconstruction process, and a time-resolved heart image is obtained. By using a numerical phantom, a physical cardiac phantom, and an animal data set, we demonstrate that the proposed algorithm can noticeably improve the image quality by reducing motion artifacts throughout the image.

  3. Effects of acquisition time and reconstruction algorithm on image quality, quantitative parameters, and clinical interpretation of myocardial perfusion imaging

    DEFF Research Database (Denmark)

    Enevoldsen, Lotte H; Menashi, Changez A K; Andersen, Ulrik B

    2013-01-01

    -RR) and for quantitative analysis (FT-FBP, HT-FBP, and HT-RR). The datasets were analyzed using commercially available QGS/QPS software and read by two observers evaluating image quality and clinical interpretation. Image quality was assessed on a 10-cm visual analog scale score. RESULTS: HT imaging was associated......BACKGROUND: Recently introduced iterative reconstruction algorithms with resolution recovery (RR) and noise-reduction technology seem promising for reducing scan time or radiation dose without loss of image quality. However, the relative effects of reduced acquisition time and reconstruction...... with loss of image quality that was compensated for by RR reconstruction. HT imaging was also associated with increasing perfusion defect extents, an effect more pronounced using RR than FBP reconstruction. Compared to standard FT-FBP, HT-RR significantly reduced left ventricular volumes whereas HT...

  4. Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner.

    Science.gov (United States)

    Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R; Badawi, Ramsey D; Qi, Jinyi

    2017-03-21

    The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq 18 F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.

  5. Quantitative image reconstruction for total-body PET imaging using the 2-meter long EXPLORER scanner

    Science.gov (United States)

    Zhang, Xuezhu; Zhou, Jian; Cherry, Simon R.; Badawi, Ramsey D.; Qi, Jinyi

    2017-03-01

    The EXPLORER project aims to build a 2 meter long total-body PET scanner, which will provide extremely high sensitivity for imaging the entire human body. It will possess a range of capabilities currently unavailable to state-of-the-art clinical PET scanners with a limited axial field-of-view. The huge number of lines-of-response (LORs) of the EXPLORER poses a challenge to the data handling and image reconstruction. The objective of this study is to develop a quantitative image reconstruction method for the EXPLORER and compare its performance with current whole-body scanners. Fully 3D image reconstruction was performed using time-of-flight list-mode data with parallel computation. To recover the resolution loss caused by the parallax error between crystal pairs at a large axial ring difference or transaxial radial offset, we applied an image domain resolution model estimated from point source data. To evaluate the image quality, we conducted computer simulations using the SimSET Monte-Carlo toolkit and XCAT 2.0 anthropomorphic phantom to mimic a 20 min whole-body PET scan with an injection of 25 MBq 18F-FDG. We compare the performance of the EXPLORER with a current clinical scanner that has an axial FOV of 22 cm. The comparison results demonstrated superior image quality from the EXPLORER with a 6.9-fold reduction in noise standard deviation comparing with multi-bed imaging using the clinical scanner.

  6. Images from Bits: Non-Iterative Image Reconstruction for Quanta Image Sensors

    Directory of Open Access Journals (Sweden)

    Stanley H. Chan

    2016-11-01

    Full Text Available A quanta image sensor (QIS is a class of single-photon imaging devices that measure light intensity using oversampled binary observations. Because of the stochastic nature of the photon arrivals, data acquired by QIS is a massive stream of random binary bits. The goal of image reconstruction is to recover the underlying image from these bits. In this paper, we present a non-iterative image reconstruction algorithm for QIS. Unlike existing reconstruction methods that formulate the problem from an optimization perspective, the new algorithm directly recovers the images through a pair of nonlinear transformations and an off-the-shelf image denoising algorithm. By skipping the usual optimization procedure, we achieve orders of magnitude improvement in speed and even better image reconstruction quality. We validate the new algorithm on synthetic datasets, as well as real videos collected by one-bit single-photon avalanche diode (SPAD cameras.

  7. Regularized Image Reconstruction for Ultrasound Attenuation Transmission Tomography

    Directory of Open Access Journals (Sweden)

    I. Peterlik

    2008-06-01

    Full Text Available The paper is focused on ultrasonic transmission tomography as a potential medical imaging modality, namely for breast cancer diagnosis. Ultrasound attenuation coefficient is one of the tissue parameters which are related to the pathological tissue state. A technique to reconstruct images of attenuation distribution is presented. Furthermore, an alternative to the commonly used filtered backprojection or algebraic reconstruction techniques is proposed. It is based on regularization of the image reconstruction problem which imposes smoothness in the resulting images while preserving edges. The approach is analyzed on synthetic data sets. The results show that it stabilizes the image restoration by compensating for main sources of estimation errors in this imaging modality.

  8. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  9. Precision Pointing Reconstruction and Geometric Metadata Generation for Cassini Images

    Science.gov (United States)

    French, R. S.; Showalter, M. R.; Gordon, M. K.

    2017-06-01

    We are reconstructing accurate pointing for 400,000 images taken by Cassini at Saturn. The results will be provided to the public along with per-pixel metadata describing precise image contents such as geographical location and viewing geometry.

  10. Development and evaluation of QSPECT open-source software for the iterative reconstruction of SPECT images.

    Science.gov (United States)

    Loudos, George K; Papadimitroulas, Panagiotis; Zotos, Panteleimon; Tsougos, Ioannis; Georgoulias, Panagiotis

    2010-06-01

    In this study open-source software (QSPECT) suitable for the iterative reconstruction of single-photon emission computed tomography (SPECT) data is presented. QSPECT implements maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms in a user-friendly graphical interface. The software functionality is described and validation results are presented. Maximum likelihood expectation maximization and ordered subsets expectation maximization algorithms are implemented in C++. The Qt toolkit, a standard C++ framework for developing high-performance cross-platform applications, has been used for the graphical user interface development. QSPECT is tested using original projection data from two clinical SPECT systems: (i) APEX SPX-6/6HR and (ii) Millennium MG. Phantom experiments were carried out to evaluate the quality of reconstructed images in terms of (i) spatial resolution, (ii) sensitivity to activity variations, and (iii) the presence of scatter media. A cardiac phantom was used to simulate a normal and abnormal scenario. Finally, clinical cardiac SPECT images were reconstructed. In all cases, QSPECT results were compared with the clinical systems reconstruction software that uses the standard filtered backprojection algorithm. The reconstructed images show that QSPECT, when compared with standard clinical reconstruction, provides images with higher contrast, reduced background, and better separation of small sources located in small distances. In addition, reconstruction with QSPECT provides more quantitative images, and reduces the background created by scatter media. Finally, the phantom and clinical cardiac images are reconstructed with similar quality. QSPECT is a freely distributed, open-source standalone application that provides real-time, high-quality SPECT images. The software can be further modified to improve reconstruction algorithms, and include more correction techniques, such as, scatter and attenuation

  11. Comparison of clinical and physics scoring of PET images when image reconstruction parameters are varied.

    Science.gov (United States)

    Walsh, C; Johnston, C; Sheehy, N; O' Reilly, G

    2013-02-01

    In this study the quantitative and qualitative image quality (IQ) measurements with clinical judgement of IQ in positron emission tomography (PET) were compared. The limitations of IQ metrics and the proposed criteria of acceptability for PET scanners are discussed. Phantom and patient images were reconstructed using seven different iterative reconstruction protocols. For each reconstructed set of images, IQ was scored based both on the visual analysis and on the quantitative metrics. The quantitative physics metrics did not rank the reconstruction protocols in the same order as the clinicians' scoring of perceived IQ (R(s)=-0.54). Better agreement was achieved when comparing the clinical perception of IQ to the physicist's visual assessment of IQ in the phantom images (R(s)=+0.59). The closest agreement was seen between the quantitative physics metrics and the measurement of the standard uptake values (SUVs) in small tumours (R(s)=+0.92). Given the disparity between the clinical perception of IQ and the physics metrics a cautious approach to use of IQ measurements for determining suspension levels is warranted.

  12. 3D Reconstruction of NMR Images by LabVIEW

    Directory of Open Access Journals (Sweden)

    Peter IZAK

    2007-01-01

    Full Text Available This paper introduces the experiment of 3D reconstruction NMR images via virtual instrumentation - LabVIEW. The main idea is based on marching cubes algorithm and image processing implemented by module of Vision assistant. The two dimensional images shot by the magnetic resonance device provide information about the surface properties of human body. There is implemented algorithm which can be used for 3D reconstruction of magnetic resonance images in biomedical application.

  13. Hybrid iterative reconstruction algorithm improves image quality in craniocervical CT angiography.

    Science.gov (United States)

    Löve, Askell; Siemund, Roger; Höglund, Peter; Ramgren, Birgitta; Undrén, Per; Björkman-Burtscher, Isabella M

    2013-12-01

    The purpose of this study was to evaluate the potential of a hybrid iterative reconstruction algorithm for improving image quality in craniocervical CT angiography (CTA) and to assess observer performance. Thirty patients (mean age, 58 years; range 16-80 years) underwent standard craniocervical CTA (volume CT dose index, 6.8 mGy, 2.8 mSv). Images were reconstructed using both filtered back projection (FBP) and a hybrid iterative reconstruction algorithm. Five neuroradiologists assessed general image quality and delineation of the vessel lumen in seven arterial segments using a 4-grade scale. Interobserver and intraobserver variability were determined. Mean attenuation and noise were measured and signal-to-noise and contrast-to-noise ratios calculated. Descriptive statistics are presented and data analyzed using linear mixed-effects models. In pooled data, image quality in iterative reconstruction was graded superior to FBP regarding all five quality criteria (p Iterative reconstruction resulted in elimination of arterial segments graded poor. Interobserver percentage agreement was significantly better (p = 0.024) for iterative reconstruction (69%) than for FBP (66%) but worse than intraobserver percentage agreement (mean, 79%). Noise levels, signal-to-noise ratio, and contrast-to-noise ratio were significantly (p iterative reconstruction at all measured levels. The iterative reconstruction algorithm significantly improves image quality in craniocervical CT, especially at the thoracic inlet. Despite careful study design, considerable interobserver and intraobserver variability was noted.

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

    OpenAIRE

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

    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 o...

  15. Undersampled MR Image Reconstruction with Data-Driven Tight Frame

    Directory of Open Access Journals (Sweden)

    Jianbo Liu

    2015-01-01

    Full Text Available Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.

  16. Undersampled MR Image Reconstruction with Data-Driven Tight Frame.

    Science.gov (United States)

    Liu, Jianbo; Wang, Shanshan; Peng, Xi; Liang, Dong

    2015-01-01

    Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.

  17. Optimization of the alpha image reconstruction - an iterative CT-image reconstruction with well-defined image quality metrics.

    Science.gov (United States)

    Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

    2017-09-01

    Optimization of the AIR-algorithm for improved convergence and performance. The AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

  18. Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

    Energy Technology Data Exchange (ETDEWEB)

    Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc [German Cancer Research Center, Heidelberg (Germany).

    2017-10-01

    Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

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

    Directory of Open Access Journals (Sweden)

    Oliver S Grosser

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    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 pART 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

  2. Image reconstruction and scan configurations enabled by optimization-based algorithms in multispectral CT

    Science.gov (United States)

    Chen, Buxin; Zhang, Zheng; Sidky, Emil Y.; Xia, Dan; Pan, Xiaochuan

    2017-11-01

    Optimization-based algorithms for image reconstruction in multispectral (or photon-counting) computed tomography (MCT) remains a topic of active research. The challenge of optimization-based image reconstruction in MCT stems from the inherently non-linear data model that can lead to a non-convex optimization program for which no mathematically exact solver seems to exist for achieving globally optimal solutions. In this work, based upon a non-linear data model, we design a non-convex optimization program, derive its first-order-optimality conditions, and propose an algorithm to solve the program for image reconstruction in MCT. In addition to consideration of image reconstruction for the standard scan configuration, the emphasis is on investigating the algorithm’s potential for enabling non-standard scan configurations with no or minimum hardware modification to existing CT systems, which has potential practical implications for lowered hardware cost, enhanced scanning flexibility, and reduced imaging dose/time in MCT. Numerical studies are carried out for verification of the algorithm and its implementation, and for a preliminary demonstration and characterization of the algorithm in reconstructing images and in enabling non-standard configurations with varying scanning angular range and/or x-ray illumination coverage in MCT.

  3. Image reconstruction for a Positron Emission Tomograph optimized for breast cancer imaging

    Energy Technology Data Exchange (ETDEWEB)

    Virador, Patrick R.G. [Univ. of California, Berkeley, CA (United States)

    2000-04-01

    The author performs image reconstruction for a novel Positron Emission Tomography camera that is optimized for breast cancer imaging. This work addresses for the first time, the problem of fully-3D, tomographic reconstruction using a septa-less, stationary, (i.e. no rotation or linear motion), and rectangular camera whose Field of View (FOV) encompasses the entire volume enclosed by detector modules capable of measuring Depth of Interaction (DOI) information. The camera is rectangular in shape in order to accommodate breasts of varying sizes while allowing for soft compression of the breast during the scan. This non-standard geometry of the camera exacerbates two problems: (a) radial elongation due to crystal penetration and (b) reconstructing images from irregularly sampled data. Packing considerations also give rise to regions in projection space that are not sampled which lead to missing information. The author presents new Fourier Methods based image reconstruction algorithms that incorporate DOI information and accommodate the irregular sampling of the camera in a consistent manner by defining lines of responses (LORs) between the measured interaction points instead of rebinning the events into predefined crystal face LORs which is the only other method to handle DOI information proposed thus far. The new procedures maximize the use of the increased sampling provided by the DOI while minimizing interpolation in the data. The new algorithms use fixed-width evenly spaced radial bins in order to take advantage of the speed of the Fast Fourier Transform (FFT), which necessitates the use of irregular angular sampling in order to minimize the number of unnormalizable Zero-Efficiency Bins (ZEBs). In order to address the persisting ZEBs and the issue of missing information originating from packing considerations, the algorithms (a) perform nearest neighbor smoothing in 2D in the radial bins (b) employ a semi-iterative procedure in order to estimate the unsampled data

  4. The use of imaging in patients post breast reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Sim, Y.T. [Department of Radiology, Glasgow Royal Infirmary, Glasgow (United Kingdom); Litherland, J.C., E-mail: Janet.Litherland@ggc.scot.nhs.uk [Department of Radiology, Glasgow Royal Infirmary, Glasgow (United Kingdom)

    2012-02-15

    Aim: To evaluate the usefulness of mammographic surveillance for asymptomatic patients and as a problem-solving tool in symptomatic patients with reconstructed breasts. Materials and methods: The imaging records over 4 years identified 227 patients with a history of breast reconstruction post-mastectomy due to cancer. Clinical and imaging records were reviewed to evaluate the use of imaging in the follow-up management of these patients. Results: Records showed that 116 (51%) of the patients identified underwent surveillance mammography of the reconstructed breast, in which one recurrent cancer was detected in an autologous tissue flap reconstruction (0.86% detection rate of non-palpable recurrent cancer), with a recall rate of 4%. One other patient had interval recurrence diagnosed following presentation with pain. Mammography of the contralateral breast only was performed in 111 patients. Fifty-four patients (24%) presented on 78 occasions with symptoms relating to the breast reconstructions, most commonly lump or swelling. Half of these patient episodes subsequently found no significant abnormality, and a further 29% had fat necrosis revealed on imaging. Four recurrent cancers were diagnosed. Conclusion: There is insufficient evidence for recommending routine surveillance mammography for non-palpable recurrent cancer in the reconstructed breasts. Ultrasound and mammography are useful imaging techniques in the assessment of reconstructed breasts in the symptomatic setting. Fat necrosis is the most common benign finding on mammograms of reconstructed breasts, both in the surveillance and symptomatic groups.

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

    Directory of Open Access Journals (Sweden)

    Jingyu Guo

    2016-01-01

    Full Text Available 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.

  6. Relating Admissibility Standards for Digital Evidence to Attack Scenario Reconstruction

    Directory of Open Access Journals (Sweden)

    Changwei Liu

    2014-09-01

    Full Text Available Attackers tend to use complex techniques such as combining multi-step, multi-stage attack with anti-forensic tools to make it difficult to find incriminating evidence and reconstruct attack scenarios that can stand up to the expected level of evidence admissibility in a court of law. As a solution, we propose to integrate the legal aspects of evidence correlation into a Prolog based reasoner to address the admissibility requirements by creating most probable attack scenarios that satisfy admissibility standards for substantiating evidence. Using a prototype implementation, we show how evidence extracted by using forensic tools can be integrated with legal reasoning to reconstruct network attack scenarios. Our experiment shows this implemented reasoner can provide pre-estimate of admissibility on a digital crime towards an attacked network.

  7. Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.

    Science.gov (United States)

    Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Weavers, Paul T; Huston, John; Gray, Erin M; Bernstein, Matt A

    2016-06-01

    To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med 75:2534-2544, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  8. Surface Reconstruction and Image Enhancement via $L^1$-Minimization

    KAUST Repository

    Dobrev, Veselin

    2010-01-01

    A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.

  9. Face reconstruction from image sequences for forensic face comparison

    NARCIS (Netherlands)

    van Dam, C.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2016-01-01

    The authors explore the possibilities of a dense model-free three-dimensional (3D) face reconstruction method, based on image sequences from a single camera, to improve the current state of forensic face comparison. They propose a new model-free 3D reconstruction method for faces, based on the

  10. Total variation regularization in measurement and image space for PET reconstruction

    KAUST Repository

    Burger, M

    2014-09-18

    © 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.

  11. Image reconstruction in an electro-holographic display

    Science.gov (United States)

    Son, Jung-Young; Son, Wook-Ho; Kim, Jae-Han; Choo, Hyongon

    2017-05-01

    The optical phenomena arising in the process of forming reconstructed images in a hologram are explained and shown visually with the use of light field images. The light fields at different distances from the hologram on a DMD reveal that the reconstructed image of each object point is formed by the corresponding Fresnel zone pattern, which is reconstructed from the hologram when it is illuminated by a reconstruction laser beam. The reconstructed image is a circle of least confusion laden with noise and distortion. It has a finite size and does not appear at the object distance from the hologram due to the presence of aberrations, especially that of a strong astigmatism. The astigmatism appears along the direction of the rotating axis of each pixel and its cross at right angles. The aberrations and noise are responsible for the distortion and deterioration of the resolution in the reconstructed image, the difference of the image position from that of the object, and a reduction in the depth resolution. The light field images also reveal intensity fluctuations due to the addition of the in- and out-phase of the rays from the hologram.

  12. Algorithms for Reconstruction of Undersampled Atomic Force Microscopy Images Supplementary Material

    DEFF Research Database (Denmark)

    2017-01-01

    Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods.......Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods....

  13. Reconstruction of Optical Thickness from Hoffman Modulation Contrast Images

    DEFF Research Database (Denmark)

    Olsen, Niels Holm; Sporring, Jon; Nielsen, Mads

    2003-01-01

    Hoffman microscopy imaging systems are part of numerous fertility clinics world-wide. We discuss the physics of the Hoffman imaging system from optical thickness to image intensity, implement a simple, yet fast, reconstruction algorithm using Fast Fourier Transformation and discuss the usability...

  14. Compressed Sensing Inspired Image Reconstruction from Overlapped Projections

    Directory of Open Access Journals (Sweden)

    Lin Yang

    2010-01-01

    Full Text Available The key idea discussed in this paper is to reconstruct an image from overlapped projections so that the data acquisition process can be shortened while the image quality remains essentially uncompromised. To perform image reconstruction from overlapped projections, the conventional reconstruction approach (e.g., filtered backprojection (FBP algorithms cannot be directly used because of two problems. First, overlapped projections represent an imaging system in terms of summed exponentials, which cannot be transformed into a linear form. Second, the overlapped measurement carries less information than the traditional line integrals. To meet these challenges, we propose a compressive sensing-(CS- based iterative algorithm for reconstruction from overlapped data. This algorithm starts with a good initial guess, relies on adaptive linearization, and minimizes the total variation (TV. Then, we demonstrated the feasibility of this algorithm in numerical tests.

  15. Sparse magnetic resonance imaging reconstruction using the bregman iteration

    Science.gov (United States)

    Lee, Dong-Hoon; Hong, Cheol-Pyo; Lee, Man-Woo

    2013-01-01

    Magnetic resonance imaging (MRI) reconstruction needs many samples that are sequentially sampled by using phase encoding gradients in a MRI system. It is directly connected to the scan time for the MRI system and takes a long time. Therefore, many researchers have studied ways to reduce the scan time, especially, compressed sensing (CS), which is used for sparse images and reconstruction for fewer sampling datasets when the k-space is not fully sampled. Recently, an iterative technique based on the bregman method was developed for denoising. The bregman iteration method improves on total variation (TV) regularization by gradually recovering the fine-scale structures that are usually lost in TV regularization. In this study, we studied sparse sampling image reconstruction using the bregman iteration for a low-field MRI system to improve its temporal resolution and to validate its usefulness. The image was obtained with a 0.32 T MRI scanner (Magfinder II, SCIMEDIX, Korea) with a phantom and an in-vivo human brain in a head coil. We applied random k-space sampling, and we determined the sampling ratios by using half the fully sampled k-space. The bregman iteration was used to generate the final images based on the reduced data. We also calculated the root-mean-square-error (RMSE) values from error images that were obtained using various numbers of bregman iterations. Our reconstructed images using the bregman iteration for sparse sampling images showed good results compared with the original images. Moreover, the RMSE values showed that the sparse reconstructed phantom and the human images converged to the original images. We confirmed the feasibility of sparse sampling image reconstruction methods using the bregman iteration with a low-field MRI system and obtained good results. Although our results used half the sampling ratio, this method will be helpful in increasing the temporal resolution at low-field MRI systems.

  16. A review of GPU-based medical image reconstruction.

    Science.gov (United States)

    Després, Philippe; Jia, Xun

    2017-10-01

    Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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

    Science.gov (United States)

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

    2014-03-01

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

  18. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR)

    Energy Technology Data Exchange (ETDEWEB)

    Notohamiprodjo, S.; Deak, Z.; Meurer, F.; Maertz, F.; Mueck, F.G.; Geyer, L.L.; Wirth, S. [Ludwig-Maximilians University Hospital of Munich, Institute for Clinical Radiology, Munich (Germany)

    2015-01-15

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)

  19. Computationally rapid method of estimating signal-to-noise ratio for phased array image reconstructions.

    Science.gov (United States)

    Wiens, Curtis N; Kisch, Shawn J; Willig-Onwuachi, Jacob D; McKenzie, Charles A

    2011-10-01

    Measuring signal-to-noise ratio (SNR) for parallel MRI reconstructions is difficult due to spatially dependent noise amplification. Existing approaches for measuring parallel MRI SNR are limited because they are not applicable to all reconstructions, require significant computation time, or rely on repeated image acquisitions. A new SNR estimation approach is proposed, a hybrid of the repeated image acquisitions method detailed in the National Electrical Manufacturers Association (NEMA) standard and the Monte Carlo based pseudo-multiple replica method, in which the difference between images reconstructed from the unaltered acquired data and that same data reconstructed after the addition of calibrated pseudo-noise is used to estimate the noise in the parallel MRI image reconstruction. This new noise estimation method can be used to rapidly compute the pixel-wise SNR of the image generated from any parallel MRI reconstruction of a single acquisition. SNR maps calculated with the new method are validated against existing SNR calculation techniques. Copyright © 2011 Wiley-Liss, Inc.

  20. Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis

    DEFF Research Database (Denmark)

    Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    solutions can aid in iterative image reconstruction algorithm design. This issue is particularly acute for iterative image reconstruction in Digital Breast Tomosynthesis (DBT), where the corresponding data model IS particularly poorly conditioned. The impact of this poor conditioning is that iterative......Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization...... algorithms applied to this system can be slow to converge. Recent developments in first-order algorithms are now beginning to allow for accurate solutions to optimization problems of interest to tomographic imaging in general. In particular, we investigate an algorithm developed by Chambolle and Pock (2011 J...

  1. Application of Super-Resolution Image Reconstruction to Digital Holography

    Directory of Open Access Journals (Sweden)

    Zhang Shuqun

    2006-01-01

    Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.

  2. Information Propagation in Prior-Image-Based Reconstruction.

    Science.gov (United States)

    Stayman, J Webster; Prince, Jerry L; Siewerdsen, Jeffrey H

    Advanced reconstruction methods for computed tomography include sophisticated forward models of the imaging system that capture the pertinent physical processes affecting the signal and noise in projection measurements. However, most do little to integrate prior knowledge of the subject - often relying only on very general notions of local smoothness or edges. In many cases, as in longitudinal surveillance or interventional imaging, a patient has undergone a sequence of studies prior to the current image acquisition that hold a wealth of prior information on patient-specific anatomy. While traditional techniques tend to treat each data acquisition as an isolated event and disregard such valuable patient-specific prior information, some reconstruction methods, such as PICCS[1] and PIR-PLE[2], can incorporate prior images into a reconstruction objective function. Inclusion of such information allows for dramatic reduction in the data fidelity requirements and more robustly accommodate substantial undersampling and exposure reduction with consequent benefits to imaging speed and reduced radiation dose. While such prior-image-based methods offer tremendous promise, the introduction of prior information in the reconstruction raises significant concern regarding the accurate representation of features in the image and whether those features arise from the current data acquisition or from the prior images. In this work we propose a novel framework to analyze the propagation of information in prior-image-based reconstruction by decomposing the estimation into distinct components supported by the current data acquisition and by the prior image. This decomposition quantifies the contributions from prior and current data as a spatial map and can trace specific features in the image to their source. Such "information source maps" can potentially be used as a check on confidence that a given image feature arises from the current data or from the prior and to more quantitatively

  3. Proposal of fault-tolerant tomographic image reconstruction

    CERN Document Server

    Kudo, Hiroyuki; Yamazaki, Fukashi; Nemoto, Takuya

    2016-01-01

    This paper deals with tomographic image reconstruction under the situation where some of projection data bins are contaminated with abnormal data. Such situations occur in various instances of tomography. We propose a new reconstruction algorithm called the Fault-Tolerant reconstruction outlined as follows. The least-squares (L2-norm) error function ||Ax-b||_2^2 used in ordinary iterative reconstructions is sensitive to the existence of abnormal data. The proposed algorithm utilizes the L1-norm error function ||Ax-b||_1^1 instead of the L2-norm, and we develop a row-action-type iterative algorithm using the proximal splitting framework in convex optimization fields. We also propose an improved version of the L1-norm reconstruction called the L1-TV reconstruction, in which a weak Total Variation (TV) penalty is added to the cost function. Simulation results demonstrate that reconstructed images with the L2-norm were severely damaged by the effect of abnormal bins, whereas images with the L1-norm and L1-TV reco...

  4. Compressed Sensing MR Image Reconstruction Exploiting TGV and Wavelet Sparsity

    Directory of Open Access Journals (Sweden)

    Di Zhao

    2014-01-01

    Full Text Available Compressed sensing (CS based methods make it possible to reconstruct magnetic resonance (MR images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV regularization to eliminate the staircasing artifacts caused by conventional total variation (TV. Fast composite splitting algorithm (FCSA is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively.

  5. Compressed sensing MR image reconstruction exploiting TGV and wavelet sparsity.

    Science.gov (United States)

    Zhao, Di; Du, Huiqian; Han, Yu; Mei, Wenbo

    2014-01-01

    Compressed sensing (CS) based methods make it possible to reconstruct magnetic resonance (MR) images from undersampled measurements, which is known as CS-MRI. The reference-driven CS-MRI reconstruction schemes can further decrease the sampling ratio by exploiting the sparsity of the difference image between the target and the reference MR images in pixel domain. Unfortunately existing methods do not work well given that contrast changes are incorrectly estimated or motion compensation is inaccurate. In this paper, we propose to reconstruct MR images by utilizing the sparsity of the difference image between the target and the motion-compensated reference images in wavelet transform and gradient domains. The idea is attractive because it requires neither the estimation of the contrast changes nor multiple times motion compensations. In addition, we apply total generalized variation (TGV) regularization to eliminate the staircasing artifacts caused by conventional total variation (TV). Fast composite splitting algorithm (FCSA) is used to solve the proposed reconstruction problem in order to improve computational efficiency. Experimental results demonstrate that the proposed method can not only reduce the computational cost but also decrease sampling ratio or improve the reconstruction quality alternatively.

  6. Fast dictionary-based reconstruction for diffusion spectrum imaging.

    Science.gov (United States)

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

    2013-11-01

    Diffusion spectrum imaging 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 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.

  7. Towards nonlinear wave reconstruction and prediction from synthetic radar images

    NARCIS (Netherlands)

    Wijaya, Andreas Parama

    2016-01-01

    The use of remotely wave sensing by a marine radar is increasingly needed to provide wave information for the sake of safety and operational effectiveness in many offshore activities. Reconstruction of radar images needs to be carried out since radar images are a poor representation of the sea

  8. Pose Reconstruction of Flexible Instruments from Endoscopic Images using Markers

    NARCIS (Netherlands)

    Reilink, Rob; Stramigioli, Stefano; Misra, Sarthak

    2012-01-01

    A system is developed that can reconstruct the pose of flexible endoscopic instruments that are used in ad- vanced flexible endoscopes using solely the endoscopic images. Four markers are placed on the instrument, whose positions are measured in the image. These measurements are compared to a

  9. Gadgetron: An Open Source Framework for Medical Image Reconstruction

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

    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...

  10. Radioastronomical image reconstruction with regularized least squares

    NARCIS (Netherlands)

    Naghibzadeh, S.; Mouri Sardarabadi, A.; van der Veen, A.J.; Dong, Min; Zheng, Thomas Fang

    Image formation using the data from an array of sensors is a familiar problem in many fields such as radio astronomy, biomedical and geodetic imaging. The problem can be formulated as a least squares (LS) estimation problem and becomes ill-posed at high resolutions, i.e. large number of image

  11. An imaging algorithm for vertex reconstruction for ATLAS Run-2

    CERN Document Server

    The ATLAS collaboration

    2015-01-01

    The reconstruction of vertices corresponding to proton--proton collisions in ATLAS is an essential element of event reconstruction used in many performance studies and physics analyses. During Run-1 of the LHC, ATLAS has employed an iterative approach to vertex finding. In order to improve the flexibility of the algorithm and ensure continued performance for very high numbers of simultaneous collisions in future LHC data taking, a new approach to seeding vertex finding is being developed inspired by image reconstruction techniques. This note provides a brief outline of how reconstructed tracks are used to create an image of likely vertex collisions in an event and presents some preliminary results of the performance of the algorithm in simulation approximating early Run-2 conditions.

  12. DCT and DST Based Image Compression for 3D Reconstruction

    Science.gov (United States)

    Siddeq, Mohammed M.; Rodrigues, Marcos A.

    2017-03-01

    This paper introduces a new method for 2D image compression whose quality is demonstrated through accurate 3D reconstruction using structured light techniques and 3D reconstruction from multiple viewpoints. The method is based on two discrete transforms: (1) A one-dimensional Discrete Cosine Transform (DCT) is applied to each row of the image. (2) The output from the previous step is transformed again by a one-dimensional Discrete Sine Transform (DST), which is applied to each column of data generating new sets of high-frequency components followed by quantization of the higher frequencies. The output is then divided into two parts where the low-frequency components are compressed by arithmetic coding and the high frequency ones by an efficient minimization encoding algorithm. At decompression stage, a binary search algorithm is used to recover the original high frequency components. The technique is demonstrated by compressing 2D images up to 99% compression ratio. The decompressed images, which include images with structured light patterns for 3D reconstruction and from multiple viewpoints, are of high perceptual quality yielding accurate 3D reconstruction. Perceptual assessment and objective quality of compression are compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results show that the proposed compression method is superior to both JPEG and JPEG2000 concerning 3D reconstruction, and with equivalent perceptual quality to JPEG2000.

  13. Probability of correct reconstruction in compressive spectral imaging

    Directory of Open Access Journals (Sweden)

    Samuel Eduardo Pinilla

    2016-08-01

    Full Text Available Coded Aperture Snapshot Spectral Imaging (CASSI systems capture the 3-dimensional (3D spatio-spectral information of a scene using a set of 2-dimensional (2D random coded Focal Plane Array (FPA measurements. A compressed sensing reconstruction algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the statistical structure of the coded apertures. The Restricted Isometry Property (RIP of the CASSI sensing matrix is used to determine the probability of correct image reconstruction and provides guidelines for the minimum number of FPA measurement shots needed for image reconstruction. Further, the RIP can be used to determine the optimal structure of the coded projections in CASSI. This article describes the CASSI optical architecture and develops the RIP for the sensing matrix in this system. Simulations show the higher quality of spectral image reconstructions when the RIP property is satisfied. Simulations also illustrate the higher performance of the optimal structured projections in CASSI.

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

    Science.gov (United States)

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

    2017-06-01

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

  15. Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose.

    Science.gov (United States)

    Aurumskjöld, Marie-Louise; Söderberg, Marcus; Stålhammar, Fredrik; von Steyern, Kristina Vult; Tingberg, Anders; Ydström, Kristina

    2017-01-01

    Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose(4)), and images from the low-dose examinations were reconstructed with both iDose(4) and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose(4) and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose(4) images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60-0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose(4) method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

  16. Parallel hyperspectral image reconstruction using random projections

    Science.gov (United States)

    Sevilla, Jorge; Martín, Gabriel; Nascimento, José M. P.

    2016-10-01

    Spaceborne sensors systems are characterized by scarce onboard computing and storage resources and by communication links with reduced bandwidth. Random projections techniques have been demonstrated as an effective and very light way to reduce the number of measurements in hyperspectral data, thus, the data to be transmitted to the Earth station is reduced. However, the reconstruction of the original data from the random projections may be computationally expensive. SpeCA is a blind hyperspectral reconstruction technique that exploits the fact that hyperspectral vectors often belong to a low dimensional subspace. SpeCA has shown promising results in the task of recovering hyperspectral data from a reduced number of random measurements. In this manuscript we focus on the implementation of the SpeCA algorithm for graphics processing units (GPU) using the compute unified device architecture (CUDA). Experimental results conducted using synthetic and real hyperspectral datasets on the GPU architecture by NVIDIA: GeForce GTX 980, reveal that the use of GPUs can provide real-time reconstruction. The achieved speedup is up to 22 times when compared with the processing time of SpeCA running on one core of the Intel i7-4790K CPU (3.4GHz), with 32 Gbyte memory.

  17. High resolution image reconstruction with constrained, total-variation minimization

    CERN Document Server

    Sidky, Emil Y; Duchin, Yuval; Ullberg, Christer; Pan, Xiaochuan

    2011-01-01

    This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate. Such systems pose a challenge for iterative image reconstruction, because a very fine image grid is needed to realize the resolution inherent in such scanners. These image arrays lead to under-determined imaging models whose inversion is unstable and can result in undesirable artifacts and noise patterns. There are many possibilities to stabilize the imaging model, and this work proposes a method which may have an advantage in terms of algorithm efficiency. The proposed method introduces additional constraints in the optimization problem; these constraints set to zero high spatial frequency components which are beyond the sensing capability of the detector. The method is demonstrated with an actual CT data set and compared with another method based on projection up-sampling.

  18. Reconstructing flaw image using dataset of full matrix capture technique

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Tae Hun; Kim, Yong Sik; Lee, Jeong Seok [KHNP Central Research Institute, Daejeon (Korea, Republic of)

    2017-02-15

    A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.

  19. Blind reconstruction of sparse images with unknown point spread function

    Science.gov (United States)

    Herrity, Kyle; Raich, Raviv; Hero, Alfred O., III

    2008-02-01

    We consider the image reconstruction problem when the original image is assumed to be sparse and when partial knowledge of the point spread function (PSF) is available. In particular, we are interested in recovering the magnetization density given magnetic resonance force microscopy (MRFM) data, and we present an iterative alternating minimization algorithm (AM) to solve this problem. A smoothing penalty is introduced on allowable PSFs to improve the reconstruction. Simulations demonstrate its performance in reconstructing both the image and unknown point spread function. In addition, we develop an optimization transfer approach to solving a total variation (TV) blind deconvolution algorithm presented in a paper by Chan and Wong. We compare the performance of the AM algorithm to the blind TV algorithm as well as to a TV based majorization-minimization algorithm developed by Figueiredo et al.

  20. Regularization Reconstruction Method for Imaging Problems in Electrical Capacitance Tomography

    Science.gov (United States)

    Chu, Pan; Lei, Jing

    2017-11-01

    The electrical capacitance tomography (ECT) is deemed to be a powerful visualization measurement technique for the parametric measurement in a multiphase flow system. The inversion task in the ECT technology is an ill-posed inverse problem, and seeking for an efficient numerical method to improve the precision of the reconstruction images is important for practical measurements. By the introduction of the Tikhonov regularization (TR) methodology, in this paper a loss function that emphasizes the robustness of the estimation and the low rank property of the imaging targets is put forward to convert the solution of the inverse problem in the ECT reconstruction task into a minimization problem. Inspired by the split Bregman (SB) algorithm, an iteration scheme is developed for solving the proposed loss function. Numerical experiment results validate that the proposed inversion method not only reconstructs the fine structures of the imaging targets, but also improves the robustness.

  1. Reconstruction of CT images by the Bayes- back projection method

    CERN Document Server

    Haruyama, M; Takase, M; Tobita, H

    2002-01-01

    In the course of research on quantitative assay of non-destructive measurement of radioactive waste, the have developed a unique program based on the Bayesian theory for reconstruction of transmission computed tomography (TCT) image. The reconstruction of cross-section images in the CT technology usually employs the Filtered Back Projection method. The new imaging reconstruction program reported here is based on the Bayesian Back Projection method, and it has a function of iterative improvement images by every step of measurement. Namely, this method has the capability of prompt display of a cross-section image corresponding to each angled projection data from every measurement. Hence, it is possible to observe an improved cross-section view by reflecting each projection data in almost real time. From the basic theory of Baysian Back Projection method, it can be not only applied to CT types of 1st, 2nd, and 3rd generation. This reported deals with a reconstruction program of cross-section images in the CT of ...

  2. Image reconstruction from incomplete convolution data via total variation regularization

    Directory of Open Access Journals (Sweden)

    Zhida Shen

    2015-02-01

    Full Text Available Variational models with Total Variation (TV regularization have long been known to preserve image edges and produce high quality reconstruction. On the other hand, recent theory on compressive sensing has shown that it is feasible to accurately reconstruct  images from a few linear measurements via TV regularization. However, in general TV models are difficult to solve due to the nondifferentiability and the universal coupling of variables. In this paper, we propose the use of alternating direction method for image reconstruction from highly incomplete convolution data, where an image is reconstructed as a minimizer of an energy function that sums   a TV term for image regularity and a least squares term for data fitting. Our algorithm, called RecPK, takes advantage of problem structures and has an extremely low per-iteration cost. To demonstrate the efficiency of RecPK, we  compare it with TwIST, a state-of-the-art algorithm for minimizing TV models. Moreover, we also demonstrate the usefulness of RecPK in image zooming.

  3. Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU

    Directory of Open Access Journals (Sweden)

    Arefan D

    2015-06-01

    Full Text Available 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.

  4. Image reconstruction technique using projection data from neutron tomography system

    Directory of Open Access Journals (Sweden)

    Waleed Abd el Bar

    2015-12-01

    Full Text Available Neutron tomography is a very powerful technique for nondestructive evaluation of heavy industrial components as well as for soft hydrogenous materials enclosed in heavy metals which are usually difficult to image using X-rays. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. This paper gives a description of a filter back projection (FBP technique, which is used for reconstruction of projected data obtained from transmission measurements by neutron tomography system We demonstrated the use of spatial Discrete Fourier Transform (DFT and the 2D Inverse DFT in the formulation of the method, and outlined the theory of reconstruction of a 2D neutron image from a sequence of 1D projections taken at different angles between 0 and π in MATLAB environment. Projections are generated by applying the Radon transform to the original image at different angles.

  5. Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

    Directory of Open Access Journals (Sweden)

    Ran Li

    2016-01-01

    Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

  6. Accurate tissue characterization in low-dose CT imaging with pure iterative reconstruction.

    Science.gov (United States)

    Murphy, Kevin P; McLaughlin, Patrick D; Twomey, Maria; Chan, Vincent E; Moloney, Fiachra; Fung, Adrian J; Chan, Faimee E; Kao, Tafline; O'Neill, Siobhan B; Watson, Benjamin; O'Connor, Owen J; Maher, Michael M

    2017-04-01

    We assess the ability of low-dose hybrid iterative reconstruction (IR) and 'pure' model-based IR (MBIR) images to maintain accurate Hounsfield unit (HU)-determined tissue characterization. Standard-protocol (SP) and low-dose modified-protocol (MP) CTs were contemporaneously acquired in 34 Crohn's disease patients referred for CT. SP image reconstruction was via the manufacturer's recommendations (60% FBP, filtered back projection; 40% ASiR, Adaptive Statistical iterative Reconstruction; SP-ASiR40). MP data sets underwent four reconstructions (100% FBP; 40% ASiR; 70% ASiR; MBIR). Three observers measured tissue volumes using HU thresholds for fat, soft tissue and bone/contrast on each data set. Analysis was via SPSS. Inter-observer agreement was strong for 1530 datapoints (rs > 0.9). MP-MBIR tissue volume measurement was superior to other MP reconstructions and closely correlated with the reference SP-ASiR40 images for all tissue types. MP-MBIR superiority was most marked for fat volume calculation - close SP-ASiR40 and MP-MBIR Bland-Altman plot correlation was seen with the lowest average difference (336 cm(3) ) when compared with other MP reconstructions. Hounsfield unit-determined tissue volume calculations from MP-MBIR images resulted in values comparable to SP-ASiR40 calculations and values that are superior to MP-ASiR images. Accuracy of estimation of volume of tissues (e.g. fat) using segmentation software on low-dose CT images appears optimal when reconstructed with pure IR. © 2016 The Royal Australian and New Zealand College of Radiologists.

  7. A simulation study on image reconstruction in magnetic particle imaging with field-free-line encoding

    CERN Document Server

    Murase, Kenya

    2016-01-01

    The purpose of this study was to present image reconstruction methods for magnetic particle imaging (MPI) with a field-free-line (FFL) encoding scheme and to propose the use of the maximum likelihood-expectation maximization (ML-EM) algorithm for improving the image quality of MPI. The feasibility of these methods was investigated by computer simulations, in which the projection data were generated by summing up the Fourier harmonics obtained from the MPI signals based on the Langevin function. Images were reconstructed from the generated projection data using the filtered backprojection (FBP) method and the ML-EM algorithm. The effects of the gradient of selection magnetic field (SMF), the strength of drive magnetic field (DMF), the diameter of magnetic nanoparticles (MNPs), and the number of projection data on the image quality of the reconstructed images were investigated. The spatial resolution of the reconstructed images became better with increasing gradient of SMF and with increasing diameter of MNPs u...

  8. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    Science.gov (United States)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  9. High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI

    Science.gov (United States)

    Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer

    2011-03-01

    Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.

  10. Super Resolution Reconstruction Based on Adaptive Detail Enhancement for ZY-3 Satellite Images

    Science.gov (United States)

    Zhu, Hong; Song, Weidong; Tan, Hai; Wang, Jingxue; Jia, Di

    2016-06-01

    Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

  11. Image quality improvements using adaptive statistical iterative reconstruction for evaluating chronic myocardial infarction using iodine density images with spectral CT.

    Science.gov (United States)

    Kishimoto, Junichi; Ohta, Yasutoshi; Kitao, Shinichiro; Watanabe, Tomomi; Ogawa, Toshihide

    2017-10-19

    Single-source dual-energy CT (ssDECT) allows the reconstruction of iodine density images (IDIs) from projection based computing. We hypothesized that adding adaptive statistical iterative reconstruction (ASiR) could improve image quality. The aim of our study was to evaluate the effect and determine the optimal blend percentages of ASiR for IDI of myocardial late iodine enhancement (LIE) in the evaluation of chronic myocardial infarction using ssDECT. A total of 28 patients underwent cardiac LIE using a ssDECT scanner. IDIs between 0 and 100% of ASiR contributions in 10% increments were reconstructed. The signal-to-noise ratio (SNR) of remote myocardia and the contrast-to-noise ratio (CNR) of infarcted myocardia were measured. Transmural extent of infarction was graded using a 5-point scale. The SNR, CNR, and transmural extent were assessed for each ASiR contribution ratio. The transmural extents were compared with MRI as a reference standard. Compared to 0% ASiR, the use of 20-100% ASiR resulted in a reduction of image noise (p ASiR images, reconstruction with 100% ASiR image showed the highest improvement in SNR (229%; p ASiR above 80% showed the highest ratio (73.7%) of accurate transmural extent classification. In conclusion, ASiR intensity of 80-100% in IDIs can improve image quality without changes in signal and maximizes the accuracy of transmural extent in infarcted myocardium.

  12. Image reconstructions from super-sampled data sets with resolution modeling in PET imaging.

    Science.gov (United States)

    Li, Yusheng; Matej, Samuel; Metzler, Scott D

    2014-12-01

    Spatial resolution in positron emission tomography (PET) is still a limiting factor in many imaging applications. To improve the spatial resolution for an existing scanner with fixed crystal sizes, mechanical movements such as scanner wobbling and object shifting have been considered for PET systems. Multiple acquisitions from different positions can provide complementary information and increased spatial sampling. The objective of this paper is to explore an efficient and useful reconstruction framework to reconstruct super-resolution images from super-sampled low-resolution data sets. The authors introduce a super-sampling data acquisition model based on the physical processes with tomographic, downsampling, and shifting matrices as its building blocks. Based on the model, we extend the MLEM and Landweber algorithms to reconstruct images from super-sampled data sets. The authors also derive a backprojection-filtration-like (BPF-like) method for the super-sampling reconstruction. Furthermore, they explore variant methods for super-sampling reconstructions: the separate super-sampling resolution-modeling reconstruction and the reconstruction without downsampling to further improve image quality at the cost of more computation. The authors use simulated reconstruction of a resolution phantom to evaluate the three types of algorithms with different super-samplings at different count levels. Contrast recovery coefficient (CRC) versus background variability, as an image-quality metric, is calculated at each iteration for all reconstructions. The authors observe that all three algorithms can significantly and consistently achieve increased CRCs at fixed background variability and reduce background artifacts with super-sampled data sets at the same count levels. For the same super-sampled data sets, the MLEM method achieves better image quality than the Landweber method, which in turn achieves better image quality than the BPF-like method. The authors also demonstrate

  13. Objective evaluation of reconstruction methods for quantitative SPECT imaging in the absence of ground truth.

    Science.gov (United States)

    Jha, Abhinav K; Song, Na; Caffo, Brian; Frey, Eric C

    2015-04-13

    Quantitative single-photon emission computed tomography (SPECT) imaging is emerging as an important tool in clinical studies and biomedical research. There is thus a need for optimization and evaluation of systems and algorithms that are being developed for quantitative SPECT imaging. An appropriate objective method to evaluate these systems is by comparing their performance in the end task that is required in quantitative SPECT imaging, such as estimating the mean activity concentration in a volume of interest (VOI) in a patient image. This objective evaluation can be performed if the true value of the estimated parameter is known, i.e. we have a gold standard. However, very rarely is this gold standard known in human studies. Thus, no-gold-standard techniques to optimize and evaluate systems and algorithms in the absence of gold standard are required. In this work, we developed a no-gold-standard technique to objectively evaluate reconstruction methods used in quantitative SPECT when the parameter to be estimated is the mean activity concentration in a VOI. We studied the performance of the technique with realistic simulated image data generated from an object database consisting of five phantom anatomies with all possible combinations of five sets of organ uptakes, where each anatomy consisted of eight different organ VOIs. Results indicate that the method provided accurate ranking of the reconstruction methods. We also demonstrated the application of consistency checks to test the no-gold-standard output.

  14. Gadgetron: an open source framework for medical image reconstruction.

    Science.gov (United States)

    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. Copyright © 2012 Wiley Periodicals, Inc.

  15. Magnetic resonance imaging with nonlinear gradient fields signal encoding and image reconstruction

    CERN Document Server

    Schultz, Gerrit

    2013-01-01

    Within the past few decades magnetic resonance imaging has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This text deals with a radically new approach of image encoding: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics.   Contents n  Image Reconstruction in MRI n  Nonlinear Gradient Encoding: PatLoc Imaging n  Presentation of Initial Hardware Designs n  Basics of Signal Encoding and Image Reconstruction in PatLoc Imaging n ...

  16. Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi

    OpenAIRE

    Vardhanabhuti, Varut; Ilyas, Sumaira; Gutteridge, Catherine; Freeman, Simon J.; Roobottom, Carl A

    2013-01-01

    Objectives To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. Methods Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and me...

  17. Image reconstruction for digital breast tomosynthesis (DBT) by using projection-angle-dependent filter functions

    Energy Technology Data Exchange (ETDEWEB)

    Park, Yeonok; Park, Chulkyu; Cho, Hyosung; Je, Uikyu; Hong, Daeki; Lee, Minsik; Cho, Heemoon; Choi, Sungil; Koo, Yangseo [Yonsei University, Wonju (Korea, Republic of)

    2014-09-15

    Digital breast tomosynthesis (DBT) is considered in clinics as a standard three-dimensional imaging modality, allowing the earlier detection of cancer. It typically acquires only 10-30 projections over a limited angle range of 15 - 60 .deg. with a stationary detector and typically uses a computationally-efficient filtered-backprojection (FBP) algorithm for image reconstruction. However, a common FBP algorithm yields poor image quality resulting from the loss of average image value and the presence of severe image artifacts due to the elimination of the dc component of the image by the ramp filter and to the incomplete data, respectively. As an alternative, iterative reconstruction methods are often used in DBT to overcome these difficulties, even though they are still computationally expensive. In this study, as a compromise, we considered a projection-angle dependent filtering method in which one-dimensional geometry-adapted filter kernels are computed with the aid of a conjugate-gradient method and are incorporated into the standard FBP framework. We implemented the proposed algorithm and performed systematic simulation works to investigate the imaging characteristics. Our results indicate that the proposed method is superior to a conventional FBP method for DBT imaging and has a comparable computational cost, while preserving good image homogeneity and edge sharpening with no serious image artifacts.

  18. Generalized Fourier slice theorem for cone-beam image reconstruction.

    Science.gov (United States)

    Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang

    2015-01-01

    The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).

  19. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    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.

  20. Efficient iterative image reconstruction algorithm for dedicated breast CT

    Science.gov (United States)

    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.

  1. Direct reconstruction of cardiac PET kinetic parametric images using a preconditioned conjugate gradient approach.

    Science.gov (United States)

    Rakvongthai, Yothin; Ouyang, Jinsong; Guerin, Bastien; Li, Quanzheng; Alpert, Nathaniel M; El Fakhri, Georges

    2013-10-01

    Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach. Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach. At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG. The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.

  2. Autofocus imaging : Image reconstruction based on inverse scattering theory

    NARCIS (Netherlands)

    Behura, J.; Wapenaar, C.P.A.; Snieder, R.

    2014-01-01

    Conventional imaging algorithms assume single scattering and therefore cannot image multiply scattered waves correctly. The multiply scattered events in the data are imaged at incorrect locations resulting in spurious subsurface structures and erroneous interpretation. This drawback of current

  3. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique1

    OpenAIRE

    Jiang, Jinxing; Hirano, Keiichi; Sakurai, Kenji

    2017-01-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a ...

  4. Memory and Perception-based Facial Image Reconstruction.

    Science.gov (United States)

    Chang, Chi-Hsun; Nemrodov, Dan; Lee, Andy C H; Nestor, Adrian

    2017-07-26

    Visual memory for faces has been extensively researched, especially regarding the main factors that influence face memorability. However, what we remember exactly about a face, namely, the pictorial content of visual memory, remains largely unclear. The current work aims to elucidate this issue by reconstructing face images from both perceptual and memory-based behavioural data. Specifically, our work builds upon and further validates the hypothesis that visual memory and perception share a common representational basis underlying facial identity recognition. To this end, we derived facial features directly from perceptual data and then used such features for image reconstruction separately from perception and memory data. Successful levels of reconstruction were achieved in both cases for newly-learned faces as well as for familiar faces retrieved from long-term memory. Theoretically, this work provides insights into the content of memory-based representations while, practically, it may open the path to novel applications, such as computer-based 'sketch artists'.

  5. Progress Update on Iterative Reconstruction of Neutron Tomographic Images

    Energy Technology Data Exchange (ETDEWEB)

    Hausladen, Paul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gregor, Jens [Univ. of Tennessee, Knoxville, TN (United States)

    2016-09-15

    This report satisfies the fiscal year 2016 technical deliverable to report on progress in development of fast iterative reconstruction algorithms for project OR16-3DTomography-PD2Jb, "3D Tomography and Image Processing Using Fast Neutrons." This project has two overall goals. The first of these goals is to extend associated-particle fast neutron transmission and, particularly, induced-reaction tomographic imaging algorithms to three dimensions. The second of these goals is to automatically segment the resultant tomographic images into constituent parts, and then extract information about the parts, such as the class of shape and potentially shape parameters. This report addresses of the component of the project concerned with three-dimensional (3D) image reconstruction.

  6. Skin image reconstruction using Monte Carlo based color generation

    Science.gov (United States)

    Aizu, Yoshihisa; Maeda, Takaaki; Kuwahara, Tomohiro; Hirao, Tetsuji

    2010-11-01

    We propose a novel method of skin image reconstruction based on color generation using Monte Carlo simulation of spectral reflectance in the nine-layered skin tissue model. The RGB image and spectral reflectance of human skin are obtained by RGB camera and spectrophotometer, respectively. The skin image is separated into the color component and texture component. The measured spectral reflectance is used to evaluate scattering and absorption coefficients in each of the nine layers which are necessary for Monte Carlo simulation. Various skin colors are generated by Monte Carlo simulation of spectral reflectance in given conditions for the nine-layered skin tissue model. The new color component is synthesized to the original texture component to reconstruct the skin image. The method is promising for applications in the fields of dermatology and cosmetics.

  7. Simultaneous deblurring and iterative reconstruction of CBCT for image guided brain radiosurgery.

    Science.gov (United States)

    Hashemi, SayedMasoud; Song, William Y; Sahgal, Arjun; Lee, Young; Huynh, Christopher; Grouza, Vladimir; Nordström, Håkan; Eriksson, Markus; Dorenlot, Antoine; Régis, Jean Marie; Mainprize, James G; Ruschin, Mark

    2017-04-07

    One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details

  8. Simultaneous deblurring and iterative reconstruction of CBCT for image guided brain radiosurgery

    Science.gov (United States)

    Hashemi, SayedMasoud; Song, William Y.; Sahgal, Arjun; Lee, Young; Huynh, Christopher; Grouza, Vladimir; Nordström, Håkan; Eriksson, Markus; Dorenlot, Antoine; Régis, Jean Marie; Mainprize, James G.; Ruschin, Mark

    2017-04-01

    One of the limiting factors in cone-beam CT (CBCT) image quality is system blur, caused by detector response, x-ray source focal spot size, azimuthal blurring, and reconstruction algorithm. In this work, we develop a novel iterative reconstruction algorithm that improves spatial resolution by explicitly accounting for image unsharpness caused by different factors in the reconstruction formulation. While the model-based iterative reconstruction techniques use prior information about the detector response and x-ray source, our proposed technique uses a simple measurable blurring model. In our reconstruction algorithm, denoted as simultaneous deblurring and iterative reconstruction (SDIR), the blur kernel can be estimated using the modulation transfer function (MTF) slice of the CatPhan phantom or any other MTF phantom, such as wire phantoms. The proposed image reconstruction formulation includes two regularization terms: (1) total variation (TV) and (2) nonlocal regularization, solved with a split Bregman augmented Lagrangian iterative method. The SDIR formulation preserves edges, eases the parameter adjustments to achieve both high spatial resolution and low noise variances, and reduces the staircase effect caused by regular TV-penalized iterative algorithms. The proposed algorithm is optimized for a point-of-care head CBCT unit for image-guided radiosurgery and is tested with CatPhan phantom, an anthropomorphic head phantom, and 6 clinical brain stereotactic radiosurgery cases. Our experiments indicate that SDIR outperforms the conventional filtered back projection and TV penalized simultaneous algebraic reconstruction technique methods (represented by adaptive steepest-descent POCS algorithm, ASD-POCS) in terms of MTF and line pair resolution, and retains the favorable properties of the standard TV-based iterative reconstruction algorithms in improving the contrast and reducing the reconstruction artifacts. It improves the visibility of the high contrast details

  9. Single Image Super Resolution via Sparse Reconstruction

    NARCIS (Netherlands)

    Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.

    2012-01-01

    High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.

  10. Realise : reconstruction of reality from image sequences

    NARCIS (Netherlands)

    Leymarie, F.; de la Fortelle, A.; Koenderink, Jan J.; Kappers, A. M L; Stavridi, M.; van Ginneken, B.; Muller, S.; Krake, S.; Faugeras, O.; Robert, L.; Gauclin, C.; Laveau, S.; Zeller, C.; Anon,

    1996-01-01

    REALISE has for principal goals to extract from sequences of images, acquired with a moving camera, information necessary for determining the 3D (CAD-like) structure of a real-life scene together with information about the radiometric signatures of surfaces bounding the extracted 3D objects (e.g.

  11. Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

    2011-07-01

    We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

  12. High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware.

    Science.gov (United States)

    Freiberger, Manuel; Egger, Herbert; Liebmann, Manfred; Scharfetter, Hermann

    2011-11-01

    Image reconstruction in fluorescence optical tomography is a three-dimensional nonlinear ill-posed problem governed by a system of partial differential equations. In this paper we demonstrate that a combination of state of the art numerical algorithms and a careful hardware optimized implementation allows to solve this large-scale inverse problem in a few seconds on standard desktop PCs with modern graphics hardware. In particular, we present methods to solve not only the forward but also the non-linear inverse problem by massively parallel programming on graphics processors. A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images.

  13. High-performance image reconstruction in fluorescence tomography on desktop computers and graphics hardware

    Science.gov (United States)

    Freiberger, Manuel; Egger, Herbert; Liebmann, Manfred; Scharfetter, Hermann

    2011-01-01

    Image reconstruction in fluorescence optical tomography is a three-dimensional nonlinear ill-posed problem governed by a system of partial differential equations. In this paper we demonstrate that a combination of state of the art numerical algorithms and a careful hardware optimized implementation allows to solve this large-scale inverse problem in a few seconds on standard desktop PCs with modern graphics hardware. In particular, we present methods to solve not only the forward but also the non-linear inverse problem by massively parallel programming on graphics processors. A comparison of optimized CPU and GPU implementations shows that the reconstruction can be accelerated by factors of about 15 through the use of the graphics hardware without compromising the accuracy in the reconstructed images. PMID:22076279

  14. An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging.

    Science.gov (United States)

    Valente, Solivan A; Zibetti, Marcelo V W; Pipa, Daniel R; Maia, Joaquim M; Schneider, Fabio K

    2017-03-08

    Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an ℓ 1 -regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable.

  15. Undersampled Hyperspectral Image Reconstruction Based on Surfacelet Transform

    Directory of Open Access Journals (Sweden)

    Lei Liu

    2015-01-01

    Full Text Available Hyperspectral imaging is a crucial technique for military and environmental monitoring. However, limited equipment hardware resources severely affect the transmission and storage of a huge amount of data for hyperspectral images. This limitation has the potentials to be solved by compressive sensing (CS, which allows reconstructing images from undersampled measurements with low error. Sparsity and incoherence are two essential requirements for CS. In this paper, we introduce surfacelet, a directional multiresolution transform for 3D data, to sparsify the hyperspectral images. Besides, a Gram-Schmidt orthogonalization is used in CS random encoding matrix, two-dimensional and three-dimensional orthogonal CS random encoding matrixes and a patch-based CS encoding scheme are designed. The proposed surfacelet-based hyperspectral images reconstruction problem is solved by a fast iterative shrinkage-thresholding algorithm. Experiments demonstrate that reconstruction of spectral lines and spatial images is significantly improved using the proposed method than using conventional three-dimensional wavelets, and growing randomness of encoding matrix can further improve the quality of hyperspectral data. Patch-based CS encoding strategy can be used to deal with large data because data in different patches can be independently sampled.

  16. Multi-view 3D reconstruction with volumetric registration in a freehand ultrasound imaging system

    Science.gov (United States)

    Yu, Honggang; Pattichis, Marios S.; Goens, M. Beth

    2006-03-01

    In this paper, we describe a new freehand ultrasound imaging system for reconstructing the left ventricle from 2D echocardiography slices. An important contribution of the proposed system is its ability to reconstruct from multiple standard views. The multi-view reconstruction procedure results in significant reduction in reconstruction error over single view reconstructions. The system uses object-based 3D volumetric registration, allowing for arbitrary rigid object movements in inter-view acquisition. Furthermore, a new segmentation procedure that combines level set methods with gradient vector flow(GVF) is used for automatically segmenting the 2D ultrasound images, in which low level of contrast, high level of speckle noise, and weak boundaries are common. The new segmentation approach is shown to be robust to these artifacts and is found to converge to the boundary from a wider range of initial conditions than competitive methods. The proposed system has been validated on a physical, 3D ultrasound calibration phantom and evaluated on one actual cardiac echocardiography data set. In the phantom experiment, two calibrated volumetric egg-shape objects were scanned from the top and side windows and reconstructed using the new method. The volume error was measured to be less than 4%. In a real heart data set experiment, qualitative results of 3D surface reconstruction from parasternal and apical views appear significantly improved over single view reconstructions. The estimated volumes from the 3D reconstructions were also found to be in agreement with the manual clinical measurements from 2D slices. Further extension of this work is to compare the quantitative results with more accuracy MRI data.

  17. A novel data processing technique for image reconstruction of penumbral imaging

    Science.gov (United States)

    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.

  18. Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction

    Science.gov (United States)

    Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N

    2011-01-01

    Objective We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Methods Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. Results The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (pASIR did not suppress the severe artefacts of contrast medium. Conclusion In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode. PMID:21081572

  19. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  20. Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2016-03-01

    Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using

  1. Statistical reconstruction algorithms for continuous wave electron spin resonance imaging

    Science.gov (United States)

    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.

  2. Tomographic Image Reconstruction Using Training Images with Matrix and Tensor Formulations

    DEFF Research Database (Denmark)

    Soltani, Sara

    Reducing X-ray exposure while maintaining the image quality is a major challenge in computed tomography (CT); since the imperfect data produced from the few view and/or low intensity projections results in low-quality images that are suffering from severe artifacts when using conventional...... the image resolution compared to a classical reconstruction method such as Filtered Back Projection (FBP). Some priors for the tomographic reconstruction take the form of cross-section images of similar objects, providing a set of the so-called training images, that hold the key to the structural...... information about the solution. The training images must be reliable and application-specific. This PhD project aims at providing a mathematical and computational framework for the use of training sets as non-parametric priors for the solution in tomographic image reconstruction. Through an unsupervised...

  3. Polarimetric ISAR: Simulation and image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Chambers, David H. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2016-03-21

    In polarimetric ISAR the illumination platform, typically airborne, carries a pair of antennas that are directed toward a fixed point on the surface as the platform moves. During platform motion, the antennas maintain their gaze on the point, creating an effective aperture for imaging any targets near that point. The interaction between the transmitted fields and targets (e.g. ships) is complicated since the targets are typically many wavelengths in size. Calculation of the field scattered from the target typically requires solving Maxwell’s equations on a large three-dimensional numerical grid. This is prohibitive to use in any real-world imaging algorithm, so the scattering process is typically simplified by assuming the target consists of a cloud of independent, non-interacting, scattering points (centers). Imaging algorithms based on this scattering model perform well in many applications. Since polarimetric radar is not very common, the scattering model is often derived for a scalar field (single polarization) where the individual scatterers are assumed to be small spheres. However, when polarization is important, we must generalize the model to explicitly account for the vector nature of the electromagnetic fields and its interaction with objects. In this note, we present a scattering model that explicitly includes the vector nature of the fields but retains the assumption that the individual scatterers are small. The response of the scatterers is described by electric and magnetic dipole moments induced by the incident fields. We show that the received voltages in the antennas are linearly related to the transmitting currents through a scattering impedance matrix that depends on the overall geometry of the problem and the nature of the scatterers.

  4. Optimized 3D Street Scene Reconstruction from Driving Recorder Images

    Directory of Open Access Journals (Sweden)

    Yongjun Zhang

    2015-07-01

    Full Text Available The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building.

  5. Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Gillam, John E. [The University of Sydney, Faculty of Health Sciences and The Brain and Mind Centre, Camperdown (Australia); Rafecas, Magdalena, E-mail: rafecas@imt.uni-luebeck.de [University of Lubeck, Institute of Medical Engineering, Ratzeburger Allee 160, 23538 Lübeck (Germany)

    2016-02-11

    Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.

  6. 40 CFR 63.1346 - Standards for new or reconstructed raw material dryers.

    Science.gov (United States)

    2010-07-01

    ... Industry Emission Standards and Operating Limits § 63.1346 Standards for new or reconstructed raw material dryers. (a) New or reconstructed raw material dryers located at facilities that are major sources can not... demonstrate a 98 percent reduction in THC emissions from the exit of the raw materials dryer to discharge to...

  7. Proton Computed Tomography: iterative image reconstruction and dose evaluation

    Science.gov (United States)

    Civinini, C.; Bonanno, D.; Brianzi, M.; Carpinelli, M.; Cirrone, G. A. P.; Cuttone, G.; Lo Presti, D.; Maccioni, G.; Pallotta, S.; Randazzo, N.; Scaringella, M.; Romano, F.; Sipala, V.; Talamonti, C.; Vanzi, E.; Bruzzi, M.

    2017-01-01

    Proton Computed Tomography (pCT) is a medical imaging method with a potential for increasing accuracy of treatment planning and patient positioning in hadron therapy. A pCT system based on a Silicon microstrip tracker and a YAG:Ce crystal calorimeter has been developed within the INFN Prima-RDH collaboration. The prototype has been tested with a 175 MeV proton beam at The Svedberg Laboratory (Uppsala, Sweden) with the aim to reconstruct and characterize a tomographic image. Algebraic iterative reconstruction methods (ART), together with the most likely path formalism, have been used to obtain tomographies of an inhomogeneous phantom to eventually extract density and spatial resolutions. These results will be presented and discussed together with an estimation of the average dose delivered to the phantom and the dependence of the image quality on the dose. Due to the heavy computation load required by the algebraic algorithms the reconstruction programs have been implemented to fully exploit the high calculation parallelism of Graphics Processing Units. An extended field of view pCT system is in an advanced construction stage. This apparatus will be able to reconstruct objects of the size of a human head making possible to characterize this pCT approach in a pre-clinical environment.

  8. Clinical evaluation of PET image reconstruction using a spatial resolution model

    DEFF Research Database (Denmark)

    Andersen, Flemming Littrup; Klausen, Thomas Levin; Loft, Annika

    2013-01-01

    reconstructed on 336×336-matrices using: (R1) standard AW-OSEM (4 iter, 8 subsets, 4mm Gaussian) and (R2) AW-OSEM with PSF (3 iter, 21 subsets, 2mm). Blinded and randomised reading of R1- and R2-PET images was performed. Individual lesions were located and counted independently on both sets of images......PURPOSE: PET image resolution is variable across the measured field-of-view and described by the point spread function (PSF). When accounting for the PSF during PET image reconstruction image resolution is improved and partial volume effects are reduced. Here, we evaluate the effect of PSF......-based reconstruction on lesion quantification in routine clinical whole-body (WB) PET/CT imaging. MATERIALS AND METHODS: 41 oncology patients were referred for a WB-PET/CT examination (Biograph 40 TruePoint). Emission data were acquired at 2.5min/bed at 1hpi of 400 MBq [18F]-FDG. Attenuation-corrected PET images were...

  9. Upgrade to iterative image reconstruction (IR) in abdominal MDCT imaging. A clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR)

    Energy Technology Data Exchange (ETDEWEB)

    Mueck, F.G.; Koerner, M.; Scherr, M.K.; Geyer, L.L.; Deak, Z.; Linsenmaier, U.; Reiser, M.; Wirth, S. [Ludwig-Maximilians-Univ. Muenchen (Germany). Inst. fuer Klinische Radiologie

    2012-03-15

    To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (-2: diagnostically inferior, -1: inferior, 0: equal, +1: superior, +2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 {+-} 5.5 to 12.2 {+-} 4.7 mGy (p < 0.001). The ICC was 0.861. The total image quality of the dose-reduced ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p < 0.01). After the system upgrade, the vendor recommendation of ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. (orig.)

  10. An estimation method of MR signal parameters for improved image reconstruction in unilateral scanner.

    Science.gov (United States)

    Bergman, Elad; Yeredor, Arie; Nevo, Uri

    2013-12-01

    Unilateral NMR devices are used in various applications including non-destructive testing and well logging, but are not used routinely for imaging. This is mainly due to the inhomogeneous magnetic field (B0) in these scanners. This inhomogeneity results in low sensitivity and further forces the use of the slow single point imaging scan scheme. Improving the measurement sensitivity is therefore an important factor as it can improve image quality and reduce imaging times. Short imaging times can facilitate the use of this affordable and portable technology for various imaging applications. This work presents a statistical signal-processing method, designed to fit the unique characteristics of imaging with a unilateral device. The method improves the imaging capabilities by improving the extraction of image information from the noisy data. This is done by the use of redundancy in the acquired MR signal and by the use of the noise characteristics. Both types of data were incorporated into a Weighted Least Squares estimation approach. The method performance was evaluated with a series of imaging acquisitions applied on phantoms. Images were extracted from each measurement with the proposed method and were compared to the conventional image reconstruction. All measurements showed a significant improvement in image quality based on the MSE criterion - with respect to gold standard reference images. An integration of this method with further improvements may lead to a prominent reduction in imaging times aiding the use of such scanners in imaging application. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. SIRFING: Sparse Image Reconstruction For INterferometry using GPUs

    Science.gov (United States)

    Cranmer, Miles; Garsden, Hugh; Mitchell, Daniel A.; Greenhill, Lincoln

    2018-01-01

    We present a deconvolution code for radio interferometric imaging based on the compressed sensing algorithms in Garsden et al. (2015). Being computationally intensive, compressed sensing is ripe for parallelization over GPUs. Our compressed sensing implementation generates images using wavelets, and we have ported the underlying wavelet library to CUDA, targeting the spline filter reconstruction part of the algorithm. The speedup achieved is almost an order of magnitude. The code is modular but is also being integrated into the calibration and imaging pipeline in use by the LEDA project at the Long Wavelength Array (LWA) as well as by the Murchinson Widefield Array (MWA).

  12. Sampling conditions for gradient-magnitude sparsity based image reconstruction algorithms

    DEFF Research Database (Denmark)

    Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    We seek to characterize the sampling conditions for iterative image reconstruction exploiting gradient-magnitude sparsity. We seek the number of views necessary for accurate image reconstruction by constrained, total variation (TV) minimization, which is the optimization problem suggested...

  13. Missing data reconstruction using Gaussian mixture models for fingerprint images

    Science.gov (United States)

    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.

  14. Complications of anterior cruciate ligament reconstruction: MR imaging

    Energy Technology Data Exchange (ETDEWEB)

    Papakonstantinou, Olympia; Chung, Christine B.; Chanchairujira, Kullanuch; Resnick, Donald L. [Department of Radiology, Veterans Affairs Medical Center, University of California, 3350 La Jolla Village Dr., San Diego, CA 92161 (United States)

    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. (orig.)

  15. Holographic images reconstructed from GMR-based fringe pattern

    Directory of Open Access Journals (Sweden)

    Kikuchi Hiroshi

    2013-01-01

    Full Text Available We have developed a magneto-optical spatial light modulator (MOSLM using giant magneto-resistance (GMR structures for realizing a holographic three-dimensional (3D display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.

  16. Holographic images reconstructed from GMR-based fringe pattern

    Science.gov (United States)

    Kato, Daisuke; Aoshima, Kenichi; Machida, Kenji; Emoto, Akira; Kinjo, Hidekazu; Kuga, Kiyoshi; Ono, Hiroshi; Ishibashi, Takayuki; Kikuchi, Hiroshi; Shimidzu, Naoki

    2013-01-01

    We have developed a magneto-optical spatial light modulator (MOSLM) using giant magneto-resistance (GMR) structures for realizing a holographic three-dimensional (3D) display. For practical applications, reconstructed image of hologram consisting of GMR structures should be investigated in order to study the feasibility of the MOSLM. In this study, we fabricated a hologram with GMR based fringe-pattern and demonstrated a reconstructed image. A fringe-pattern convolving a crossshaped image was calculated by a conventional binary computer generated hologram (CGH) technique. The CGH-pattern has 2,048 × 2,048 with 5 μm pixel pitch. The GMR stack consists of a Tb-Fe-Co/CoFe pinned layer, a Ag spacer, a Gd-Fe free layer for light modulation, and a Ru capping layer, was deposited by dc-magnetron sputtering. The GMR hologram was formed using photo-lithography and Krion milling processes, followed by the deposition of a Tb-Fe-Co reference layer with large coercivity and the same Kerr-rotation angle compared to the free layer, and a lift-off process. The reconstructed image of the ON-state was clearly observed and successfully distinguished from the OFF-state by switching the magnetization direction of the free-layer with an external magnetic field. These results indicate the possibility of realizing a holographic 3D display by the MOSLM using the GMR structures.

  17. Applicator reconstruction in MRI 3D image-based dose planning of brachytherapy for cervical cancer.

    Science.gov (United States)

    Haack, Søren; Nielsen, Søren Kynde; Lindegaard, Jacob Christian; Gelineck, John; Tanderup, Kari

    2009-05-01

    To elaborate a method for applicator reconstruction for MRI-based brachytherapy for cervical cancer. Custom-made plastic catheters with a copper sulphate solution were made for insertion in the source channels of MR-CT compatible applicators: plastic and titanium tandem ring applicators, and titanium needles. The applicators were CT and MR scanned in a phantom for accurate 3D assessment of applicator visibility and geometry. A reconstruction method was developed and evaluated in 19 patient MR examinations with ring applicator (plastic: 14, titanium: 5). MR applicator reconstruction uncertainties related to inter-observer variation were evaluated. The catheters were visible in the plastic applicator on T1-weighted images in phantom and in 14/14 clinical applications. On T2-weighted images, the catheters appeared weaker but still visible in phantom and in 13/14 MR clinical applications. In the titanium applicator, the catheters could not be separated from the artifacts from the applicator itself. However, these artifacts could be used to localize both titanium ring applicator (5/5 clinical applications) and needles (6/6 clinical applications). Standard deviations of inter-observer differences were below 2 mm in all directions. 3D applicator reconstruction based on MR imaging could be performed for plastic and titanium applicators. Plastic applicators proved well to be suited for MRI-based reconstruction. For improved practicability of titanium applicator reconstruction, development of MR applicator markers is essential. Reconstruction of titanium applicator and needles at 1.5 T MR requires geometric evaluations in phantoms before using the applicator in patients.

  18. Deterministic Compressive Sampling for High-Quality Image Reconstruction of Ultrasound Tomography

    CERN Document Server

    Quang-Huy, Tran; Tue, Huynh Huu; Linh-Trung, Nguyen

    2015-01-01

    A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. Compressed Sensing (CS) technique was applied to the detection geometry configuration of ultrasound tomography as a powerful tool for improved image reconstruction quality. However, this configuration is very difficult to implement in practice. Inspired of easier hardware implementation of deterministic CS, in this paper, we propose the chaos measurements in the detection geometry configuration and the image reconstruction process is implemen...

  19. A comparison of five standard methods for evaluating image intensity uniformity in partially parallel imaging MRI.

    Science.gov (United States)

    Goerner, Frank L; Duong, Timothy; Stafford, R Jason; Clarke, Geoffrey D

    2013-08-01

    To investigate the utility of five different standard measurement methods for determining image uniformity for partially parallel imaging (PPI) acquisitions in terms of consistency across a variety of pulse sequences and reconstruction strategies. Images were produced with a phantom using a 12-channel head matrix coil in a 3T MRI system (TIM TRIO, Siemens Medical Solutions, Erlangen, Germany). Images produced using echo-planar, fast spin echo, gradient echo, and balanced steady state free precession pulse sequences were evaluated. Two different PPI reconstruction methods were investigated, generalized autocalibrating partially parallel acquisition algorithm (GRAPPA) and modified sensitivity-encoding (mSENSE) with acceleration factors (R) of 2, 3, and 4. Additionally images were acquired with conventional, two-dimensional Fourier imaging methods (R=1). Five measurement methods of uniformity, recommended by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) were considered. The methods investigated were (1) an ACR method and a (2) NEMA method for calculating the peak deviation nonuniformity, (3) a modification of a NEMA method used to produce a gray scale uniformity map, (4) determining the normalized absolute average deviation uniformity, and (5) a NEMA method that focused on 17 areas of the image to measure uniformity. Changes in uniformity as a function of reconstruction method at the same R-value were also investigated. Two-way analysis of variance (ANOVA) was used to determine whether R-value or reconstruction method had a greater influence on signal intensity uniformity measurements for partially parallel MRI. Two of the methods studied had consistently negative slopes when signal intensity uniformity was plotted against R-value. The results obtained comparing mSENSE against GRAPPA found no consistent difference between GRAPPA and mSENSE with regard to signal intensity uniformity. The results of the two

  20. Upgrade to iterative image reconstruction (IR) in abdominal MDCT imaging: a clinical study for detailed parameter optimization beyond vendor recommendations using the adaptive statistical iterative reconstruction environment (ASIR).

    Science.gov (United States)

    Mueck, F G; Körner, M; Scherr, M K; Geyer, L L; Deak, Z; Linsenmaier, U; Reiser, M; Wirth, S

    2012-03-01

    To compare the image quality of dose-reduced 64-row abdominal CT reconstructed at different levels of adaptive statistical iterative reconstruction (ASIR) to full-dose baseline examinations reconstructed with filtered back-projection (FBP) in a clinical setting and upgrade situation. Abdominal baseline examinations (noise index NI = 29; LightSpeed VCT XT, GE) were intra-individually compared to follow-up studies on a CT with an ASIR option (NI = 43; Discovery HD750, GE), n = 42. Standard-kernel images were calculated with ASIR blendings of 0 - 100 % in slice and volume mode, respectively. Three experienced radiologists compared the image quality of these 567 sets to their corresponding full-dose baseline examination (- 2: diagnostically inferior, - 1: inferior, 0: equal, + 1: superior, + 2: diagnostically superior). Furthermore, a phantom was scanned. Statistical analysis used the Wilcoxon - the Mann-Whitney U-test and the intra-class correlation (ICC). The mean CTDIvol decreased from 19.7 ± 5.5 to 12.2 ± 4.7 mGy (p ASIR studies was comparable to the baseline at ASIR 50 % in slice (p = 0.18) and ASIR 50 - 100 % in volume mode (p > 0.10). Volume mode performed 73 % slower than slice mode (p ASIR 50 % in slice mode allowed for a dose reduction of 38 % in abdominal CT with comparable image quality and time expenditure. However, there is still further dose reduction potential for more complex reconstruction settings. © Georg Thieme Verlag KG Stuttgart · New York.

  1. PHOTOGRAMMETRIC 3D BUILDING RECONSTRUCTION FROM THERMAL IMAGES

    Directory of Open Access Journals (Sweden)

    E. Maset

    2017-08-01

    Full Text Available This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

  2. Photogrammetric 3d Building Reconstruction from Thermal Images

    Science.gov (United States)

    Maset, E.; Fusiello, A.; Crosilla, F.; Toldo, R.; Zorzetto, D.

    2017-08-01

    This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR) images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV) and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP) algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

  3. Stokes image reconstruction for two-color microgrid polarization imaging systems.

    Science.gov (United States)

    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.

  4. Standard digital reference images for titanium castings

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2010-01-01

    1.1 The digital reference images provided in the adjunct to this standard illustrate various types and degrees of discontinuities occurring in titanium castings. Use of this standard for the specification or grading of castings requires procurement of the adjunct digital reference images, which illustrate the discontinuity types and severity levels. They are intended to provide the following: 1.1.1 A guide enabling recognition of titanium casting discontinuities and their differentiation both as to type and degree through digital radiographic examination. 1.1.2 Example digital radiographic illustrations of discontinuities and a nomenclature for reference in acceptance standards, specifications and drawings. 1.2 The digital reference images consist of seventeen digital files each illustrating eight grades of increasing severity. The files illustrate seven common discontinuity types representing casting sections up to 1-in. (25.4-mm). 1.3 The reference radiographs were developed for casting sections up to 1...

  5. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

    2017-05-01

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

  6. Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies.

    Science.gov (United States)

    Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

    2017-05-07

    Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18 F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans-each containing 1/8th of the total number of events-were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18 F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

  7. Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality - preliminary findings

    Energy Technology Data Exchange (ETDEWEB)

    Mieville, Frederic A. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland); University Hospital Center and University of Lausanne, Institute of Radiation Physics - Medical Radiology, Lausanne (Switzerland); Gudinchet, Francois; Rizzo, Elena [University Hospital Center and University of Lausanne, Department of Radiology, Lausanne (Switzerland); Ou, Phalla; Brunelle, Francis [Necker Children' s Hospital, Department of Radiology, Paris (France); Bochud, Francois O.; Verdun, Francis R. [University Hospital Center and University of Lausanne, Institute of Radiation Physics, Lausanne (Switzerland)

    2011-09-15

    Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI{sub vol} 4.8-7.9 mGy, DLP 37.1-178.9 mGy.cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p < 0.001) whereas with ASIR above 50%, image quality significantly decreased (p < 0.001). With 100% ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone. (orig.)

  8. Preoperative implant selection for unilateral breast reconstruction using 3D imaging with the Microsoft Kinect sensor.

    Science.gov (United States)

    Pöhlmann, Stefanie T L; Harkness, Elaine; Taylor, Christopher J; Gandhi, Ashu; Astley, Susan M

    2017-08-01

    This study aimed to investigate whether breast volume measured preoperatively using a Kinect 3D sensor could be used to determine the most appropriate implant size for reconstruction. Ten patients underwent 3D imaging before and after unilateral implant-based reconstruction. Imaging used seven configurations, varying patient pose and Kinect location, which were compared regarding suitability for volume measurement. Four methods of defining the breast boundary for automated volume calculation were compared, and repeatability assessed over five repetitions. The most repeatable breast boundary annotation used an ellipse to track the inframammary fold and a plane describing the chest wall (coefficient of repeatability: 70 ml). The most reproducible imaging position comparing pre- and postoperative volume measurement of the healthy breast was achieved for the sitting patient with elevated arms and Kinect centrally positioned (coefficient of repeatability: 141 ml). Optimal implant volume was calculated by correcting used implant volume by the observed postoperative asymmetry. It was possible to predict implant size using a linear model derived from preoperative volume measurement of the healthy breast (coefficient of determination R(2) = 0.78, standard error of prediction 120 ml). Mastectomy specimen weight and experienced surgeons' choice showed similar predictive ability (both: R(2) = 0.74, standard error: 141/142 ml). A leave one-out validation showed that in 61% of cases, 3D imaging could predict implant volume to within 10%; however for 17% of cases it was >30%. This technology has the potential to facilitate reconstruction surgery planning and implant procurement to maximise symmetry after unilateral reconstruction. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

  9. Stable Image Registration for In-Vivo Fetoscopic Panorama Reconstruction

    Directory of Open Access Journals (Sweden)

    Floris Gaisser

    2018-01-01

    Full Text Available A Twin-to-Twin Transfusion Syndrome (TTTS is a condition that occurs in about 10% of pregnancies involving monochorionic twins. This complication can be treated with fetoscopic laser coagulation. The procedure could greatly benefit from panorama reconstruction to gain an overview of the placenta. In previous work we investigated which steps could improve the reconstruction performance for an in-vivo setting. In this work we improved this registration by proposing a stable region detection method as well as extracting matchable features based on a deep-learning approach. Finally, we extracted a measure for the image registration quality and the visibility condition. With experiments we show that the image registration performance is increased and more constant. Using these methods a system can be developed that supports the surgeon during the surgery, by giving feedback and providing a more complete overview of the placenta.

  10. A maximum entropy reconstruction technique for tomographic particle image velocimetry

    Science.gov (United States)

    Bilsky, A. V.; Lozhkin, V. A.; Markovich, D. M.; Tokarev, M. P.

    2013-04-01

    This paper studies a novel approach for reducing tomographic PIV computational complexity. The proposed approach is an algebraic reconstruction technique, termed MENT (maximum entropy). This technique computes the three-dimensional light intensity distribution several times faster than SMART, using at least ten times less memory. Additionally, the reconstruction quality remains nearly the same as with SMART. This paper presents the theoretical computation performance comparison for MENT, SMART and MART, followed by validation using synthetic particle images. Both the theoretical assessment and validation of synthetic images demonstrate significant computational time reduction. The data processing accuracy of MENT was compared to that of SMART in a slot jet experiment. A comparison of the average velocity profiles shows a high level of agreement between the results obtained with MENT and those obtained with SMART.

  11. Fan beam image reconstruction with generalized Fourier slice theorem.

    Science.gov (United States)

    Zhao, Shuangren; Yang, Kang; Yang, Kevin

    2014-01-01

    For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.

  12. Laboratory demonstration of image reconstruction for coherent optical system of modular imaging collectors (COSMIC)

    Science.gov (United States)

    Traub, W. A.

    1984-01-01

    The first physical demonstration of the principle of image reconstruction using a set of images from a diffraction-blurred elongated aperture is reported. This is an optical validation of previous theoretical and numerical simulations of the COSMIC telescope array (coherent optical system of modular imaging collectors). The present experiment utilizes 17 diffraction blurred exposures of a laboratory light source, as imaged by a lens covered by a narrow-slit aperture; the aperture is rotated 10 degrees between each exposure. The images are recorded in digitized form by a CCD camera, Fourier transformed, numerically filtered, and added; the sum is then filtered and inverse Fourier transformed to form the final image. The image reconstruction process is found to be stable with respect to uncertainties in values of all physical parameters such as effective wavelength, rotation angle, pointing jitter, and aperture shape. Future experiments will explore the effects of low counting rates, autoguiding on the image, various aperture configurations, and separated optics.

  13. PSNR BASED OPTIMIZATION APPLIED TO ALGEBRAIC RECONSTRUCTION TECHNIQUE FOR IMAGE RECONSTRUCTION ON A MULTI-CORE SYSTEM

    Directory of Open Access Journals (Sweden)

    Bharathi Lakshmi Agnimarimuthu

    2017-06-01

    Full Text Available The present work attempts to reveal a parallel Algebraic Reconstruction Technique (pART to reduce the computational speed of reconstructing artifact-free images from projections. ART is an iterative algorithm well known to reconstruct artifact-free images with limited number of projections. In this work, a novel idea has been focused on to optimize the number of iterations mandatory based on Peak to Signal Noise Ratio (PSNR to reconstruct an image. However, it suffers of worst computation speed. Hence, an attempt is made to reduce the computation time by running iterative algorithm on a multi-core parallel environment. The execution times are computed for both serial and parallel implementations of ART using different projection data, and, tabulated for comparison. The experimental results demonstrate that the parallel computing environment provides a source of high computational power leading to obtain reconstructed image instantaneously.

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Science.gov (United States)

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

    2016-11-22

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

  16. A Novel Kernel-Based Regularization Technique for PET Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Abdelwahhab Boudjelal

    2017-06-01

    Full Text Available Positron emission tomography (PET is an imaging technique that generates 3D detail of physiological processes at the cellular level. The technique requires a radioactive tracer, which decays and releases a positron that collides with an electron; consequently, annihilation photons are emitted, which can be measured. The purpose of PET is to use the measurement of photons to reconstruct the distribution of radioisotopes in the body. Currently, PET is undergoing a revamp, with advancements in data measurement instruments and the computing methods used to create the images. These computer methods are required to solve the inverse problem of “image reconstruction from projection”. This paper proposes a novel kernel-based regularization technique for maximum-likelihood expectation-maximization ( κ -MLEM to reconstruct the image. Compared to standard MLEM, the proposed algorithm is more robust and is more effective in removing background noise, whilst preserving the edges; this suppresses image artifacts, such as out-of-focus slice blur.

  17. Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography.

    Science.gov (United States)

    Huy, Tran Quang; Tue, Huynh Huu; Long, Ton That; Duc-Tan, Tran

    2017-05-25

    A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. One of the challenges for a high quality reconstruction is to obtain many measurements from the number of transmitters and receivers. Given the fact that biomedical images are often sparse, the compressed sensing (CS) technique could be therefore effectively applied to ultrasound tomography by reducing the number of transmitters and receivers, while maintaining a high quality of image reconstruction. There are currently several work on CS that dispose randomly distributed locations for the measurement system. However, this random configuration is relatively difficult to implement in practice. Instead of it, we should adopt a methodology that helps determine the locations of measurement devices in a deterministic way. For this, we develop the novel DCS-DBIM algorithm that is highly applicable in practice. Inspired of the exploitation of the deterministic compressed sensing technique (DCS) introduced by the authors few years ago with the image reconstruction process implemented using l 1 regularization. Simulation results of the proposed approach have demonstrated its high performance, with the normalized error approximately 90% reduced, compared to the conventional approach, this new approach can save half of number of measurements and only uses two iterations. Universal image quality index is also evaluated in order to prove the efficiency of the proposed approach. Numerical simulation results

  18. Enhanced imaging colonoscopy facilitates dense motion-based 3D reconstruction.

    Science.gov (United States)

    Alcantarilla, Pablo F; Bartoli, Adrien; Chadebecq, Francois; Tilmant, Christophe; Lepilliez, Vincent

    2013-01-01

    We propose a novel approach for estimating a dense 3D model of neoplasia in colonoscopy using enhanced imaging endoscopy modalities. Estimating a dense 3D model of neoplasia is important to make 3D measurements and to classify the superficial lesions in standard frameworks such as the Paris classification. However, it is challenging to obtain decent dense 3D models using computer vision techniques such as Structure-from-Motion due to the lack of texture in conventional (white light) colonoscopy. Therefore, we propose to use enhanced imaging endoscopy modalities such as Narrow Band Imaging and chromoendoscopy to facilitate the 3D reconstruction process. Thanks to the use of these enhanced endoscopy techniques, visualization is improved, resulting in more reliable feature tracks and 3D reconstruction results. We first build a sparse 3D model of neoplasia using Structure-from-Motion from enhanced endoscopy imagery. Then, the sparse reconstruction is densified using a Multi-View Stereo approach, and finally the dense 3D point cloud is transformed into a mesh by means of Poisson surface reconstruction. The obtained dense 3D models facilitate classification of neoplasia in the Paris classification, in which the 3D size and the shape of the neoplasia play a major role in the diagnosis.

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

    Energy Technology Data Exchange (ETDEWEB)

    Solomon, Justin, E-mail: justin.solomon@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Biomedical Engineering and Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27705 (United States)

    2014-09-15

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

  20. CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION FROM IMAGES AND VIDEOS

    Directory of Open Access Journals (Sweden)

    D. Bulatov

    2012-07-01

    Full Text Available Detection of buildings and vegetation, and even more reconstruction of urban terrain from sequences of aerial images and videos is known to be a challenging task. It has been established that those methods that have as input a high-quality Digital Surface Model (DSM, are more straight-forward and produce more robust and reliable results than those image-based methods that require matching line segments or even whole regions. This motivated us to develop a new dense matching technique for DSM generation that is capable of simultaneous integration of multiple images in the reconstruction process. The DSMs generated by this new multi-image matching technique can be used for urban object extraction. In the first contribution of this paper, two examples of external sources of information added to the reconstruction pipeline will be shown. The GIS layers are used for recognition of streets and suppressing false alarms in the depth maps that were caused by moving vehicles while the near infrared channel is applied for separating vegetation from buildings. Three examples of data sets including both UAV-borne video sequences with a relatively high number of frames and high-resolution (10 cm ground sample distance data sets consisting of (few spatial-temporarily diverse images from large-format aerial frame cameras, will be presented. By an extensive quantitative evaluation of the Vaihingen block from the ISPRS benchmark on urban object detection, it will become clear that our procedure allows a straight-forward, efficient, and reliable instantiation of 3D city models.

  1. Reduced Radiation Dose with Model-based Iterative Reconstruction versus Standard Dose with Adaptive Statistical Iterative Reconstruction in Abdominal CT for Diagnosis of Acute Renal Colic.

    Science.gov (United States)

    Fontarensky, Mikael; Alfidja, Agaïcha; Perignon, Renan; Schoenig, Arnaud; Perrier, Christophe; Mulliez, Aurélien; Guy, Laurent; Boyer, Louis

    2015-07-01

    To evaluate the accuracy of reduced-dose abdominal computed tomographic (CT) imaging by using a new generation model-based iterative reconstruction (MBIR) to diagnose acute renal colic compared with a standard-dose abdominal CT with 50% adaptive statistical iterative reconstruction (ASIR). This institutional review board-approved prospective study included 118 patients with symptoms of acute renal colic who underwent the following two successive CT examinations: standard-dose ASIR 50% and reduced-dose MBIR. Two radiologists independently reviewed both CT examinations for presence or absence of renal calculi, differential diagnoses, and associated abnormalities. The imaging findings, radiation dose estimates, and image quality of the two CT reconstruction methods were compared. Concordance was evaluated by κ coefficient, and descriptive statistics and t test were used for statistical analysis. Intraobserver correlation was 100% for the diagnosis of renal calculi (κ = 1). Renal calculus (τ = 98.7%; κ = 0.97) and obstructive upper urinary tract disease (τ = 98.16%; κ = 0.95) were detected, and differential or alternative diagnosis was performed (τ = 98.87% κ = 0.95). MBIR allowed a dose reduction of 84% versus standard-dose ASIR 50% (mean volume CT dose index, 1.7 mGy ± 0.8 [standard deviation] vs 10.9 mGy ± 4.6; mean size-specific dose estimate, 2.2 mGy ± 0.7 vs 13.7 mGy ± 3.9; P < .001) without a conspicuous deterioration in image quality (reduced-dose MBIR vs ASIR 50% mean scores, 3.83 ± 0.49 vs 3.92 ± 0.27, respectively; P = .32) or increase in noise (reduced-dose MBIR vs ASIR 50% mean, respectively, 18.36 HU ± 2.53 vs 17.40 HU ± 3.42). Its main drawback remains the long time required for reconstruction (mean, 40 minutes). A reduced-dose protocol with MBIR allowed a dose reduction of 84% without increasing noise and without an conspicuous deterioration in image quality in patients suspected of having renal colic.

  2. The quest for standards in medical imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gibaud, Bernard, E-mail: bernard.gibaud@irisa.fr [INSERM, VisAGeS U746 Unit/Project, Faculty of Medicine, Campus de Villejean, F-35043 Rennes (France); INRIA, VisAGeS U746 Unit/Project, IRISA, Campus de Beaulieu, F-35042 Rennes (France); University of Rennes I-CNRS UMR 6074, IRISA, Campus de Beaulieu, F-35042 Rennes (France)

    2011-05-15

    This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.

  3. Optimization of image reconstruction conditions with phantoms for brain FDG and amyloid PET imaging

    National Research Council Canada - National Science Library

    Akamatsu, Go; Ikari, Yasuhiko; Nishio, Tomoyuki; Nishida, Hiroyuki; Ohnishi, Akihito; Aita, Kazuki; Sasaki, Masahiro; Sasaki, Masayuki; Senda, Michio

    2016-01-01

    The purpose of this study was to optimize image reconstruction conditions for brain 18F-FDG, 11C-PiB, 18F-florbetapir and 18F-flutemetamol PET imaging with Discovery-690 PET/CT for diagnosis and research on Alzheimer’s disease (AD...

  4. Image Reconstruction and Discrimination at Low Light Levels

    Science.gov (United States)

    Zerom, Petros

    Quantum imaging is a recent and promising branch of quantum optics that exploits the quantum nature of light. Improving the limitations imposed by classical sources of light in optical imaging techniques or overcoming the classical boundaries of image formation is one of the key motivations in quantum imaging. In this thesis, I describe certain aspects of both quantum and thermal ghost imaging and I also study image discrimination with high fidelity at low light levels. First of all, I present a theoretical and experimental study of entangled-photon compressive ghost imaging. In quantum ghost imaging using entangled photon pairs, the brightness of readily available sources is rather weak. The usual technique of image acquisition in this imaging modality is to raster scan a single-pixel single-photon sensitive detector in one arm of a ghost imaging setup. In most imaging modalities, the number of measurements required to fully resolve an object is dependent on the measurement's Nyquist limit. In the first part of the thesis, I propose a ghost imaging (GI) configuration that uses bucket detectors (as opposed to a raster scanning detector) in both arms of the GI setup. High resolution image reconstruction using only 27% of the measurement's Nyquist limit using compressed sensing algorithms are presented. The second part of my thesis deals with thermal ghost imaging. Unlike in quantum GI, bright and spatially correlated classical sources of radiation are used in thermal GI. Usually high-contrast speckle patterns are used as sources of the correlated beams of radiation. I study the effect of the field statistics of the illuminating source on the quality of ghost images. I show theoretically and experimentally that a thermal GI setup can produce high quality images even when low-contrast (intensity-averaged) speckle patterns are used as an illuminating source, as long as the collected signal is mainly caused by the random fluctuation of the incident speckle field, as

  5. Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

    Science.gov (United States)

    Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

    2016-10-01

    Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

  6. Object segmentation controls image reconstruction from natural scenes.

    Science.gov (United States)

    Neri, Peter

    2017-08-01

    The structure of the physical world projects images onto our eyes. However, those images are often poorly representative of environmental structure: well-defined boundaries within the eye may correspond to irrelevant features of the physical world, while critical features of the physical world may be nearly invisible at the retinal projection. The challenge for the visual cortex is to sort these two types of features according to their utility in ultimately reconstructing percepts and interpreting the constituents of the scene. We describe a novel paradigm that enabled us to selectively evaluate the relative role played by these two feature classes in signal reconstruction from corrupted images. Our measurements demonstrate that this process is quickly dominated by the inferred structure of the environment, and only minimally controlled by variations of raw image content. The inferential mechanism is spatially global and its impact on early visual cortex is fast. Furthermore, it retunes local visual processing for more efficient feature extraction without altering the intrinsic transduction noise. The basic properties of this process can be partially captured by a combination of small-scale circuit models and large-scale network architectures. Taken together, our results challenge compartmentalized notions of bottom-up/top-down perception and suggest instead that these two modes are best viewed as an integrated perceptual mechanism.

  7. Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Qiaofeng; Sawatzky, Alex; Anastasio, Mark A., E-mail: anastasio@wustl.edu [Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130 (United States); Yang, Deshan [Department of Radiation Oncology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri 63110 (United States); Tan, Jun [Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States)

    2016-04-15

    Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated

  8. Impact of iterative reconstruction on image quality and radiation dose in multidetector CT of large body size adults.

    Science.gov (United States)

    Desai, Gaurav S; Uppot, Raul N; Yu, Elaine W; Kambadakone, Avinash R; Sahani, Dushyant V

    2012-08-01

    To compare image quality and radiation dose using Adaptive Statistical Iterative Reconstruction (ASiR) and Filtered Back Projection (FBP) in patients weighing ≥ 91 kg. In this Institution Review Board-approved retrospective study, single-phase contrast-enhanced abdominopelvic CT examinations of 100 adults weighing ≥ 91 kg (mean body weight: 107.6 ± 17.4 kg range: 91-181.9 kg) with (1) ASiR and (2) FBP were reviewed by two readers in a blinded fashion for subjective measures of image quality (using a subjective standardized numerical scale and objective noise) and for radiation exposure. Imaging parameters and radiation dose results of the two techniques were compared within weight and BMI sub-categories. All examinations were found to be of adequate quality. Both subjective (mean = 1.4 ± 0.5 vs. 1.6 ± 0.6, P image quality were comparable between the two techniques. Trends for all parameters were similar in patients across weight and BMI sub-categories. In obese individuals, abdominal CT images reconstructed using ASiR provide diagnostic images with reduced image noise at lower radiation dose. • CT images in obese adults are noisy, even with high radiation dose. • Newer iterative reconstruction techniques have theoretical advantages in obese patients. • Adaptive statistical iterative reconstruction should reduce image noise and radiation dose. • This has been proven in abdominopelvic CT images of obese patients.

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

    Science.gov (United States)

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

    2014-01-01

    Purpose To retrospectively compare image quality and radiation dose between a reduced-dose computed tomographic (CT) protocol that uses model-based iterative reconstruction (MBIR) and a standard-dose CT protocol that uses 30% adaptive statistical iterative reconstruction (ASIR) with filtered back projection. Materials and Methods Institutional review board approval was obtained. Clinical CT images of the chest, abdomen, and pelvis obtained with a reduced-dose protocol were identified. Images were reconstructed with two algorithms: MBIR and 100% ASIR. All subjects had undergone standard-dose CT within the prior year, and the images were reconstructed with 30% ASIR. Reduced- and standard-dose images were evaluated objectively and subjectively. Reduced-dose images were evaluated for lesion detectability. Spatial resolution was assessed in a phantom. Radiation dose was estimated by using volumetric CT dose index (CTDIvol) and calculated size-specific dose estimates (SSDE). A combination of descriptive statistics, analysis of variance, and t tests was used for statistical analysis. Results In the 25 patients who underwent the reduced-dose protocol, mean decrease in CTDIvol was 46% (range, 19%–65%) and mean decrease in SSDE was 44% (range, 19%–64%). Reduced-dose MBIR images had less noise (P > .004). Spatial resolution was superior for reduced-dose MBIR images. Reduced-dose MBIR images were equivalent to standard-dose images for lungs and soft tissues (P > .05) but were inferior for bones (P = .004). Reduced-dose 100% ASIR images were inferior for soft tissues (P ASIR. Conclusion CT performed with a reduced-dose protocol and MBIR is feasible in the pediatric population, and it maintains diagnostic quality. © RSNA, 2013 Online supplemental material is available for this article. PMID:24091359

  10. GF-4 Images Super Resolution Reconstruction Based on POCS

    Directory of Open Access Journals (Sweden)

    XU Lina

    2017-08-01

    Full Text Available The super resolution reconstruction of GF-4 is made by projection on convex sets (POCS. Papoulis-Gerchberg is used to construct reference frame which can reduce iteration and improve algorithm efficiency.Vandewalle is used to estimate motion parameter which is benefit to block process. Tested and analyzed by real GF-4 series images, it shows that sharpness of super resolution result is positive correlatie to frame amount, and signal to noise ratio (SNR is negative correlate to frame amount. After processing by 5 frames, information entropy (IE changes little; sharpness (average gradient increases from 7.803 to 14.386; SNR reduces a little, from 3.411 to 3.336. The experiment shows that after super resolution reconstruction, sharpness and detail information of results can be greatly improved.

  11. A novel partial volume effects correction technique integrating deconvolution associated with denoising within an iterative PET image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Merlin, Thibaut, E-mail: thibaut.merlin@telecom-bretagne.eu [Université Bordeaux INCIA, CNRS UMR 5287, Hôpital de Bordeaux , Bordeaux 33 33076 (France); Visvikis, Dimitris [INSERM, UMR1101, LaTIM, Université de Bretagne Occidentale, Brest 29 29609 (France); Fernandez, Philippe; Lamare, Frederic [Université Bordeaux INCIA, CNRS UMR 5287, Hôpital de Bordeaux, Bordeaux 33 33076 (France)

    2015-02-15

    Purpose: Partial volume effect (PVE) plays an important role in both qualitative and quantitative PET image accuracy, especially for small structures. A previously proposed voxelwise PVE correction method applied on PET reconstructed images involves the use of Lucy–Richardson deconvolution incorporating wavelet-based denoising to limit the associated propagation of noise. The aim of this study is to incorporate the deconvolution, coupled with the denoising step, directly inside the iterative reconstruction process to further improve PVE correction. Methods: The list-mode ordered subset expectation maximization (OSEM) algorithm has been modified accordingly with the application of the Lucy–Richardson deconvolution algorithm to the current estimation of the image, at each reconstruction iteration. Acquisitions of the NEMA NU2-2001 IQ phantom were performed on a GE DRX PET/CT system to study the impact of incorporating the deconvolution inside the reconstruction [with and without the point spread function (PSF) model] in comparison to its application postreconstruction and to standard iterative reconstruction incorporating the PSF model. The impact of the denoising step was also evaluated. Images were semiquantitatively assessed by studying the trade-off between the intensity recovery and the noise level in the background estimated as relative standard deviation. Qualitative assessments of the developed methods were additionally performed on clinical cases. Results: Incorporating the deconvolution without denoising within the reconstruction achieved superior intensity recovery in comparison to both standard OSEM reconstruction integrating a PSF model and application of the deconvolution algorithm in a postreconstruction process. The addition of the denoising step permitted to limit the SNR degradation while preserving the intensity recovery. Conclusions: This study demonstrates the feasibility of incorporating the Lucy–Richardson deconvolution associated with a

  12. Automatic speed of sound correction with photoacoustic image reconstruction

    Science.gov (United States)

    Ye, Meng; Cao, Meng; Feng, Ting; Yuan, Jie; Cheng, Qian; Liu, XIaojun; Xu, Guan; Wang, Xueding

    2016-03-01

    Sound velocity measurement is of great importance to the application of biomedical especially in the research of acoustic detection and acoustic tomography. Using correct sound velocities in each medium other than one unified sound propagation speed, we can effectively enhance sound based imaging resolution. Photoacoustic tomography (PAT), is defined as cross-sectional or three-dimensional (3D) imaging of a material based on the photoacoustic effect and it is a developing, non-invasive imaging method in biomedical research. This contribution proposes a method to concurrently calculate multiple acoustic speeds in different mediums. Firstly, we get the size of infra-structure of the target by B-mode ultrasonic imaging method. Then we build the photoacoustic (PA) image of the same target with different acoustic speed in different medium. By repeatedly evaluate the quality of reconstruct PA image, we dynamically calibrate the acoustic speeds in different medium to build a finest PA image. Thus, we take these speeds of sound as the correct acoustic propagation velocities in according mediums. Experiments show that our non-invasive method can yield correct speed of sound with less than 0.3% error which might benefit future research in biomedical science.

  13. A quantitative reconstruction software suite for SPECT imaging

    Science.gov (United States)

    Namías, Mauro; Jeraj, Robert

    2017-11-01

    Quantitative Single Photon Emission Tomography (SPECT) imaging allows for measurement of activity concentrations of a given radiotracer in vivo. Although SPECT has usually been perceived as non-quantitative by the medical community, the introduction of accurate CT based attenuation correction and scatter correction from hybrid SPECT/CT scanners has enabled SPECT systems to be as quantitative as Positron Emission Tomography (PET) systems. We implemented a software suite to reconstruct quantitative SPECT images from hybrid or dedicated SPECT systems with a separate CT scanner. Attenuation, scatter and collimator response corrections were included in an Ordered Subset Expectation Maximization (OSEM) algorithm. A novel scatter fraction estimation technique was introduced. The SPECT/CT system was calibrated with a cylindrical phantom and quantitative accuracy was assessed with an anthropomorphic phantom and a NEMA/IEC image quality phantom. Accurate activity measurements were achieved at an organ level. This software suite helps increasing quantitative accuracy of SPECT scanners.

  14. High fidelity system modeling for high quality image reconstruction in clinical CT.

    Directory of Open Access Journals (Sweden)

    Synho Do

    Full Text Available Today, while many researchers focus on the improvement of the regularization term in IR algorithms, they pay less concern to the improvement of the fidelity term. In this paper, we hypothesize that improving the fidelity term will further improve IR image quality in low-dose scanning, which typically causes more noise. The purpose of this paper is to systematically test and examine the role of high-fidelity system models using raw data in the performance of iterative image reconstruction approach minimizing energy functional. We first isolated the fidelity term and analyzed the importance of using focal spot area modeling, flying focal spot location modeling, and active detector area modeling as opposed to just flying focal spot motion. We then compared images using different permutations of all three factors. Next, we tested the ability of the fidelity terms to retain signals upon application of the regularization term with all three factors. We then compared the differences between images generated by the proposed method and Filtered-Back-Projection. Lastly, we compared images of low-dose in vivo data using Filtered-Back-Projection, Iterative Reconstruction in Image Space, and the proposed method using raw data. The initial comparison of difference maps of images constructed showed that the focal spot area model and the active detector area model also have significant impacts on the quality of images produced. Upon application of the regularization term, images generated using all three factors were able to substantially decrease model mismatch error, artifacts, and noise. When the images generated by the proposed method were tested, conspicuity greatly increased, noise standard deviation decreased by 90% in homogeneous regions, and resolution also greatly improved. In conclusion, the improvement of the fidelity term to model clinical scanners is essential to generating higher quality images in low-dose imaging.

  15. Dynamic relaxation in algebraic reconstruction technique (ART) for breast tomosynthesis imaging.

    Science.gov (United States)

    Oliveira, N; Mota, A M; Matela, N; Janeiro, L; Almeida, P

    2016-08-01

    A major challenge in Digital Breast Tomosynthesis (DBT) is handling image noise since the 3D reconstructed images are obtained from low dose projections and limited angular range. The use of the iterative reconstruction algorithm Algebraic Reconstruction Technique (ART) in clinical context depends on two key factors: the number of iterations needed (time consuming) and the image noise after iterations. Both factors depend highly on a relaxation coefficient (λ), which may give rise to slow or noisy reconstructions, when a single λ value is considered for the entire iterative process. The aim of this work is to present a new implementation for the ART that takes into account a dynamic mode to calculate λ in DBT image reconstruction. A set of initial reconstructions of real phantom data was done using constant λ values. The results were used to choose, for each iteration, the suitable λ value, taking into account the image noise level and the convergence speed. A methodology to optimize λ automatically during the image reconstruction was proposed. Results showed we can dynamically choose λ values in such a way that the time needed to reconstruct the images can be significantly reduced (up to 70%) while achieving similar image quality. These results were confirmed with one clinical dataset. With simple methodology we were able to dynamically choose λ in DBT image reconstruction with ART, allowing a shorter image reconstruction time without increasing image noise. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia.

    Science.gov (United States)

    Sun, Jihang; Yu, Tong; Liu, Jinrong; Duan, Xiaomin; Hu, Di; Liu, Yong; Peng, Yun

    2017-03-16

    Model-based iterative reconstruction (MBIR) is a promising reconstruction method which could improve CT image quality with low radiation dose. The purpose of this study was to demonstrate the advantage of using MBIR for noise reduction and image quality improvement in low dose chest CT for children with necrotizing pneumonia, over the adaptive statistical iterative reconstruction (ASIR) and conventional filtered back-projection (FBP) technique. Twenty-six children with necrotizing pneumonia (aged 2 months to 11 years) who underwent standard of care low dose CT scans were included. Thinner-slice (0.625 mm) images were retrospectively reconstructed using MBIR, ASIR and conventional FBP techniques. Image noise and signal-to-noise ratio (SNR) for these thin-slice images were measured and statistically analyzed using ANOVA. Two radiologists independently analyzed the image quality for detecting necrotic lesions, and results were compared using a Friedman's test. Radiation dose for the overall patient population was 0.59 mSv. There was a significant improvement in the high-density and low-contrast resolution of the MBIR reconstruction resulting in more detection and better identification of necrotic lesions (38 lesions in 0.625 mm MBIR images vs. 29 lesions in 0.625 mm FBP images). The subjective display scores (mean ± standard deviation) for the detection of necrotic lesions were 5.0 ± 0.0, 2.8 ± 0.4 and 2.5 ± 0.5 with MBIR, ASIR and FBP reconstruction, respectively, and the respective objective image noise was 13.9 ± 4.0HU, 24.9 ± 6.6HU and 33.8 ± 8.7HU. The image noise decreased by 58.9 and 26.3% in MBIR images as compared to FBP and ASIR images. Additionally, the SNR of MBIR images was significantly higher than FBP images and ASIR images. The quality of chest CT images obtained by MBIR in children with necrotizing pneumonia was significantly improved by the MBIR technique as compared to the ASIR and FBP reconstruction, to

  17. Assessment of the impact of modeling axial compression on PET image reconstruction.

    Science.gov (United States)

    Belzunce, Martin A; Reader, Andrew J

    2017-10-01

    To comprehensively evaluate both the acceleration and image-quality impacts of axial compression and its degree of modeling in fully 3D PET image reconstruction. Despite being used since the very dawn of 3D PET reconstruction, there are still no extensive studies on the impact of axial compression and its degree of modeling during reconstruction on the end-point reconstructed image quality. In this work, an evaluation of the impact of axial compression on the image quality is performed by extensively simulating data with span values from 1 to 121. In addition, two methods for modeling the axial compression in the reconstruction were evaluated. The first method models the axial compression in the system matrix, while the second method uses an unmatched projector/backprojector, where the axial compression is modeled only in the forward projector. The different system matrices were analyzed by computing their singular values and the point response functions for small subregions of the FOV. The two methods were evaluated with simulated and real data for the Biograph mMR scanner. For the simulated data, the axial compression with span values lower than 7 did not show a decrease in the contrast of the reconstructed images. For span 11, the standard sinogram size of the mMR scanner, losses of contrast in the range of 5-10 percentage points were observed when measured for a hot lesion. For higher span values, the spatial resolution was degraded considerably. However, impressively, for all span values of 21 and lower, modeling the axial compression in the system matrix compensated for the spatial resolution degradation and obtained similar contrast values as the span 1 reconstructions. Such approaches have the same processing times as span 1 reconstructions, but they permit significant reduction in storage requirements for the fully 3D sinograms. For higher span values, the system has a large condition number and it is therefore difficult to recover accurately the higher

  18. Local Surface Reconstruction from MER images using Stereo Workstation

    Science.gov (United States)

    Shin, Dongjoe; Muller, Jan-Peter

    2010-05-01

    The authors present a semi-automatic workflow that reconstructs the 3D shape of the martian surface from local stereo images delivered by PnCam or NavCam on systems such as the NASA Mars Exploration Rover (MER) Mission and in the future the ESA-NASA ExoMars rover PanCam. The process is initiated with manually selected tiepoints on a stereo workstation which is then followed by a tiepoint refinement, stereo-matching using region growing and Levenberg-Marquardt Algorithm (LMA)-based bundle adjustment processing. The stereo workstation, which is being developed by UCL in collaboration with colleagues at the Jet Propulsion Laboratory (JPL) within the EU FP7 ProVisG project, includes a set of practical GUI-based tools that enable an operator to define a visually correct tiepoint via a stereo display. To achieve platform and graphic hardware independence, the stereo application has been implemented using JPL's JADIS graphic library which is written in JAVA and the remaining processing blocks used in the reconstruction workflow have also been developed as a JAVA package to increase the code re-usability, portability and compatibility. Although initial tiepoints from the stereo workstation are reasonably acceptable as true correspondences, it is often required to employ an optional validity check and/or quality enhancing process. To meet this requirement, the workflow has been designed to include a tiepoint refinement process based on the Adaptive Least Square Correlation (ALSC) matching algorithm so that the initial tiepoints can be further enhanced to sub-pixel precision or rejected if they fail to pass the ALSC matching threshold. Apart from the accuracy of reconstruction, it is obvious that the other criterion to assess the quality of reconstruction is the density (or completeness) of reconstruction, which is not attained in the refinement process. Thus, we re-implemented a stereo region growing process, which is a core matching algorithm within the UCL

  19. Analysis of discrete-to-discrete imaging models for iterative tomographic image reconstruction and compressive sensing

    CERN Document Server

    Jørgensen, Jakob H; Pan, Xiaochuan

    2011-01-01

    Discrete-to-discrete imaging models for computed tomography (CT) are becoming increasingly ubiquitous as the interest in iterative image reconstruction algorithms has heightened. Despite this trend, all the intuition for algorithm and system design derives from analysis of continuous-to-continuous models such as the X-ray and Radon transform. While the similarity between these models justifies some crossover, questions such as what are sufficient sampling conditions can be quite different for the two models. This sampling issue is addressed extensively in the first half of the article using singular value decomposition analysis for determining sufficient number of views and detector bins. The question of full sampling for CT is particularly relevant to current attempts to adapt compressive sensing (CS) motivated methods to application in CT image reconstruction. The second half goes in depth on this subject and discusses the link between object sparsity and sufficient sampling for accurate reconstruction. Par...

  20. [Image reconstruction of conductivity on magnetoacoustic tomography with magnetic induction].

    Science.gov (United States)

    Li, Jingyu; Yin, Tao; Liu, Zhipeng; Xu, Guohui

    2010-04-01

    The electric characteristics such as impedance and conductivity of the organization will change in the case where pathological changes occurred in the biological tissue. The change in electric characteristics usually took place before the change in the density of tissues, and also, the difference in electric characteristics such as conductivity between normal tissue and pathological tissue is obvious. The method of magneto-acoustic tomography with magnetic induction is based on the theory of magnetic eddy current induction, the principle of vibration generation and acoustic transmission to get the boundary of the pathological tissue. The pathological change could be inspected by electricity characteristic imaging which is invasive to the tissue. In this study, a two-layer concentric spherical model is established to simulate the malignant tumor tissue surrounded by normal tissue mutual relations of the magneto-sound coupling effect and the coupling equations in the magnetic field are used to get the algorithms for reconstructing the conductivity. Simulation study is conducted to test the proposed model and validate the performance of the reconstructed algorithms. The result indicates that the use of signal processing method in this paper can image the conductivity boundaries of the sample in the scanning cross section. The computer simulating results validate the feasibility of applying the method of magneto-acoustic tomography with magnetic induction for malignant tumor imaging.

  1. Filtered gradient reconstruction algorithm for compressive spectral imaging

    Science.gov (United States)

    Mejia, Yuri; Arguello, Henry

    2017-04-01

    Compressive sensing matrices are traditionally based on random Gaussian and Bernoulli entries. Nevertheless, they are subject to physical constraints, and their structure unusually follows a dense matrix distribution, such as the case of the matrix related to compressive spectral imaging (CSI). The CSI matrix represents the integration of coded and shifted versions of the spectral bands. A spectral image can be recovered from CSI measurements by using iterative algorithms for linear inverse problems that minimize an objective function including a quadratic error term combined with a sparsity regularization term. However, current algorithms are slow because they do not exploit the structure and sparse characteristics of the CSI matrices. A gradient-based CSI reconstruction algorithm, which introduces a filtering step in each iteration of a conventional CSI reconstruction algorithm that yields improved image quality, is proposed. Motivated by the structure of the CSI matrix, Φ, this algorithm modifies the iterative solution such that it is forced to converge to a filtered version of the residual ΦTy, where y is the compressive measurement vector. We show that the filtered-based algorithm converges to better quality performance results than the unfiltered version. Simulation results highlight the relative performance gain over the existing iterative algorithms.

  2. Application of the fractional Fourier transform to image reconstruction in MRI.

    Science.gov (United States)

    Parot, Vicente; Sing-Long, Carlos; Lizama, Carlos; Tejos, Cristian; Uribe, Sergio; Irarrazaval, Pablo

    2012-07-01

    The classic paradigm for MRI requires a homogeneous B(0) field in combination with linear encoding gradients. Distortions are produced when the B(0) is not homogeneous, and several postprocessing techniques have been developed to correct them. Field homogeneity is difficult to achieve, particularly for short-bore magnets and higher B(0) fields. Nonlinear magnetic components can also arise from concomitant fields, particularly in low-field imaging, or intentionally used for nonlinear encoding. In any of these situations, the second-order component is key, because it constitutes the first step to approximate higher-order fields. We propose to use the fractional Fourier transform for analyzing and reconstructing the object's magnetization under the presence of quadratic fields. The fractional fourier transform provides a precise theoretical framework for this. We show how it can be used for reconstruction and for gaining a better understanding of the quadratic field-induced distortions, including examples of reconstruction for simulated and in vivo data. The obtained images have improved quality compared with standard Fourier reconstructions. The fractional fourier transform opens a new paradigm for understanding the MR signal generated by an object under a quadratic main field or nonlinear encoding. Copyright © 2011 Wiley Periodicals, Inc.

  3. Reconstructing cosmological matter perturbations using standard candles and rulers

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Ujjaini [Los Alamos National Laboratory; Sahni, Varun [IUCAA, PUNE; Starobinsky, Alexei A [LANDAU INST, MOSCOW

    2008-01-01

    For a large class of dark energy (DE) models, for which the effective gravitational constant is a constant and there is no direct exchange of energy between DE and dark matter (DM), knowledge of the expansion history suffices to reconstruct the growth factor of linearized density perturbations in the non-relativistic matter component on scales much smaller than the Hubble distance. In this paper, we develop a non-parametric method for extracting information about the perturbative growth factor from data pertaining to the luminosity or angular size distances. A comparison of the reconstructed density contrast with observations of large-scale structure and gravitational lensing can help distinguish DE models such as the cosmological constant and quintessence from models based on modified gravity theories as well as models in which DE and DM are either unified or interact directly. We show that for current supernovae (SNe) data, the linear growth factor at z = 0.3 can be constrained to 5% and the linear growth rate to 6%. With future SNe data, such as expected from the Joint Dark Energy Mission, we may be able to constrain the growth factor to 2%-3% and the growth rate to 3%-4% at z = 0.3 with this unbiased, model-independent reconstruction method. For future baryon acoustic oscillation data which would deliver measurements of both the angular diameter distance and the Hubble parameter, it should be possible to constrain the growth factor at z = 2.5%-9%. These constraints grow tighter with the errors on the data sets. With a large quantity of data expected in the next few years, this method can emerge as a competitive tool for distinguishing between different models of dark energy.

  4. Dental non-linear image registration and collection method with 3D reconstruction and change detection

    Science.gov (United States)

    Rahmes, Mark; Fagan, Dean; Lemieux, George

    2017-03-01

    The capability of a software algorithm to automatically align same-patient dental bitewing and panoramic x-rays over time is complicated by differences in collection perspectives. We successfully used image correlation with an affine transform for each pixel to discover common image borders, followed by a non-linear homography perspective adjustment to closely align the images. However, significant improvements in image registration could be realized if images were collected from the same perspective, thus facilitating change analysis. The perspective differences due to current dental image collection devices are so significant that straightforward change analysis is not possible. To address this, a new custom dental tray could be used to provide the standard reference needed for consistent positioning of a patient's mouth. Similar to sports mouth guards, the dental tray could be fabricated in standard sizes from plastic and use integrated electronics that have been miniaturized. In addition, the x-ray source needs to be consistently positioned in order to collect images with similar angles and scales. Solving this pose correction is similar to solving for collection angle in aerial imagery for change detection. A standard collection system would provide a method for consistent source positioning using real-time sensor position feedback from a digital x-ray image reference. Automated, robotic sensor positioning could replace manual adjustments. Given an image set from a standard collection, a disparity map between images can be created using parallax from overlapping viewpoints to enable change detection. This perspective data can be rectified and used to create a three-dimensional dental model reconstruction.

  5. Towards establishing compact imaging spectrometer standards

    Science.gov (United States)

    Slonecker, E. Terrence; Allen, David W.; Resmini, Ronald G.

    2016-01-01

    Remote sensing science is currently undergoing a tremendous expansion in the area of hyperspectral imaging (HSI) technology. Spurred largely by the explosive growth of Unmanned Aerial Vehicles (UAV), sometimes called Unmanned Aircraft Systems (UAS), or drones, HSI capabilities that once required access to one of only a handful of very specialized and expensive sensor systems are now miniaturized and widely available commercially. Small compact imaging spectrometers (CIS) now on the market offer a number of hyperspectral imaging capabilities in terms of spectral range and sampling. The potential uses of HSI/CIS on UAVs/UASs seem limitless. However, the rapid expansion of unmanned aircraft and small hyperspectral sensor capabilities has created a number of questions related to technological, legal, and operational capabilities. Lightweight sensor systems suitable for UAV platforms are being advertised in the trade literature at an ever-expanding rate with no standardization of system performance specifications or terms of reference. To address this issue, both the U.S. Geological Survey and the National Institute of Standards and Technology are eveloping draft standards to meet these issues. This paper presents the outline of a combined USGS/NIST cooperative strategy to develop and test a characterization methodology to meet the needs of a new and expanding UAV/CIS/HSI user community.

  6. Analysis of Interpolation Methods in the Image Reconstruction Tasks

    Directory of Open Access Journals (Sweden)

    V. T. Nguyen

    2017-01-01

    Full Text Available The article studies the interpolation methods used for image reconstruction. These methods were also implemented and tested with several images to estimate their effectiveness.The considered interpolation methods are a nearest-neighbor method, linear method, a cubic B-spline method, a cubic convolution method, and a Lanczos method. For each method were presented an interpolation kernel (interpolation function and a frequency response (Fourier transform.As a result of the experiment, the following conclusions were drawn:-         the nearest neighbor algorithm is very simple and often used. With using this method, the reconstructed images contain artifacts (blurring and haloing;-         the linear method is quickly and easily performed. It also reduces some visual distortion caused by changing image size. Despite the advantages using this method causes a large amount of interpolation artifacts, such as blurring and haloing;-         cubic B-spline method provides smoothness of reconstructed images and eliminates apparent ramp phenomenon. But in the interpolation process a low-pass filter is used, and a high frequency component is suppressed. This will lead to fuzzy edge and false artificial traces;-         cubic convolution method offers less distortion interpolation. But its algorithm is more complicated and more execution time is required as compared to the nearest-neighbor method and the linear method;-         using the Lanczos method allows us to achieve a high-definition image. In spite of the great advantage the method requires more execution time as compared to the other methods of interpolation.The result obtained not only shows a comparison of the considered interpolation methods for various aspects, but also enables users to select an appropriate interpolation method for their applications.It is advisable to study further the existing methods and develop new ones using a number of methods

  7. Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

    Science.gov (United States)

    Ren, Zhong; Liu, Guodong; Huang, Zhen

    2012-11-01

    The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

  8. Detail displaying difference of the digital holographic reconstructed image between the convolution algorithm and Fresnel algorithm.

    Science.gov (United States)

    Zhong, Liyun; Li, Hongyan; Tao, Tao; Zhang, Zhun; Lu, Xiaoxu

    2011-11-07

    To reach the limiting resolution of a digital holographic system and improve the displaying quality of the reconstructed image, the subdivision convolution algorithm and the subdivision Fresnel algorithm are presented, respectively. The obtained results show that the lateral size of the reconstructed image obtained by two kinds of subdivision algorithms is the same in the central region of the reconstructed image-plane; moreover, the size of the central region is in proportional to the recording distance. Importantly, in the central region of the reconstructed image-plane, the reconstruction can be performed by the subdivision Fresnel algorithm instead of the subdivision convolution algorithm effectively, and, based on these subdivision approaches, both the displaying quality and the resolution of the reconstructed image can be improved significantly. Furthermore, in the reconstruction of the digital hologram with the large numerical aperture, the computer's memory consumed and the calculating time resulting from the subdivision Fresnel algorithm is significantly less than those from the subdivision convolution algorithm.

  9. Reconstruction algorithm medical imaging DRR; Algoritmo de construccion de imagenes medicas DRR

    Energy Technology Data Exchange (ETDEWEB)

    Estrada Espinosa, J. C.

    2013-07-01

    The method of reconstruction for digital radiographic Imaging (DRR), is based on two orthogonal images, on the dorsal and lateral decubitus position of the simulation. DRR images are reconstructed with an algorithm that simulates running a conventional X-ray, a single rendition team, beam emitted is not divergent, in this case, the rays are considered to be parallel in the image reconstruction DRR, for this purpose, it is necessary to use all the values of the units (HU) hounsfield of each voxel in all axial cuts that form the study TC, finally obtaining the reconstructed image DRR performing a transformation from 3D to 2D. (Author)

  10. PET image reconstruction using multi-parametric anato-functional priors.

    Science.gov (United States)

    Mehranian, Abolfazl; Belzunce, Martin A; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J

    2017-07-06

    In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [ 18 F]florbetaben and [ 18 F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical

  11. PET image reconstruction using multi-parametric anato-functional priors

    Science.gov (United States)

    Mehranian, Abolfazl; Belzunce, Martin A.; Niccolini, Flavia; Politis, Marios; Prieto, Claudia; Turkheimer, Federico; Hammers, Alexander; Reader, Andrew J.

    2017-08-01

    In this study, we investigate the application of multi-parametric anato-functional (MR-PET) priors for the maximum a posteriori (MAP) reconstruction of brain PET data in order to address the limitations of the conventional anatomical priors in the presence of PET-MR mismatches. In addition to partial volume correction benefits, the suitability of these priors for reconstruction of low-count PET data is also introduced and demonstrated, comparing to standard maximum-likelihood (ML) reconstruction of high-count data. The conventional local Tikhonov and total variation (TV) priors and current state-of-the-art anatomical priors including the Kaipio, non-local Tikhonov prior with Bowsher and Gaussian similarity kernels are investigated and presented in a unified framework. The Gaussian kernels are calculated using both voxel- and patch-based feature vectors. To cope with PET and MR mismatches, the Bowsher and Gaussian priors are extended to multi-parametric priors. In addition, we propose a modified joint Burg entropy prior that by definition exploits all parametric information in the MAP reconstruction of PET data. The performance of the priors was extensively evaluated using 3D simulations and two clinical brain datasets of [18F]florbetaben and [18F]FDG radiotracers. For simulations, several anato-functional mismatches were intentionally introduced between the PET and MR images, and furthermore, for the FDG clinical dataset, two PET-unique active tumours were embedded in the PET data. Our simulation results showed that the joint Burg entropy prior far outperformed the conventional anatomical priors in terms of preserving PET unique lesions, while still reconstructing functional boundaries with corresponding MR boundaries. In addition, the multi-parametric extension of the Gaussian and Bowsher priors led to enhanced preservation of edge and PET unique features and also an improved bias-variance performance. In agreement with the simulation results, the clinical results

  12. Clinical evaluation of a novel CT image reconstruction algorithm for direct dose calculations

    Directory of Open Access Journals (Sweden)

    Brent van der Heyden

    2017-03-01

    Full Text Available Background and purpose: Computed tomography (CT imaging is frequently used in radiation oncology to calculate radiation dose distributions. In order to calculate doses, the CT numbers must be converted into densities by an energy dependent conversion curve. A recently developed algorithm directly reconstructs CT projection data into relative electron densities which eliminates the use of separate conversion curves for different X-ray tube potentials. Our work evaluates this algorithm for various cancer sites and shows its applicability in a clinical workflow. Materials and methods: The Gammex phantom with tissue mimicking inserts was scanned to characterize the CT number to density conversion curves. In total, 33 patients with various cancer sites were scanned using multiple tube potentials. All CT acquisitions were reconstructed with the standard filtered back-projection (FBP and the new developed DirectDensity™ (DD algorithm. The mean tumor doses and the volume percentage that receives more than 95% of the prescribed dose were calculated for the planning target volume. Relevant parameters for the organs at risk for each tumor site were also calculated. Results: The relative mean dose differences between the standard 120 kVp FBP CT scan workflow and the DD CT scans (80, 100, 120 and 140 kVp were in general less than 1% for the planned target volume and organs at risk. Conclusion: The energy independent DD algorithm allows for accurate dose calculations over a variety of body sites. This novel algorithm eliminates the tube potential specific calibration procedure and thereby simplifies the clinical radiotherapy workflow. Keywords: CT imaging, Image reconstruction, Dose calculations, Electron density reconstruction

  13. Combined use of iterative reconstruction and monochromatic imaging in spinal fusion CT images.

    Science.gov (United States)

    Wang, Fengdan; Zhang, Yan; Xue, Huadan; Han, Wei; Yang, Xianda; Jin, Zhengyu; Zwar, Richard

    2017-01-01

    Spinal fusion surgery is an important procedure for treating spinal diseases and computed tomography (CT) is a critical tool for postoperative evaluation. However, CT image quality is considerably impaired by metal artifacts and image noise. To explore whether metal artifacts and image noise can be reduced by combining two technologies, adaptive statistical iterative reconstruction (ASIR) and monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. A total of 51 patients with 318 spinal pedicle screws were prospectively scanned by dual-energy CT using fast kV-switching GSI between 80 and 140 kVp. Monochromatic GSI images at 110 keV were reconstructed either without or with various levels of ASIR (30%, 50%, 70%, and 100%). The quality of five sets of images was objectively and subjectively assessed. With objective image quality assessment, metal artifacts decreased when increasing levels of ASIR were applied (P ASIR to GSI also decreased image noise (P ASIR levels (P ASIR and GSI decreased image noise and improved image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels ≥70%. © The Foundation Acta Radiologica 2016.

  14. Iterative PET Image Reconstruction Using Translation Invariant Wavelet Transform.

    Science.gov (United States)

    Zhou, Jian; Senhadji, Lotfi; Coatrieux, Jean-Louis; Luo, Limin

    2009-02-01

    The present work describes a Bayesian maximum a posteriori (MAP) method using a statistical multiscale wavelet prior model. Rather than using the orthogonal discrete wavelet transform (DWT), this prior is built on the translation invariant wavelet transform (TIWT). The statistical modeling of wavelet coefficients relies on the generalized Gaussian distribution. Image reconstruction is performed in spatial domain with a fast block sequential iteration algorithm. We study theoretically the TIWT MAP method by analyzing the Hessian of the prior function to provide some insights on noise and resolution properties of image reconstruction. We adapt the key concept of local shift invariance and explore how the TIWT MAP algorithm behaves with different scales. It is also shown that larger support wavelet filters do not offer better performance in contrast recovery studies. These theoretical developments are confirmed through simulation studies. The results show that the proposed method is more attractive than other MAP methods using either the conventional Gibbs prior or the DWT-based wavelet prior.

  15. 3D Image Reconstruction from X-Ray Measurements with Overlap

    CERN Document Server

    Klodt, Maria

    2016-01-01

    3D image reconstruction from a set of X-ray projections is an important image reconstruction problem, with applications in medical imaging, industrial inspection and airport security. The innovation of X-ray emitter arrays allows for a novel type of X-ray scanners with multiple simultaneously emitting sources. However, two or more sources emitting at the same time can yield measurements from overlapping rays, imposing a new type of image reconstruction problem based on nonlinear constraints. Using traditional linear reconstruction methods, respective scanner geometries have to be implemented such that no rays overlap, which severely restricts the scanner design. We derive a new type of 3D image reconstruction model with nonlinear constraints, based on measurements with overlapping X-rays. Further, we show that the arising optimization problem is partially convex, and present an algorithm to solve it. Experiments show highly improved image reconstruction results from both simulated and real-world measurements.

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

    Science.gov (United States)

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

    2017-09-01

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

  17. A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction.

    Science.gov (United States)

    Konkle, Justin J; Goodwill, Patrick W; Hensley, Daniel W; Orendorff, Ryan D; Lustig, Michael; Conolly, Steven M

    2015-01-01

    Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

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

    Science.gov (United States)

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

    2016-12-01

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

  19. Computed tomography image source identification by discriminating CT-scanner image reconstruction process.

    Science.gov (United States)

    Duan, Y; Coatrieux, G; Shu, H Z

    2015-08-01

    In this paper, we focus on the identification of the Computed Tomography (CT) scanner that has produced a CT image. To do so, we propose to discriminate CT-Scanner systems based on their reconstruction process, the footprint or the signature of which can be established based on the way they modify the intrinsic sensor noise of X-ray detectors. After having analyzed how the sensor noise is modified in the reconstruction process, we define a set of image features so as to serve as CT acquisition system footprint. These features are used to train a SVM based classifier. Experiments conducted on images issued from 15 different CT-Scanner models of 4 distinct manufacturers show it is possible to identify the origin of one CT image with high accuracy.

  20. Images from the Mind: BCI image reconstruction based on Rapid Serial Visual Presentations of polygon primitives

    Directory of Open Access Journals (Sweden)

    Luís F Seoane

    2015-04-01

    Full Text Available We provide a proof of concept for an EEG-based reconstruction of a visual image which is on a user's mind. Our approach is based on the Rapid Serial Visual Presentation (RSVP of polygon primitives and Brain-Computer Interface (BCI technology. In an experimental setup, subjects were presented bursts of polygons: some of them contributed to building a target image (because they matched the shape and/or color of the target while some of them did not. The presentation of the contributing polygons triggered attention-related EEG patterns. These Event Related Potentials (ERPs could be determined using BCI classification and could be matched to the stimuli that elicited them. These stimuli (i.e. the ERP-correlated polygons were accumulated in the display until a satisfactory reconstruction of the target image was reached. As more polygons were accumulated, finer visual details were attained resulting in more challenging classification tasks. In our experiments, we observe an average classification accuracy of around 75%. An in-depth investigation suggests that many of the misclassifications were not misinterpretations of the BCI concerning the users' intent, but rather caused by ambiguous polygons that could contribute to reconstruct several different images. When we put our BCI-image reconstruction in perspective with other RSVP BCI paradigms, there is large room for improvement both in speed and accuracy. These results invite us to be optimistic. They open a plethora of possibilities to explore non-invasive BCIs for image reconstruction both in healthy and impaired subjects and, accordingly, suggest interesting recreational and clinical applications.

  1. 3D Sorghum Reconstructions from Depth Images Identify QTL Regulating Shoot Architecture1[OPEN

    Science.gov (United States)

    2016-01-01

    Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height, leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits. PMID:27528244

  2. Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis.

    Science.gov (United States)

    Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth; Vardhanabhuti, Varut; Stuckey, Colin; Gutteridge, Catherine; Hyde, Christopher; Roobottom, Carl

    2017-03-13

    To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. • MBIR allows reduced CT dose with similar diagnostic accuracy • MBIR outperforms ASIR when used for the reconstruction of reduced-dose scans • MBIR can be used to accurately assess stones 3 mm and above.

  3. Geometric correction method for 3D in-line X-ray phase contrast image reconstruction.

    Science.gov (United States)

    Wu, Geming; Wu, Mingshu; Dong, Linan; Luo, Shuqian

    2014-07-29

    Mechanical system with imperfect or misalignment of X-ray phase contrast imaging (XPCI) components causes projection data misplaced, and thus result in the reconstructed slice images of computed tomography (CT) blurred or with edge artifacts. So the features of biological microstructures to be investigated are destroyed unexpectedly, and the spatial resolution of XPCI image is decreased. It makes data correction an essential pre-processing step for CT reconstruction of XPCI. To remove unexpected blurs and edge artifacts, a mathematics model for in-line XPCI is built by considering primary geometric parameters which include a rotation angle and a shift variant in this paper. Optimal geometric parameters are achieved by finding the solution of a maximization problem. And an iterative approach is employed to solve the maximization problem by using a two-step scheme which includes performing a composite geometric transformation and then following a linear regression process. After applying the geometric transformation with optimal parameters to projection data, standard filtered back-projection algorithm is used to reconstruct CT slice images. Numerical experiments were carried out on both synthetic and real in-line XPCI datasets. Experimental results demonstrate that the proposed method improves CT image quality by removing both blurring and edge artifacts at the same time compared to existing correction methods. The method proposed in this paper provides an effective projection data correction scheme and significantly improves the image quality by removing both blurring and edge artifacts at the same time for in-line XPCI. It is easy to implement and can also be extended to other XPCI techniques.

  4. SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space

    Science.gov (United States)

    Lustig, Michael; Pauly, John M.

    2010-01-01

    A new approach to autocalibrating, coil-by-coil parallel imaging reconstruction is presented. It is a generalized reconstruction framework based on self consistency. The reconstruction problem is formulated as an optimization that yields the most consistent solution with the calibration and acquisition data. The approach is general and can accurately reconstruct images from arbitrary k-space sampling patterns. The formulation can flexibly incorporate additional image priors such as off-resonance correction and regularization terms that appear in compressed sensing. Several iterative strategies to solve the posed reconstruction problem in both image and k-space domain are presented. These are based on a projection over convex sets (POCS) and a conjugate gradient (CG) algorithms. Phantom and in-vivo studies demonstrate efficient reconstructions from undersampled Cartesian and spiral trajectories. Reconstructions that include off-resonance correction and nonlinear ℓ1-wavelet regularization are also demonstrated. PMID:20665790

  5. AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

    OpenAIRE

    F. Alidoost; H. Arefi

    2015-01-01

    Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud gen...

  6. Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation.

    Science.gov (United States)

    Karakatsanis, Nicolas A; Tsoumpas, Charalampos; Zaidi, Habib

    2017-09-01

    Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and

  7. A data-parallelism approach for PSO-ANN based medical image reconstruction on a multi-core system

    Directory of Open Access Journals (Sweden)

    Subramanian Kartheeswaran

    Full Text Available This paper presents the sequential and parallel data decomposition strategies implemented on a Particle Swarm Optimization (PSO algorithm based Artificial Neural Network (PSO-ANN weights optimization for image reconstruction. The application system is developed for the reconstruction of two-dimensional spatial standard Computed Tomography (CT phantom images. It is running on a multi-core computer by varying the number of cores. The feed forward ANN initializes the weight between the ‘ideal’ images that are reconstructed using filtered back projection (FBP technique and the corresponding projection data of CT phantom. In an earlier work, ANN training time is too long. Hence, we propose that the ANN exemplar datasets are decomposed into subsets. Using these subsets, artificial sub neural nets (subnets are initialized and each subnet initial weights are optimized using PSO. Consequently, it was observed that the sequential approach of the proposed method consumes more training time. Hence the parallel strategy is attempted to reduce the computational training time. The parallel approach is further explored for image reconstruction from ‘noisy’ and ‘limited-angle’ datasets also. Keywords: Image reconstruction, Filtered back projection, Artificial neural networks, Particle swarm optimization, Multi-core processors

  8. Patient dose and image quality in low-dose abdominal CT: a comparison between iterative reconstruction and filtered back projection.

    Science.gov (United States)

    Kataria, Bharti; Smedby, Orjan

    2013-06-01

    In computed tomography (CT), there is increasing concern for potential CT radiation hazards. Several raw-data-based iterative reconstruction techniques attempt to facilitate low-dose imaging without compromising image quality, which raises the question whether these techniques may allow further dose reduction. To compare image quality of iterative reconstruction and filtered back projection in low-dose abdominal CT and study the potential for further dose reduction. Forty-five patients underwent CT of the abdomen twice: with standard low-dose technique and with 30% reduced dose, using both iterative reconstruction and filtered back projection. Four radiologists made pair-wise image quality assessment using five visual criteria. Visual grading regression (VGR) and weighted kappa (κ w) were used to analyze the data. There were significant effects of log(mAs) (P reconstruction algorithm (P iterative reconstruction algorithm improved image quality in abdominal CT, but the estimated dose reduction was rather small. The full potential of the algorithm remains unclear. © 2013 The Foundation Acta Radiologica.

  9. Characterization of a computed tomography iterative reconstruction algorithm by image quality evaluations with an anthropomorphic phantom

    Energy Technology Data Exchange (ETDEWEB)

    Rampado, O., E-mail: orampado@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Bossi, L., E-mail: laura-bossi@hotmail.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Garabello, D., E-mail: dgarabello@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Davini, O., E-mail: odavini@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Ropolo, R., E-mail: rropolo@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy)

    2012-11-15

    Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10-22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from -2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.

  10. Resolution enhanced 3D image reconstruction by use of ray tracing and auto-focus in computational integral imaging

    Science.gov (United States)

    Yuan, Ying; Yu, Shuo; Wang, Xiaorui; Zhang, Jianlei

    2017-12-01

    We propose a three-dimensional (3D) image reconstruction algorithm that can computationally reconstruct the light field image with enhanced resolution. This method is based on ray tracing and can reconstruct the elemental images from arbitrary viewpoints. In the conventional integral imaging reconstruction process, a plane needs to be selected to make the reconstructed image in focus, so prior knowledge is required. Auto-focus (AF) of the digital camera is applied in the integral imaging reconstruction process and the optimal reconstruction plane can be selected automatically without any prior knowledge. Thus, the integral imaging system can record the light field of 3D scene without focusing on them and image focusing will be completed in the computational post-processing process. To our knowledge, this is the first time to apply auto-focus method to 3D integral imaging reconstruction. Furthermore, the depth-of-field can be controlled by adjusting the transmission angle of light ray from the elemental images. Experimental results are presented to demonstrate the feasibility and effectiveness of the proposed method.

  11. Muscle Activity Map Reconstruction from High Density Surface EMG Signals With Missing Channels Using Image Inpainting and Surface Reconstruction Methods.

    Science.gov (United States)

    Ghaderi, Parviz; Marateb, Hamid R

    2017-07-01

    The aim of this study was to reconstruct low-quality High-density surface EMG (HDsEMG) signals, recorded with 2-D electrode arrays, using image inpainting and surface reconstruction methods. It is common that some fraction of the electrodes may provide low-quality signals. We used variety of image inpainting methods, based on partial differential equations (PDEs), and surface reconstruction methods to reconstruct the time-averaged or instantaneous muscle activity maps of those outlier channels. Two novel reconstruction algorithms were also proposed. HDsEMG signals were recorded from the biceps femoris and brachial biceps muscles during low-to-moderate-level isometric contractions, and some of the channels (5-25%) were randomly marked as outliers. The root-mean-square error (RMSE) between the original and reconstructed maps was then calculated. Overall, the proposed Poisson and wave PDE outperformed the other methods (average RMSE 8.7 μVrms ± 6.1 μVrms and 7.5 μVrms ± 5.9 μVrms) for the time-averaged single-differential and monopolar map reconstruction, respectively. Biharmonic Spline, the discrete cosine transform, and the Poisson PDE outperformed the other methods for the instantaneous map reconstruction. The running time of the proposed Poisson and wave PDE methods, implemented using a Vectorization package, was 4.6 ± 5.7 ms and 0.6 ± 0.5 ms, respectively, for each signal epoch or time sample in each channel. The proposed reconstruction algorithms could be promising new tools for reconstructing muscle activity maps in real-time applications. Proper reconstruction methods could recover the information of low-quality recorded channels in HDsEMG signals.

  12. Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer.

    Science.gov (United States)

    Knoll, Florian; Holler, Martin; Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

    2017-01-01

    While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy.

  13. 3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging.

    Science.gov (United States)

    Mertzanidou, Thomy; Hipwell, John H; Reis, Sara; Hawkes, David J; Ehteshami Bejnordi, Babak; Dalmis, Mehmet; Vreemann, Suzan; Platel, Bram; van der Laak, Jeroen; Karssemeijer, Nico; Hermsen, Meyke; Bult, Peter; Mann, Ritse

    2017-03-01

    In breast imaging, radiological in vivo images, such as x-ray mammography and magnetic resonance imaging (MRI), are used for tumor detection, diagnosis, and size determination. After excision, the specimen is typically sliced into slabs and a small subset is sampled. Histopathological imaging of the stained samples is used as the gold standard for characterization of the tumor microenvironment. A 3D volume reconstruction of the whole specimen from the 2D slabs could facilitate bridging the gap between histology and in vivo radiological imaging. This task is challenging, however, due to the large deformation that the breast tissue undergoes after surgery and the significant undersampling of the specimen obtained in histology. In this work, we present a method to reconstruct a coherent 3D volume from 2D digital radiographs of the specimen slabs. To reconstruct a 3D breast specimen volume, we propose the use of multiple target neighboring slices, when deforming each 2D slab radiograph in the volume, rather than performing pairwise registrations. The algorithm combines neighborhood slice information with free-form deformations, which enables a flexible, nonlinear deformation to be computed subject to the constraint that a coherent 3D volume is obtained. The neighborhood information provides adequate constraints, without the need for any additional regularization terms. The volume reconstruction algorithm is validated on clinical mastectomy samples using a quantitative assessment of the volume reconstruction smoothness and a comparison with a whole specimen 3D image acquired for validation before slicing. Additionally, a target registration error of 5 mm (comparable to the specimen slab thickness of 4 mm) was obtained for five cases. The error was computed using manual annotations from four observers as gold standard, with interobserver variability of 3.4 mm. Finally, we illustrate how the reconstructed volumes can be used to map histology images to a 3D specimen

  14. Impact of model-based iterative reconstruction on image quality of contrast-enhanced neck CT.

    Science.gov (United States)

    Gaddikeri, S; Andre, J B; Benjert, J; Hippe, D S; Anzai, Y

    2015-02-01

    Improved image quality is clinically desired for contrast-enhanced CT of the neck. We compared 30% adaptive statistical iterative reconstruction and model-based iterative reconstruction algorithms for the assessment of image quality of contrast-enhanced CT of the neck. Neck contrast-enhanced CT data from 64 consecutive patients were reconstructed retrospectively by using 30% adaptive statistical iterative reconstruction and model-based iterative reconstruction. Objective image quality was assessed by comparing SNR, contrast-to-noise ratio, and background noise at levels 1 (mandible) and 2 (superior mediastinum). Two independent blinded readers subjectively graded the image quality on a scale of 1-5, (grade 5 = excellent image quality without artifacts and grade 1 = nondiagnostic image quality with significant artifacts). The percentage of agreement and disagreement between the 2 readers was assessed. Compared with 30% adaptive statistical iterative reconstruction, model-based iterative reconstruction significantly improved the SNR and contrast-to-noise ratio at levels 1 and 2. Model-based iterative reconstruction also decreased background noise at level 1 (P = .016), though there was no difference at level 2 (P = .61). Model-based iterative reconstruction was scored higher than 30% adaptive statistical iterative reconstruction by both reviewers at the nasopharynx (P iterative reconstruction. Model-based iterative reconstruction offers improved subjective and objective image quality as evidenced by a higher SNR and contrast-to-noise ratio and lower background noise within the same dataset for contrast-enhanced neck CT. Model-based iterative reconstruction has the potential to reduce the radiation dose while maintaining the image quality, with a minor downside being prominent artifacts related to thyroid shield use on model-based iterative reconstruction. © 2015 by American Journal of Neuroradiology.

  15. Guidelines for imaging retinoblastoma: imaging principles and MRI standardization

    Energy Technology Data Exchange (ETDEWEB)

    Graaf, Pim de; Rodjan, Firazia; Castelijns, Jonas A. [VU University Medical Center, Department of Radiology, Amsterdam (Netherlands); Goericke, Sophia [University Hospital, Department of Diagnostic and Interventional Radiology and Neuroradiology, Essen (Germany); Galluzzi, Paolo [Azienda Ospedaliera e Universitaria Senese, Policlinico ' ' Le Scotte' ' , Unit of Diagnostic and Therapeutic Neuroradiology, Siena (Italy); Maeder, Philippe [CHUV, Service de Radiodiagnostic et Radiologie Interventionelle, Lausanne (Switzerland); Brisse, Herve J. [Institut Curie, Departement d' Imagerie, Paris (France)

    2012-01-15

    Retinoblastoma is the most common intraocular tumor in children. The diagnosis is usually established by the ophthalmologist on the basis of fundoscopy and US. Together with US, high-resolution MRI has emerged as an important imaging modality for pretreatment assessment, i.e. for diagnostic confirmation, detection of local tumor extent, detection of associated developmental malformation of the brain and detection of associated intracranial primitive neuroectodermal tumor (trilateral retinoblastoma). Minimum requirements for pretreatment diagnostic evaluation of retinoblastoma or mimicking lesions are presented, based on consensus among members of the European Retinoblastoma Imaging Collaboration (ERIC). The most appropriate techniques for imaging in a child with leukocoria are reviewed. CT is no longer recommended. Implementation of a standardized MRI protocol for retinoblastoma in clinical practice may benefit children worldwide, especially those with hereditary retinoblastoma, since a decreased use of CT reduces the exposure to ionizing radiation. (orig.)

  16. An adaptive total variation image reconstruction method for speckles through disordered media

    Science.gov (United States)

    Gong, Changmei; Shao, Xiaopeng; Wu, Tengfei

    2013-09-01

    Multiple scattering of light in highly disordered medium can break the diffraction limit of conventional optical system combined with image reconstruction method. Once the transmission matrix of the imaging system is obtained, the target image can be reconstructed from its speckle pattern by image reconstruction algorithm. Nevertheless, the restored image attained by common image reconstruction algorithms such as Tikhonov regularization has a relatively low signal-tonoise ratio (SNR) due to the experimental noise and reconstruction noise, greatly reducing the quality of the result image. In this paper, the speckle pattern of the test image is simulated by the combination of light propagation theories and statistical optics theories. Subsequently, an adaptive total variation (ATV) algorithm—the TV minimization by augmented Lagrangian and alternating direction algorithms (TVAL3), which is based on augmented Lagrangian and alternating direction algorithm, is utilized to reconstruct the target image. Numerical simulation experimental results show that, the TVAL3 algorithm can effectively suppress the noise of the restored image and preserve more image details, thus greatly boosts the SNR of the restored image. It also indicates that, compared with the image directly formed by `clean' system, the reconstructed results can overcoming the diffraction limit of the `clean' system, therefore being conductive to the observation of cells and protein molecules in biological tissues and other structures in micro/nano scale.

  17. 2-D Fused Image Reconstruction approach for Microwave Tomography: a theoretical assessment using FDTD Model.

    Science.gov (United States)

    Bindu, G; Semenov, S

    2013-01-01

    This paper describes an efficient two-dimensional fused image reconstruction approach for Microwave Tomography (MWT). Finite Difference Time Domain (FDTD) models were created for a viable MWT experimental system having the transceivers modelled using thin wire approximation with resistive voltage sources. Born Iterative and Distorted Born Iterative methods have been employed for image reconstruction with the extremity imaging being done using a differential imaging technique. The forward solver in the imaging algorithm employs the FDTD method of solving the time domain Maxwell's equations with the regularisation parameter computed using a stochastic approach. The algorithm is tested with 10% noise inclusion and successful image reconstruction has been shown implying its robustness.

  18. Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

    Directory of Open Access Journals (Sweden)

    Mingjian Sun

    2015-01-01

    Full Text Available Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO optimized support vector machine (SVM interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

  19. Comparison of pure and hybrid iterative reconstruction techniques with conventional filtered back projection: Image quality assessment in the cervicothoracic region

    Energy Technology Data Exchange (ETDEWEB)

    Katsura, Masaki, E-mail: mkatsura-tky@umin.ac.jp [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan); Sato, Jiro; Akahane, Masaaki; Matsuda, Izuru; Ishida, Masanori; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan)

    2013-02-15

    Objectives: To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Methods: Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Student's t-test. Results: MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P < 0.01) and FBP images (26.52 ± 5.8, P < 0.01). Significant improvements in streak artifacts of the cervicothoracic region were observed with the use of MBIR (P < 0.001 each for MBIR vs. the other two image data sets for both readers), while no significant difference was observed between ASIR and FBP (P > 0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. Conclusions: MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic.

  20. Fat-constrained 18F-FDG PET reconstruction using Dixon MR imaging and the origin ensemble algorithm

    Science.gov (United States)

    Wülker, Christian; Heinzer, Susanne; Börnert, Peter; Renisch, Steffen; Prevrhal, Sven

    2015-03-01

    Combined PET/MR imaging allows to incorporate the high-resolution anatomical information delivered by MRI into the PET reconstruction algorithm for improvement of PET accuracy beyond standard corrections. We used the working hypothesis that glucose uptake in adipose tissue is low. Thus, our aim was to shift 18F-FDG PET signal into image regions with a low fat content. Dixon MR imaging can be used to generate fat-only images via the water/fat chemical shift difference. On the other hand, the Origin Ensemble (OE) algorithm, a novel Markov chain Monte Carlo method, allows to reconstruct PET data without the use of forward- and back projection operations. By adequate modifications to the Markov chain transition kernel, it is possible to include anatomical a priori knowledge into the OE algorithm. In this work, we used the OE algorithm to reconstruct PET data of a modified IEC/NEMA Body Phantom simulating body water/fat composition. Reconstruction was performed 1) natively, 2) informed with the Dixon MR fat image to down-weight 18F-FDG signal in fatty tissue compartments in favor of adjacent regions, and 3) informed with the fat image to up-weight 18F-FDG signal in fatty tissue compartments, for control purposes. Image intensity profiles confirmed the visibly improved contrast and reduced partial volume effect at water/fat interfaces. We observed a 17+/-2% increased SNR of hot lesions surrounded by fat, while image quality was almost completely retained in fat-free image regions. An additional in vivo experiment proved the applicability of the presented technique in practice, and again verified the beneficial impact of fat-constrained OE reconstruction on PET image quality.

  1. An implementation of the NiftyRec medical imaging library for PIXE-tomography reconstruction

    Science.gov (United States)

    Michelet, C.; Barberet, P.; Desbarats, P.; Giovannelli, J.-F.; Schou, C.; Chebil, I.; Delville, M.-H.; Gordillo, N.; Beasley, D. G.; Devès, G.; Moretto, P.; Seznec, H.

    2017-08-01

    A new development of the TomoRebuild software package is presented, including ;thick sample; correction for non linear X-ray production (NLXP) and X-ray absorption (XA). As in the previous versions, C++ programming with standard libraries was used for easier portability. Data reduction requires different steps which may be run either from a command line instruction or via a user friendly interface, developed as a portable Java plugin in ImageJ. All experimental and reconstruction parameters can be easily modified, either directly in the ASCII parameter files or via the ImageJ interface. A detailed user guide in English is provided. Sinograms and final reconstructed images are generated in usual binary formats that can be read by most public domain graphic softwares. New MLEM and OSEM methods are proposed, using optimized methods from the NiftyRec medical imaging library. An overview of the different medical imaging methods that have been used for ion beam microtomography applications is presented. In TomoRebuild, PIXET data reduction is performed for each chemical element independently and separately from STIMT, except for two steps where the fusion of STIMT and PIXET data is required: the calculation of the correction matrix and the normalization of PIXET data to obtain mass fraction distributions. Correction matrices for NLXP and XA are calculated using procedures extracted from the DISRA code, taking into account a large X-ray detection solid angle. For this, the 3D STIMT mass density distribution is used, considering a homogeneous global composition. A first example of PIXET experiment using two detectors is presented. Reconstruction results are compared and found in good agreement between different codes: FBP, NiftyRec MLEM and OSEM of the TomoRebuild software package, the original DISRA, its accelerated version provided in JPIXET and the accelerated MLEM version of JPIXET, with or without correction.

  2. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique1

    Science.gov (United States)

    Hirano, Keiichi

    2017-01-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a specific wavevector transfer is the two-dimensional reflectivity distribution of the sample. In this manner, it is possible to retrieve the micro-X-ray reflectivity (where the pixel size is on the microscale) profiles at different local positions on the sample. PMID:28656036

  3. Interface-sensitive imaging by an image reconstruction aided X-ray reflectivity technique.

    Science.gov (United States)

    Jiang, Jinxing; Hirano, Keiichi; Sakurai, Kenji

    2017-06-01

    Recently, the authors have succeeded in realizing X-ray reflectivity imaging of heterogeneous ultrathin films at specific wavevector transfers by applying a wide parallel beam and an area detector. By combining in-plane angle and grazing-incidence angle scans, it is possible to reconstruct a series of interface-sensitive X-ray reflectivity images at different grazing-incidence angles (proportional to wavevector transfers). The physical meaning of a reconstructed X-ray reflectivity image at a specific wavevector transfer is the two-dimensional reflectivity distribution of the sample. In this manner, it is possible to retrieve the micro-X-ray reflectivity (where the pixel size is on the microscale) profiles at different local positions on the sample.

  4. Alternative standardization approaches to improving streamflow reconstructions with ring-width indices of riparian trees

    Science.gov (United States)

    Meko, David M; Friedman, Jonathan M.; Touchan, Ramzi; Edmondson, Jesse R.; Griffin, Eleanor R.; Scott, Julian A.

    2015-01-01

    Old, multi-aged populations of riparian trees provide an opportunity to improve reconstructions of streamflow. Here, ring widths of 394 plains cottonwood (Populus deltoids, ssp. monilifera) trees in the North Unit of Theodore Roosevelt National Park, North Dakota, are used to reconstruct streamflow along the Little Missouri River (LMR), North Dakota, US. Different versions of the cottonwood chronology are developed by (1) age-curve standardization (ACS), using age-stratified samples and a single estimated curve of ring width against estimated ring age, and (2) time-curve standardization (TCS), using a subset of longer ring-width series individually detrended with cubic smoothing splines of width against year. The cottonwood chronologies are combined with the first principal component of four upland conifer chronologies developed by conventional methods to investigate the possible value of riparian tree-ring chronologies for streamflow reconstruction of the LMR. Regression modeling indicates that the statistical signal for flow is stronger in the riparian cottonwood than in the upland chronologies. The flow signal from cottonwood complements rather than repeats the signal from upland conifers and is especially strong in young trees (e.g. 5–35 years). Reconstructions using a combination of cottonwoods and upland conifers are found to explain more than 50% of the variance of LMR flow over a 1935–1990 calibration period and to yield reconstruction of flow to 1658. The low-frequency component of reconstructed flow is sensitive to the choice of standardization method for the cottonwood. In contrast to the TCS version, the ACS reconstruction features persistent low flows in the 19th century. Results demonstrate the value to streamflow reconstruction of riparian cottonwood and suggest that more studies are needed to exploit the low-frequency streamflow signal in densely sampled age-stratified stands of riparian trees.

  5. Exploring the Nuclear Landscape by Image Reconstruction Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Morales, I.; Mendoza T, J.; Lopez V, J.C.; Barea, J.; Hirsch, J.G.; Frank, A. [Instituto de Ciencias Nucleares, UNAM, AP 70-543, 04510 Mexico D.F. (Mexico); Velazquez, V. [Departamento de Fisica, Facultad de Ciencias, UNAM, AP 70-348, 04511 Mexico D.F. (Mexico)]. e-mail: frank@nucleares.unam.mx

    2007-12-15

    In spite of the development of ever more elaborate techniques for the calculation of nuclear properties, the calculation of the most basic property of atomic nuclei, their mass, still represents a challenging task. The differences between measured masses and Liquid Drop Model (LDM) predictions have well known regularities. They contain information related to shell closures, nuclear deformation and the residual nuclear interactions, and display a well defined pattern, which can be viewed as a two-dimensional image. In the present work the more than 2000 known nuclear masses are studied as an array in the N-Z plane viewed through a mask, behind which the approximately 7000 unknown unstable nuclei that can exist between the proton and neutron drip lines are hidden. Employing a Fourier transform deconvolution method these masses can be predicted. Measured masses are reconstructed with and r.m.s. error of less than 100 keV. Potential applications of the present approach are outlined. (Author)

  6. High-definition computed tomography for coronary artery stents imaging: Initial evaluation of the optimal reconstruction algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaoming, E-mail: mmayzy2008@126.com; Li, Tao, E-mail: litaofeivip@163.com; Li, Xin, E-mail: lx0803@sina.com.cn; Zhou, Weihua, E-mail: wangxue0606@gmail.com

    2015-05-15

    Highlights: • High-resolution scan mode is appropriate for imaging coronary stent. • HD-detail reconstruction algorithm is stent-dedicated kernel. • The intrastent lumen visibility also depends on stent diameter and material. - Abstract: Objective: The aim of this study was to evaluate the in vivo performance of four image reconstruction algorithms in a high-definition CT (HDCT) scanner with improved spatial resolution for the evaluation of coronary artery stents and intrastent lumina. Materials and methods: Thirty-nine consecutive patients with a total of 71 implanted coronary stents underwent coronary CT angiography (CCTA) on a HDCT (Discovery CT 750 HD; GE Healthcare) with the high-resolution scanning mode. Four different reconstruction algorithms (HD-stand, HD-detail; HD-stand-plus; HD-detail-plus) were applied to reconstruct the stented coronary arteries. Image quality for stent characterization was assessed. Image noise and intrastent luminal diameter were measured. The relationship between the measurement of inner stent diameter (ISD) and the true stent diameter (TSD) and stent type were analysed. Results: The stent-dedicated kernel (HD-detail) offered the highest percentage (53.5%) of good image quality for stent characterization and the highest ratio (68.0 ± 8.4%) of visible stent lumen/true stent lumen for luminal diameter measurement at the expense of an increased overall image noise. The Pearson correlation coefficient between the ISD and TSD measurement and spearman correlation coefficient between the ISD measurement and stent type were 0.83 and 0.48, respectively. Conclusions: Compared with standard reconstruction algorithms, high-definition CT imaging technique with dedicated high-resolution reconstruction algorithm provides more accurate stent characterization and intrastent luminal diameter measurement.

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

    NARCIS (Netherlands)

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

    To evaluate image quality (IQ) of low-radiation-dose paediatric cardiovascular CT angiography (CTA), comparing iterative reconstruction in image space (IRIS) and sinogram-affirmed iterative reconstruction (SAFIRE) with filtered back-projection (FBP) and estimate the potential for further dose

  8. Molecular Imaging : Computer Reconstruction and Practice - Proceedings of the NATO Advanced Study Institute on Molecular Imaging from Physical Principles to Computer Reconstruction and Practice

    CERN Document Server

    Lemoigne, Yves

    2008-01-01

    This volume collects the lectures presented at the ninth ESI School held at Archamps (FR) in November 2006 and is dedicated to nuclear physics applications in molecular imaging. The lectures focus on the multiple facets of image reconstruction processing and management and illustrate the role of digital imaging in clinical practice. Medical computing and image reconstruction are introduced by analysing the underlying physics principles and their implementation, relevant quality aspects, clinical performance and recent advancements in the field. Several stages of the imaging process are specifically addressed, e.g. optimisation of data acquisition and storage, distributed computing, physiology and detector modelling, computer algorithms for image reconstruction and measurement in tomography applications, for both clinical and biomedical research applications. All topics are presented with didactical language and style, making this book an appropriate reference for students and professionals seeking a comprehen...

  9. Optimization-based image reconstruction with artifact reduction in C-arm CBCT

    Science.gov (United States)

    Xia, Dan; Langan, David A.; Solomon, Stephen B.; Zhang, Zheng; Chen, Buxin; Lai, Hao; Sidky, Emil Y.; Pan, Xiaochuan

    2016-10-01

    We investigate an optimization-based reconstruction, with an emphasis on image-artifact reduction, from data collected in C-arm cone-beam computed tomography (CBCT) employed in image-guided interventional procedures. In the study, an image to be reconstructed is formulated as a solution to a convex optimization program in which a weighted data divergence is minimized subject to a constraint on the image total variation (TV); a data-derivative fidelity is introduced in the program specifically for effectively suppressing dominant, low-frequency data artifact caused by, e.g. data truncation; and the Chambolle-Pock (CP) algorithm is tailored to reconstruct an image through solving the program. Like any other reconstructions, the optimization-based reconstruction considered depends upon numerous parameters. We elucidate the parameters, illustrate their determination, and demonstrate their impact on the reconstruction. The optimization-based reconstruction, when applied to data collected from swine and patient subjects, yields images with visibly reduced artifacts in contrast to the reference reconstruction, and it also appears to exhibit a high degree of robustness against distinctively different anatomies of imaged subjects and scanning conditions of clinical significance. Knowledge and insights gained in the study may be exploited for aiding in the design of practical reconstructions of truly clinical-application utility.

  10. A qualitative and quantitative analysis of radiation dose and image quality of computed tomography images using adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Hussain, Fahad Ahmed; Mail, Noor; Shamy, Abdulrahman M; Suliman, Alghamdi; Saoudi, Abdelhamid

    2016-05-08

    Image quality is a key issue in radiology, particularly in a clinical setting where it is important to achieve accurate diagnoses while minimizing radiation dose. Some computed tomography (CT) manufacturers have introduced algorithms that claim significant dose reduction. In this study, we assessed CT image quality produced by two reconstruction algorithms provided with GE Healthcare's Discovery 690 Elite positron emission tomography (PET) CT scanner. Image quality was measured for images obtained at various doses with both conventional filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR) algorithms. A stan-dard CT dose index (CTDI) phantom and a pencil ionization chamber were used to measure the CT dose at 120 kVp and an exposure of 260 mAs. Image quality was assessed using two phantoms. CT images of both phantoms were acquired at tube voltage (kV) of 120 with exposures ranging from 25 mAs to 400 mAs. Images were reconstructed using FBP and ASIR ranging from 10% to 100%, then analyzed for noise, low-contrast detectability, contrast-to-noise ratio (CNR), and modulation transfer function (MTF). Noise was 4.6 HU in water phantom images acquired at 260 mAs/FBP 120 kV and 130 mAs/50% ASIR 120 kV. The large objects (fre-quency ASIR, compared to 260 mAs/FBP. The application of ASIR for small objects (frequency >7 lp/cm) showed poor visibility compared to FBP at 260 mAs and even worse for images acquired at less than 130 mAs. ASIR blending more than 50% at low dose tends to reduce contrast of small objects (frequency >7 lp/cm). We concluded that dose reduction and ASIR should be applied with close attention if the objects to be detected or diagnosed are small (frequency > 7 lp/cm). Further investigations are required to correlate the small objects (frequency > 7 lp/cm) to patient anatomy and clinical diagnosis.

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

    Science.gov (United States)

    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.

  12. Optoacoustic Imaging and Tomography: Reconstruction Approaches and Outstanding Challenges in Image Performance and Quantification

    Directory of Open Access Journals (Sweden)

    Daniel Razansky

    2013-06-01

    Full Text Available This paper comprehensively reviews the emerging topic of optoacoustic imaging from the image reconstruction and quantification perspective. Optoacoustic imaging combines highly attractive features, including rich contrast and high versatility in sensing diverse biological targets, excellent spatial resolution not compromised by light scattering, and relatively low cost of implementation. Yet, living objects present a complex target for optoacoustic imaging due to the presence of a highly heterogeneous tissue background in the form of strong spatial variations of scattering and absorption. Extracting quantified information on the actual distribution of tissue chromophores and other biomarkers constitutes therefore a challenging problem. Image quantification is further compromised by some frequently-used approximated inversion formulae. In this review, the currently available optoacoustic image reconstruction and quantification approaches are assessed, including back-projection and model-based inversion algorithms, sparse signal representation, wavelet-based approaches, methods for reduction of acoustic artifacts as well as multi-spectral methods for visualization of tissue bio-markers. Applicability of the different methodologies is further analyzed in the context of real-life performance in small animal and clinical in-vivo imaging scenarios.

  13. Postoperative evaluation after anterior cruciate ligament reconstruction: Measurements and abnormalities on radiographic and CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Cheol; Choi, Yun Sun; KIm, Hyoung Seop; Choi, Nam Hong [Nowon Eulji Medical Center, Eulji University, Seoul (Korea, Republic of)

    2016-11-15

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

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

    Directory of Open Access Journals (Sweden)

    Hongliang Qi

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  16. Research on assessment and improvement method of remote sensing image reconstruction

    Science.gov (United States)

    Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

    2018-01-01

    Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

  17. Research on super-resolution image reconstruction based on an improved POCS algorithm

    Science.gov (United States)

    Xu, Haiming; Miao, Hong; Yang, Chong; Xiong, Cheng

    2015-07-01

    Super-resolution image reconstruction (SRIR) can improve the fuzzy image's resolution; solve the shortage of the spatial resolution, excessive noise, and low-quality problem of the image. Firstly, we introduce the image degradation model to reveal the essence of super-resolution reconstruction process is an ill-posed inverse problem in mathematics. Secondly, analysis the blurring reason of optical imaging process - light diffraction and small angle scattering is the main reason for the fuzzy; propose an image point spread function estimation method and an improved projection onto convex sets (POCS) algorithm which indicate effectiveness by analyzing the changes between the time domain and frequency domain algorithm in the reconstruction process, pointed out that the improved POCS algorithms based on prior knowledge have the effect to restore and approach the high frequency of original image scene. Finally, we apply the algorithm to reconstruct synchrotron radiation computer tomography (SRCT) image, and then use these images to reconstruct the three-dimensional slice images. Comparing the differences between the original method and super-resolution algorithm, it is obvious that the improved POCS algorithm can restrain the noise and enhance the image resolution, so it is indicated that the algorithm is effective. This study and exploration to super-resolution image reconstruction by improved POCS algorithm is proved to be an effective method. It has important significance and broad application prospects - for example, CT medical image processing and SRCT ceramic sintering analyze of microstructure evolution mechanism.

  18. Rational designing of the internal water supply system in reconstructed residential buildings of mass standard series

    Directory of Open Access Journals (Sweden)

    Orlov Evgeny

    2018-01-01

    Full Text Available The issues of water supply system reconstruction in mass series buildings are reviewed with consideration of water- and resource saving. Principal points for location of plumbing cells in apartments, arrangement of water devices and wastewater receivers, selection of pipelines for reconstructed water line are described. Comparative analysis of design variants of inner water line before and following reconstruction are given. It was found that applying the developed system design approaches the head losses in the inner water supply line will be significantly decreased as well as the water mains length will be decreased with material and installation saving. Based on the data the conclusions on necessity to review standard arrangement solutions of water supply systems in the reconstructed buildings were made. Recommendations on water loss reduction in the system by installation of special water saving fittings on water devices and touchless faucets.

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

    Science.gov (United States)

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

    2015-01-01

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

  20. 4D reconstruction of the past: the image retrieval and 3D model construction pipeline

    Science.gov (United States)

    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.

  1. Evaluating image reconstruction methods for tumor detection performance in whole-body PET oncology imaging

    Science.gov (United States)

    Lartizien, Carole; Kinahan, Paul E.; Comtat, Claude; Lin, Michael; Swensson, Richard G.; Trebossen, Regine; Bendriem, Bernard

    2000-04-01

    This work presents initial results from observer detection performance studies using the same volume visualization software tools that are used in clinical PET oncology imaging. Research into the FORE+OSEM and FORE+AWOSEM statistical image reconstruction methods tailored to whole- body 3D PET oncology imaging have indicated potential improvements in image SNR compared to currently used analytic reconstruction methods (FBP). To assess the resulting impact of these reconstruction methods on the performance of human observers in detecting and localizing tumors, we use a non- Monte Carlo technique to generate multiple statistically accurate realizations of 3D whole-body PET data, based on an extended MCAT phantom and with clinically realistic levels of statistical noise. For each realization, we add a fixed number of randomly located 1 cm diam. lesions whose contrast is varied among pre-calibrated values so that the range of true positive fractions is well sampled. The observer is told the number of tumors and, similar to the AFROC method, asked to localize all of them. The true positive fraction for the three algorithms (FBP, FORE+OSEM, FORE+AWOSEM) as a function of lesion contrast is calculated, although other protocols could be compared. A confidence level for each tumor is also recorded for incorporation into later AFROC analysis.

  2. Reducing the radiation dose for low-dose CT of the paranasal sinuses using iterative reconstruction: Feasibility and image quality

    Energy Technology Data Exchange (ETDEWEB)

    Bulla, Stefan, E-mail: stefan.bulla@uniklinik-freiburg.de [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany); Blanke, Philipp, E-mail: philipp.blanke@uniklinik.freiburg.de [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany); Hassepass, Frederike, E-mail: frederike.hassepass@uniklinik.freiburg.de [Department of Otorhinolaryngology – Head and Neck Surgery, University Hospital Freiburg, Killianstraße 5, 79106 Freiburg (Germany); Krauss, Tobias, E-mail: tobias.krauss@uniklinik.freiburg.de [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany); Winterer, Jan Thorsten, E-mail: jan.winterer@uniklinik.freiburg.de [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany); Breunig, Christine, E-mail: christine.breunig@uniklinik.freiburg.de [Department of Otorhinolaryngology – Head and Neck Surgery, University Hospital Freiburg, Killianstraße 5, 79106 Freiburg (Germany); Langer, Mathias, E-mail: mathias.langer@uniklinik.freiburg.de [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany); Pache, Gregor [Department of Diagnostic Radiology, University Hospital Freiburg, Hugstetter Str. 55, 79106 Freiburg (Germany)

    2012-09-15

    Purpose: To evaluate image quality of dose-reduced CT of the paranasal-sinus using an iterative reconstruction technique. Methods: In this study 80 patients (mean age: 46.9 ± 18 years) underwent CT of the paranasalsinus (Siemens Definition, Forchheim, Germany), with either standard settings (A: 120 kV, 60 mAs) reconstructed with conventional filtered back projection (FBP) or with tube current–time product lowering of 20%, 40% and 60% (B: 48 mAs, C: 36 mAs and D: 24 mAs) using iterative reconstruction (n = 20 each). Subjective image quality was independently assessed by four blinded observers using a semiquantitative five-point grading scale (1 = poor, 5 = excellent). Effective dose was calculated from the dose-length product. Mann–Whitney-U-test was used for statistical analysis. Results: Mean effective dose was 0.28 ± 0.03 mSv(A), 0.23 ± 0.02 mSv(B), 0.17 ± 0.02 mSv(C) and 0.11 ± 0.01 mSv(D) resulting in a maximum dose reduction of 60% with iterative reconstruction technique as compared to the standard low-dose CT. Best image quality was observed at 48 mAs (mean 4.8; p < 0.05), whereas standard low-dose CT (A) and maximum dose reduced scans (D) showed no significant difference in subjective image quality (mean 4.37 (A) and 4.31 (B); p = 0.72). Interobserver agreement was excellent (κ values 0.79–0.93). Conclusion: As compared to filtered back projection, the iterative reconstruction technique allows for significant dose reduction of up to 60% for paranasal-sinus CT without impairing the diagnostic image quality.

  3. A two-step filtering-based iterative image reconstruction method for interior tomography.

    Science.gov (United States)

    Zhang, Hanming; Li, Lei; Yan, Bin; Wang, Linyuan; Cai, Ailong; Hu, Guoen

    2016-10-06

    The optimization-based method that utilizes the additional sparse prior of region-of-interest (ROI) image, such as total variation, has been the subject of considerable research in problems of interior tomography reconstruction. One challenge for optimization-based iterative ROI image reconstruction is to build the relationship between ROI image and truncated projection data. When the reconstruction support region is smaller than the original object, an unsuitable representation of data fidelity may lead to bright truncation artifacts in the boundary region of field of view. In this work, we aim to develop an iterative reconstruction method to suppress the truncation artifacts and improve the image quality for direct ROI image reconstruction. A novel reconstruction approach is proposed based on an optimization problem involving a two-step filtering-based data fidelity. Data filtering is achieved in two steps: the first takes the derivative of projection data; in the second step, Hilbert filtering is applied in the differentiated data. Numerical simulations and real data reconstructions have been conducted to validate the new reconstruction method. Both qualitative and quantitative results indicate that, as theoretically expected, the proposed method brings reasonable performance in suppressing truncation artifacts and preserving detailed features. The presented local reconstruction method based on the two-step filtering strategy provides a simple and efficient approach for the iterative reconstruction from truncated projections.

  4. MR Image Reconstruction Based on Iterative Split Bregman Algorithm and Nonlocal Total Variation

    Directory of Open Access Journals (Sweden)

    Varun P. Gopi

    2013-01-01

    and least-square data-fitting term to reconstruct the MR images from undersampled k-space data. The nonlocal total variation is taken as the L1-regularization functional and solved using Split Bregman iteration. The proposed algorithm is compared with previous methods in terms of the reconstruction accuracy and computational complexity. The comparison results demonstrate the superiority of the proposed algorithm for compressed MR image reconstruction.

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

    Science.gov (United States)

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

    2014-09-01

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

  6. Influence of iterative image reconstruction on CT-based calcium score measurements

    NARCIS (Netherlands)

    van Osch, Jochen A. C.; Mouden, Mohamed; van Dalen, Jorn A.; Timmer, Jorik R.; Reiffers, Stoffer; Knollema, Siert; Greuter, Marcel J. W.; Ottervanger, Jan Paul; Jager, Piet L.

    Iterative reconstruction techniques for coronary CT angiography have been introduced as an alternative for traditional filter back projection (FBP) to reduce image noise, allowing improved image quality and a potential for dose reduction. However, the impact of iterative reconstruction on the

  7. Iterative Image Reconstruction for PROPELLER-MRI using the NonUniform Fast Fourier Transform

    Science.gov (United States)

    Tamhane, Ashish A.; Anastasio, Mark A.; Gui, Minzhi; Arfanakis, Konstantinos

    2013-01-01

    Purpose To investigate an iterative image reconstruction algorithm using the non-uniform fast Fourier transform (NUFFT) for PROPELLER (Periodically Rotated Overlapping parallEL Lines with Enhanced Reconstruction) MRI. Materials and Methods Numerical simulations, as well as experiments on a phantom and a healthy human subject were used to evaluate the performance of the iterative image reconstruction algorithm for PROPELLER, and compare it to that of conventional gridding. The trade-off between spatial resolution, signal to noise ratio, and image artifacts, was investigated for different values of the regularization parameter. The performance of the iterative image reconstruction algorithm in the presence of motion was also evaluated. Results It was demonstrated that, for a certain range of values of the regularization parameter, iterative reconstruction produced images with significantly increased SNR, reduced artifacts, for similar spatial resolution, compared to gridding. Furthermore, the ability to reduce the effects of motion in PROPELLER-MRI was maintained when using the iterative reconstruction approach. Conclusion An iterative image reconstruction technique based on the NUFFT was investigated for PROPELLER MRI. For a certain range of values of the regularization parameter the new reconstruction technique may provide PROPELLER images with improved image quality compared to conventional gridding. PMID:20578028

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

    Energy Technology Data Exchange (ETDEWEB)

    Grosser, Oliver S.; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Ricke, Jens [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Wybranski, Christian [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne (Germany); Pech, Maciej [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Medical University of Gdansk, Second Department of Radiology, Gdansk (Poland); Amthauer, Holger [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Charite, Department of Nuclear Medicine, Berlin (Germany)

    2017-09-15

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

  9. Digital aberration correction of fluorescent images with coherent holographic image reconstruction by phase transfer (CHIRPT)

    Science.gov (United States)

    Field, Jeffrey J.; Bartels, Randy A.

    2016-03-01

    Coherent holographic image reconstruction by phase transfer (CHIRPT) is an imaging method that permits digital holographic propagation of fluorescent light. The image formation process in CHIRPT is based on illuminating the specimen with a precisely controlled spatio-temporally varying intensity pattern. This pattern is formed by focusing a spatially coherent illumination beam to a line focus on a spinning modulation mask, and image relaying the mask plane to the focal plane of an objective lens. Deviations from the designed spatio-temporal illumination pattern due to imperfect mounting of the circular modulation mask onto the rotation motor induce aberrations in the recovered image. Here we show that these aberrations can be measured and removed non-iteratively by measuring the disk aberration phase externally. We also demonstrate measurement and correction of systematic optical aberrations in the CHIRPT microscope.

  10. Intra-patient comparison of reduced-dose model-based iterative reconstruction with standard-dose adaptive statistical iterative reconstruction in the CT diagnosis and follow-up of urolithiasis

    Energy Technology Data Exchange (ETDEWEB)

    Tenant, Sean; Pang, Chun Lap; Dissanayake, Prageeth [Peninsula Radiology Academy, Plymouth (United Kingdom); Vardhanabhuti, Varut [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); University of Hong Kong, Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, Pokfulam (China); Stuckey, Colin; Gutteridge, Catherine [Plymouth Hospitals NHS Trust, Plymouth (United Kingdom); Hyde, Christopher [University of Exeter Medical School, St Luke' s Campus, Exeter (United Kingdom); Roobottom, Carl [Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth (United Kingdom); Plymouth Hospitals NHS Trust, Plymouth (United Kingdom)

    2017-10-15

    To evaluate the accuracy of reduced-dose CT scans reconstructed using a new generation of model-based iterative reconstruction (MBIR) in the imaging of urinary tract stone disease, compared with a standard-dose CT using 30% adaptive statistical iterative reconstruction. This single-institution prospective study recruited 125 patients presenting either with acute renal colic or for follow-up of known urinary tract stones. They underwent two immediately consecutive scans, one at standard dose settings and one at the lowest dose (highest noise index) the scanner would allow. The reduced-dose scans were reconstructed using both ASIR 30% and MBIR algorithms and reviewed independently by two radiologists. Objective and subjective image quality measures as well as diagnostic data were obtained. The reduced-dose MBIR scan was 100% concordant with the reference standard for the assessment of ureteric stones. It was extremely accurate at identifying calculi of 3 mm and above. The algorithm allowed a dose reduction of 58% without any loss of scan quality. A reduced-dose CT scan using MBIR is accurate in acute imaging for renal colic symptoms and for urolithiasis follow-up and allows a significant reduction in dose. (orig.)

  11. The DIADEM data sets: representative light microscopy images of neuronal morphology to advance automation of digital reconstructions.

    Science.gov (United States)

    Brown, Kerry M; Barrionuevo, Germán; Canty, Alison J; De Paola, Vincenzo; Hirsch, Judith A; Jefferis, Gregory S X E; Lu, Ju; Snippe, Marjolein; Sugihara, Izumi; Ascoli, Giorgio A

    2011-09-01

    The comprehensive characterization of neuronal morphology requires tracing extensive axonal and dendritic arbors imaged with light microscopy into digital reconstructions. Considerable effort is ongoing to automate this greatly labor-intensive and currently rate-determining process. Experimental data in the form of manually traced digital reconstructions and corresponding image stacks play a vital role in developing increasingly more powerful reconstruction algorithms. The DIADEM challenge (short for DIgital reconstruction of Axonal and DEndritic Morphology) successfully stimulated progress in this area by utilizing six data set collections from different animal species, brain regions, neuron types, and visualization methods. The original research projects that provided these data are representative of the diverse scientific questions addressed in this field. At the same time, these data provide a benchmark for the types of demands automated software must meet to achieve the quality of manual reconstructions while minimizing human involvement. The DIADEM data underwent extensive curation, including quality control, metadata annotation, and format standardization, to focus the challenge on the most substantial technical obstacles. This data set package is now freely released ( http://diademchallenge.org ) to train, test, and aid development of automated reconstruction algorithms.

  12. MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

    Energy Technology Data Exchange (ETDEWEB)

    Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J [UT MD Anderson Cancer Center, Houston, TX (United States)

    2015-06-15

    Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

  13. Stepwise method based on Wiener estimation for spectral reconstruction in spectroscopic Raman imaging.

    Science.gov (United States)

    Chen, Shuo; Wang, Gang; Cui, Xiaoyu; Liu, Quan

    2017-01-23

    Raman spectroscopy has demonstrated great potential in biomedical applications. However, spectroscopic Raman imaging is limited in the investigation of fast changing phenomena because of slow data acquisition. Our previous studies have indicated that spectroscopic Raman imaging can be significantly sped up using the approach of narrow-band imaging followed by spectral reconstruction. A multi-channel system was built to demonstrate the feasibility of fast wide-field spectroscopic Raman imaging using the approach of simultaneous narrow-band image acquisition followed by spectral reconstruction based on Wiener estimation in phantoms. To further improve the accuracy of reconstructed Raman spectra, we propose a stepwise spectral reconstruction method in this study, which can be combined with the earlier developed sequential weighted Wiener estimation to improve spectral reconstruction accuracy. The stepwise spectral reconstruction method first reconstructs the fluorescence background spectrum from narrow-band measurements and then the pure Raman narrow-band measurements can be estimated by subtracting the estimated fluorescence background from the overall narrow-band measurements. Thereafter, the pure Raman spectrum can be reconstructed from the estimated pure Raman narrow-band measurements. The result indicates that the stepwise spectral reconstruction method can improve spectral reconstruction accuracy significantly when combined with sequential weighted Wiener estimation, compared with the traditional Wiener estimation. In addition, qualitatively accurate cell Raman spectra were successfully reconstructed using the stepwise spectral reconstruction method from the narrow-band measurements acquired by a four-channel wide-field Raman spectroscopic imaging system. This method can potentially facilitate the adoption of spectroscopic Raman imaging to the investigation of fast changing phenomena.

  14. Applications of compressed sensing image reconstruction to sparse view phase tomography

    Science.gov (United States)

    Ueda, Ryosuke; Kudo, Hiroyuki; Dong, Jian

    2017-10-01

    X-ray phase CT has a potential to give the higher contrast in soft tissue observations. To shorten the measure- ment time, sparse-view CT data acquisition has been attracting the attention. This paper applies two major compressed sensing (CS) approaches to image reconstruction in the x-ray sparse-view phase tomography. The first CS approach is the standard Total Variation (TV) regularization. The major drawbacks of TV regularization are a patchy artifact and loss in smooth intensity changes due to the piecewise constant nature of image model. The second CS method is a relatively new approach of CS which uses a nonlinear smoothing filter to design the regularization term. The nonlinear filter based CS is expected to reduce the major artifact in the TV regular- ization. The both cost functions can be minimized by the very fast iterative reconstruction method. However, in the past research activities, it is not clearly demonstrated how much image quality difference occurs between the TV regularization and the nonlinear filter based CS in x-ray phase CT applications. We clarify the issue by applying the two CS applications to the case of x-ray phase tomography. We provide results with numerically simulated data, which demonstrates that the nonlinear filter based CS outperforms the TV regularization in terms of textures and smooth intensity changes.

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

    Science.gov (United States)

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

    2014-06-01

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

  16. 40 CFR 63.1158 - Emission standards for new or reconstructed sources.

    Science.gov (United States)

    2010-07-01

    ... Process Facilities and Hydrochloric Acid Regeneration Plants § 63.1158 Emission standards for new or... percent. (b) Hydrochloric acid regeneration plants. (1) No owner or operator of a new or reconstructed affected plant shall cause or allow to be discharged into the atmosphere from the affected plant any gases...

  17. Electrodynamics sensor for the image reconstruction process in an electrical charge tomography system.

    Science.gov (United States)

    Rahmat, Mohd Fua'ad; Isa, Mohd Daud; Rahim, Ruzairi Abdul; Hussin, Tengku Ahmad Raja

    2009-01-01

    Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of materials being conveyed based on data measured by an electrodynamics sensor installed around the pipe. Image reconstruction in electrical charge tomography is vital and has not been widely studied before. Three methods have been introduced before, namely the linear back projection method, the filtered back projection method and the least square method. These methods normally face ill-posed problems and their solutions are unstable and inaccurate. In order to ensure the stability and accuracy, a special solution should be applied to obtain a meaningful image reconstruction result. In this paper, a new image reconstruction method - Least squares with regularization (LSR) will be introduced to reconstruct the image of material in a gravity mode conveyor pipeline for electrical charge tomography. Numerical analysis results based on simulation data indicated that this algorithm efficiently overcomes the numerical instability. The results show that the accuracy of the reconstruction images obtained using the proposed algorithm was enhanced and similar to the image captured by a CCD Camera. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.

  18. Multi-view Multi-sparsity Kernel Reconstruction for Multi-class Image Classification

    KAUST Repository

    Zhu, Xiaofeng

    2015-05-28

    This paper addresses the problem of multi-class image classification by proposing a novel multi-view multi-sparsity kernel reconstruction (MMKR for short) model. Given images (including test images and training images) representing with multiple visual features, the MMKR first maps them into a high-dimensional space, e.g., a reproducing kernel Hilbert space (RKHS), where test images are then linearly reconstructed by some representative training images, rather than all of them. Furthermore a classification rule is proposed to classify test images. Experimental results on real datasets show the effectiveness of the proposed MMKR while comparing to state-of-the-art algorithms.

  19. On multigrid methods for image reconstruction from projections

    Energy Technology Data Exchange (ETDEWEB)

    Henson, V.E.; Robinson, B.T. [Naval Postgraduate School, Monterey, CA (United States); Limber, M. [Simon Fraser Univ., Burnaby, British Columbia (Canada)

    1994-12-31

    The sampled Radon transform of a 2D function can be represented as a continuous linear map R : L{sup 1} {yields} R{sup N}. The image reconstruction problem is: given a vector b {element_of} R{sup N}, find an image (or density function) u(x, y) such that Ru = b. Since in general there are infinitely many solutions, the authors pick the solution with minimal 2-norm. Numerous proposals have been made regarding how best to discretize this problem. One can, for example, select a set of functions {phi}{sub j} that span a particular subspace {Omega} {contained_in} L{sup 1}, and model R : {Omega} {yields} R{sup N}. The subspace {Omega} may be chosen as a member of a sequence of subspaces whose limit is dense in L{sup 1}. One approach to the choice of {Omega} gives rise to a natural pixel discretization of the image space. Two possible choices of the set {phi}{sub j} are the set of characteristic functions of finite-width `strips` representing energy transmission paths and the set of intersections of such strips. The authors have studied the eigenstructure of the matrices B resulting from these choices and the effect of applying a Gauss-Seidel iteration to the problem Bw = b. There exists a near null space into which the error vectors migrate with iteration, after which Gauss-Seidel iteration stalls. The authors attempt to accelerate convergence via a multilevel scheme, based on the principles of McCormick`s Multilevel Projection Method (PML). Coarsening is achieved by thickening the rays which results in a much smaller discretization of an optimal grid, and a halving of the number of variables. This approach satisfies all the requirements of the PML scheme. They have observed that a multilevel approach based on this idea accelerates convergence at least to the point where noise in the data dominates.

  20. String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images

    Science.gov (United States)

    Massambone de Oliveira, Rafael; Salomão Helou, Elias; Fontoura Costa, Eduardo

    2016-11-01

    We present a method for non-smooth convex minimization which is based on subgradient directions and string-averaging techniques. In this approach, the set of available data is split into sequences (strings) and a given iterate is processed independently along each string, possibly in parallel, by an incremental subgradient method (ISM). The end-points of all strings are averaged to form the next iterate. The method is useful to solve sparse and large-scale non-smooth convex optimization problems, such as those arising in tomographic imaging. A convergence analysis is provided under realistic, standard conditions. Numerical tests are performed in a tomographic image reconstruction application, showing good performance for the convergence speed when measured as the decrease ratio of the objective function, in comparison to classical ISM.

  1. Low-dose abdominal CT: comparison of low tube voltage with moderate-level iterative reconstruction and standard tube voltage, low tube current with high-level iterative reconstruction.

    Science.gov (United States)

    Kidoh, M; Nakaura, T; Nakamura, S; Oda, S; Utsunomiya, D; Sakai, Y; Harada, K; Yamashita, Y

    2013-10-01

    To evaluate the quality of 100 kVp images with a hybrid iterative reconstruction algorithm level of 40% and 120 kVp (low-tube-current) images with a hybrid iterative reconstruction algorithm level of 60% in low-dose abdominal computed tomography (CT) using almost the same radiation dose. This prospective study received institutional review board approval and written informed consent was obtained. One hundred and ten patients undergoing abdominal dynamic CT were randomly assigned to one of two protocols (100 and 120 kVp protocols). Radiation doses of the two protocols were almost identical. The 120 kVp images were post-processed with a hybrid iterative reconstruction algorithm level of 60% (i-120 kVp). The 100 kVp images were post-processed with a hybrid iterative reconstruction algorithm level of 40% (i-100 kVp). The effective dose (ED), image noise, CT attenuation, and signal-to-noise ratio (SNR) of the subcutaneous fat, muscle, liver, pancreas, and kidneys were compared between the protocols using Student's t-test. Qualitative analysis was also performed between the protocols. There were no significant differences in ED and SNR of any of the regions of interest (ROIs) between the protocols (p > 0.05). However, in the qualitative analysis, unnatural texture was significantly greater in the i-120 kVp than in the i-100 kVp protocol (p 0.05). The combined use of low tube voltage and moderate-level iterative reconstruction techniques can be a more effective strategy for reducing patient radiation dose while attaining acceptable image quality than the use of standard tube voltage, low tube current with high-level iterative reconstruction. Copyright © 2013 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  2. Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards.

    Science.gov (United States)

    Caffery, Liam J; Clunie, David; Curiel-Lewandrowski, Clara; Malvehy, Josep; Soyer, H Peter; Halpern, Allan C

    2018-01-17

    Imaging is increasingly being used in dermatology for documentation, diagnosis, and management of cutaneous disease. The lack of standards for dermatologic imaging is an impediment to clinical uptake. Standardization can occur in image acquisition, terminology, interoperability, and metadata. This paper presents the International Skin Imaging Collaboration position on standardization of metadata for dermatologic imaging. Metadata is essential to ensure that dermatologic images are properly managed and interpreted. There are two standards-based approaches to recording and storing metadata in dermatologic imaging. The first uses standard consumer image file formats, and the second is the file format and metadata model developed for the Digital Imaging and Communication in Medicine (DICOM) standard. DICOM would appear to provide an advantage over using consumer image file formats for metadata as it includes all the patient, study, and technical metadata necessary to use images clinically. Whereas, consumer image file formats only include technical metadata and need to be used in conjunction with another actor-for example, an electronic medical record-to supply the patient and study metadata. The use of DICOM may have some ancillary benefits in dermatologic imaging including leveraging DICOM network and workflow services, interoperability of images and metadata, leveraging existing enterprise imaging infrastructure, greater patient safety, and better compliance to legislative requirements for image retention.

  3. A biomechanical modeling guided simultaneous motion estimation and image reconstruction technique (SMEIR-Bio) for 4D-CBCT reconstruction

    Science.gov (United States)

    Huang, Xiaokun; Zhang, You; Wang, Jing

    2017-03-01

    Four-dimensional (4D) cone-beam computed tomography (CBCT) enables motion tracking of anatomical structures and removes artifacts introduced by motion. However, the imaging time/dose of 4D-CBCT is substantially longer/higher than traditional 3D-CBCT. We previously developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, to reconstruct high-quality 4D-CBCT from limited number of projections to reduce the imaging time/dose. However, the accuracy of SMEIR is limited in reconstructing low-contrast regions with fine structure details. In this study, we incorporate biomechanical modeling into the SMEIR algorithm (SMEIR-Bio), to improve the reconstruction accuracy at low-contrast regions with fine details. The efficacy of SMEIR-Bio is evaluated using 11 lung patient cases and compared to that of the original SMEIR algorithm. Qualitative and quantitative comparisons showed that SMEIR-Bio greatly enhances the accuracy of reconstructed 4D-CBCT volume in low-contrast regions, which can potentially benefit multiple clinical applications including the treatment outcome analysis.

  4. Fast and memory-efficient Monte Carlo-based image reconstruction for whole-body PET.

    Science.gov (United States)

    Zhang, Long; Staelens, Steven; Van Holen, Roel; De Beenhouwer, Jan; Verhaeghe, Jeroen; Kawrakow, Iwan; Vandenberghe, Stefaan

    2010-07-01

    Several studies have shown the benefit of an accurate system modeling using Monte Carlo techniques. For state-of-the-art whole-body positron emission tomography (PET) scanners, Monte Carlo-based image reconstruction is associated with a significant computational cost to calculate the system matrix as well as a large memory capacity to store it. In this article, the authors present a simulation-reconstruction framework to solve these problems on the Philips Gemini GS PET scanner. A fast, realistic system matrix simulation module was developed using egs_pet, which is an efficient PET simulation code based on EGSnrc. The generated system matrix was then used in a rotator-based ordered subset expectation maximization (OS-EM) algorithm, which exploits the rotational symmetry of a cylindrical PET scanner. The system matrix was further compressed by using sparse storage techniques. The system matrix simulation took five days on 50 cores of Xeon 2.66 GHz, resulting in a system matrix of 2.01 GB. The entire system matrix could be stored in the main memory of a standard personal computer. The image quality in terms of contrast-noise trade-offs was considerably improved compared to a standard OS-EM algorithm. The image quality was also compared to the clinical software on the scanner using routine parameter settings. The contrast recovery coefficient of small hot spheres and cold spheres was significantly improved. The results indicated that the proposed framework could be used for this PET scanner with improved image quality. This method could also be applied to other state-of-the-art whole-body PET scanners and preclinical PET scanners with a similar shape.

  5. Recent improvements in Hurricane Imaging Radiometer’s brightness temperature image reconstruction

    Directory of Open Access Journals (Sweden)

    Sayak K. Biswas

    Full Text Available NASA MSFCs airborne Hurricane Imaging Radiometer (HIRAD uses interferometric aperture synthesis to produce high resolution wide swath images of scene brightness temperature (Tb distribution at four discrete C-band microwave frequencies (4.0, 5.0, 6.0 and 6.6 GHz. Images of ocean surface wind speed under heavy precipitation such as in tropical cyclones, is inferred from these measurements. The baseline HIRAD Tb reconstruction algorithm had produced prominent along-track streaks in the Tb images. Particularly the 4.0 GHz channel had been so dominated by the streaks as to be unusable.The loss of a frequency channel had compromised the final wind speed retrievals. During 2016, the HIRAD team made substantial progress in developing a quality controlled signal processing technique for the HIRAD data collected in 2015’s Tropical Cyclone Intensity (TCI experiment and reduced the effect of streaks in all channels including 4.0 GHz. 2000 MSC: 41A05, 41A10, 65D05, 65D17, Keywords: Microwave radiometry, Aperture synthesis, Image reconstruction, Hurricane winds

  6. An automatic panoramic image reconstruction scheme from dental computed tomography images.

    Science.gov (United States)

    Papakosta, Thekla K; Savva, Antonis D; Economopoulos, Theodore L; Matsopoulos, George K; Gröhndal, H G

    2017-04-01

    Panoramic images of the jaws are extensively used for dental examinations and/or surgical planning because they provide a general overview of the patient's maxillary and mandibular regions. Panoramic images are two-dimensional projections of three-dimensional (3D) objects. Therefore, it should be possible to reconstruct them from 3D radiographic representations of the jaws, produced by CBCT scanning, obviating the need for additional exposure to X-rays, should there be a need of panoramic views. The aim of this article is to present an automated method for reconstructing panoramic dental images from CBCT data. The proposed methodology consists of a series of sequential processing stages for detecting a fitting dental arch which is used for projecting the 3D information of the CBCT data to the two-dimensional plane of the panoramic image. The detection is based on a template polynomial which is constructed from a training data set. A total of 42 CBCT data sets of real clinical pre-operative and post-operative representations from 21 patients were used. Eight data sets were used for training the system and the rest for testing. The proposed methodology was successfully applied to CBCT data sets, producing corresponding panoramic images, suitable for examining pre-operatively and post-operatively the patients' maxillary and mandibular regions.

  7. A BPF-FBP tandem algorithm for image reconstruction in reverse helical cone-beam CT.

    Science.gov (United States)

    Cho, Seungryong; Xia, Dan; Pellizzari, Charles A; Pan, Xiaochuan

    2010-01-01

    Reverse helical cone-beam computed tomography (CBCT) is a scanning configuration for potential applications in image-guided radiation therapy in which an accurate anatomic image of the patient is needed for image-guidance procedures. The authors previously developed an algorithm for image reconstruction from nontruncated data of an object that is completely within the reverse helix. The purpose of this work is to develop an image reconstruction approach for reverse helical CBCT of a long object that extends out of the reverse helix and therefore constitutes data truncation. The proposed approach comprises of two reconstruction steps. In the first step, a chord-based backprojection-filtration (BPF) algorithm reconstructs a volumetric image of an object from the original cone-beam data. Because there exists a chordless region in the middle of the reverse helix, the image obtained in the first step contains an unreconstructed central-gap region. In the second step, the gap region is reconstructed by use of a Pack-Noo-formula-based filteredback-projection (FBP) algorithm from the modified cone-beam data obtained by subtracting from the original cone-beam data the reprojection of the image reconstructed in the first step. The authors have performed numerical studies to validate the proposed approach in image reconstruction from reverse helical cone-beam data. The results confirm that the proposed approach can reconstruct accurate images of a long object without suffering from data-truncation artifacts or cone-angle artifacts. They developed and validated a BPF-FBP tandem algorithm to reconstruct images of a long object from reverse helical cone-beam data. The chord-based BPF algorithm was utilized for converting the long-object problem into a short-object problem. The proposed approach is applicable to other scanning configurations such as reduced circular sinusoidal trajectories.

  8. A Superresolution Image Reconstruction Algorithm Based on Landweber in Electrical Capacitance Tomography

    Directory of Open Access Journals (Sweden)

    Chen Deyun

    2013-01-01

    Full Text Available According to the image reconstruction accuracy influenced by the “soft field” nature and ill-conditioned problems in electrical capacitance tomography, a superresolution image reconstruction algorithm based on Landweber is proposed in the paper, which is based on the working principle of the electrical capacitance tomography system. The method uses the algorithm which is derived by regularization of solutions derived and derives closed solution by fast Fourier transform of the convolution kernel. So, it ensures the certainty of the solution and improves the stability and quality of image reconstruction results. Simulation results show that the imaging precision and real-time imaging of the algorithm are better than Landweber algorithm, and this algorithm proposes a new method for the electrical capacitance tomography image reconstruction algorithm.

  9. Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT.

    Science.gov (United States)

    Gebhard, Cathérine; Fiechter, Michael; Fuchs, Tobias A; Stehli, Julia; Müller, Ennio; Stähli, Barbara E; Gebhard, Caroline E; Ghadri, Jelena R; Klaeser, Bernd; Gaemperli, Oliver; Kaufmann, Philipp A

    2013-10-01

    The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P Reconstruction of CCTA from HDCT using 40 and 60% ASIR incrementally improves intra-stent luminal area, diameter visualization, and image quality compared with FBP reconstruction.

  10. Alternating Direction Total Variation Image Reconstruction and Practical Decomposition for Dual-energy Computed Tomography

    CERN Document Server

    Li, Lei; Wang, Linyuan; Yan, Bin; Zhang, Hanming; Zheng, Zhizhong; Zhang, Wenkun; Lu, Wanli; Hu, Guoen

    2016-01-01

    Dual-energy computed tomography (DECT) has shown great potential and promising applications in advanced imaging fields for its capabilities of material decomposition. However, image reconstructions and decompositions under sparse views dataset suffers severely from multi factors, such as insufficiencies of data, appearances of noise, and inconsistencies of observations. Under sparse views, conventional filtered back-projection type reconstruction methods fails to provide CT images with satisfying quality. Moreover, direct image decomposition is unstable and meet with noise boost even with full views dataset. This paper proposes an iterative image reconstruction algorithm and a practical image domain decomposition method for DECT. On one hand, the reconstruction algorithm is formulated as an optimization problem, which containing total variation regularization term and data fidelity term. The alternating direction method is utilized to design the corresponding algorithm which shows faster convergence speed com...

  11. Approximate Sparsity and Nonlocal Total Variation Based Compressive MR Image Reconstruction

    Directory of Open Access Journals (Sweden)

    Chengzhi Deng

    2014-01-01

    Full Text Available Recent developments in compressive sensing (CS show that it is possible to accurately reconstruct the magnetic resonance (MR image from undersampled k-space data by solving nonsmooth convex optimization problems, which therefore significantly reduce the scanning time. In this paper, we propose a new MR image reconstruction method based on a compound regularization model associated with the nonlocal total variation (NLTV and the wavelet approximate sparsity. Nonlocal total variation can restore periodic textures and local geometric information better than total variation. The wavelet approximate sparsity achieves more accurate sparse reconstruction than fixed wavelet l0 and l1 norm. Furthermore, a variable splitting and augmented Lagrangian algorithm is presented to solve the proposed minimization problem. Experimental results on MR image reconstruction demonstrate that the proposed method outperforms many existing MR image reconstruction methods both in quantitative and in visual quality assessment.

  12. Robust framework for PET image reconstruction incorporating system and measurement uncertainties.

    Directory of Open Access Journals (Sweden)

    Huafeng Liu

    Full Text Available In Positron Emission Tomography (PET, an optimal estimate of the radioactivity concentration is obtained from the measured emission data under certain criteria. So far, all the well-known statistical reconstruction algorithms require exactly known system probability matrix a priori, and the quality of such system model largely determines the quality of the reconstructed images. In this paper, we propose an algorithm for PET image reconstruction for the real world case where the PET system model is subject to uncertainties. The method counts PET reconstruction as a regularization problem and the image estimation is achieved by means of an uncertainty weighted least squares framework. The performance of our work is evaluated with the Shepp-Logan simulated and real phantom data, which demonstrates significant improvements in image quality over the least squares reconstruction efforts.

  13. Standard morphology of the oral commissure and changes resulting from reconstruction for defects involving the commissure.

    Science.gov (United States)

    Makiguchi, T; Yokoo, S; Ogawa, M

    2018-02-02

    The aim of this study was to characterize the standard morphology of the oral commissure and to describe the changes after reconstruction in patients with through-and-through cheek defects involving the oral commissure. Indices for the morphological analyses of the commissure were derived from examinations of 50 normal Japanese volunteers. Ten patients with full-thickness cheek defects involving the commissure were then evaluated. All of these patients underwent free flap reconstruction with vermilion advancement flaps from the remaining vermilion. The morphology of the commissure with the mouth closed was classified based on the point of entrance of the vermilion into the oral cavity. In normal volunteers, the commissure pattern consisting of the entrance of the upper vermilion into the oral cavity before the lower vermilion and just prior to forming the oral commissure was considered to be the standard. However, in the reconstructed cases, there was an increase in the pattern in which the lower vermilion enters the oral cavity before the upper vermilion for the remaining commissure postoperatively, especially when the lower lip defects were greater than those of the upper lip. It is important to refer not only to the standard morphology of the commissure, but also to the changes according to the extent of resection and the method of reconstruction. Copyright © 2018 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

  14. Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

    Science.gov (United States)

    Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

    2017-08-12

    The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

  15. Image Quality in Children with Low-Radiation Chest CT Using Adaptive Statistical Iterative Reconstruction and Model-Based Iterative Reconstruction

    OpenAIRE

    Jihang Sun; Yun Peng; Xiaomin Duan; Tong Yu; Qifeng Zhang; Yong Liu; Di Hu

    2014-01-01

    OBJECTIVE: To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR) and a full model-based iterative reconstruction (MBIR) algorithm. METHODS: Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years) who received low-dose chest CT scans were included. Age-dependent noise index (NI) was used for acquisition. Images were retrospectively reconstructed using three me...

  16. Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi.

    Science.gov (United States)

    Vardhanabhuti, Varut; Ilyas, Sumaira; Gutteridge, Catherine; Freeman, Simon J; Roobottom, Carl A

    2013-10-01

    To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and mean attenuation values of subcutaneous fat] and subjective image parameters (image noise, image contrast, overall visibility of kidneys/ureters/bladder, visibility of small structures, and overall diagnostic confidence) were assessed using a scoring system from 1 (best) to 5 (worst). Objective image measurements revealed significantly less image noise and higher CNR and the same fat attenuation values for the MBIR technique (P ASIR and 3.08-3.31 for FBP. No significant difference was observed between FBP and ASIR (P > 0.05), while there was a significant difference between ASIR vs. MBIR (P ASIR and FBP CT KUB examinations. • There are many reconstruction options in CT. • Novel model-based iterative reconstruction (MBIR) showed the least noise and optimal image quality. • For CT of the kidneys/ureters/bladder, MBIR should be utilised, if available. • Further studies to reduce the dose while maintaining image quality should be pursued.

  17. Evaluation of image quality for different kV cone-beam CT acquisition and reconstruction methods in the head and neck region

    Energy Technology Data Exchange (ETDEWEB)

    Elstroem, Ulrik V.; Muren, Ludvig P. (Dept. of Oncology, Aarhus Univ. Hospital, Aarhus (Denmark); Dept. of Medical Physics, Aarhus Univ. Hospital, Aarhus (Denmark)), e-mail: ulrielst@rm.dk; Petersen, Joergen B. B. (Dept. of Medical Physics, Aarhus Univ. Hospital, Aarhus (Denmark)); Grau, Cai (Dept. of Oncology, Aarhus Univ. Hospital, Aarhus (Denmark))

    2011-08-15

    Purpose. To evaluate the image quality obtained in a standard QA phantom with both clinical and non-clinical cone-beam computed tomography (CBCT) acquisition modes for the head and neck (HN) region as a step towards CBCT-based treatment planning. The impact of deteriorated Hounsfield unit (HU) accuracy was investigated by comparing results from clinical CBCT image reconstructions to those obtained from a pre-clinical scatter correction algorithm. Methods. Five different CBCT acquisition modes on a clinical system for kV CBCT-guided radiotherapy were investigated. Image reconstruction was performed in both standard clinical software and with an experimental reconstruction algorithm with improved beam hardening and scatter correction. Using the Catphan 504 phantom, quantitative measures of HU uniformity, HU verification and linearity, contrast-to-noise ratio (CNR), and spatial resolution using modulation transfer function (MTF) estimation were assessed. To benchmark the CBCT image properties, comparison to standard HN protocols on conventional CT scanners was performed by similar measures. Results. The HU uniformity within a water-equivalent homogeneous region was considerably improved using experimental vs. standard reconstruction, by factors of two for partial scans and four for full scans. Similarly, the amount of capping/cupping artifact was reduced by more than 1.5%. With mode and reconstruction specific HU calibration using seven inhomogeneity inserts comparable HU linearity was observed. CNR was on average 5% higher for experimental reconstruction (scaled with the square-root of dose between modes for both reconstruction methods). Conclusions. Judged on parameters affecting the common diagnostic image properties, improved beam hardening and scatter correction diminishes the difference between CBCT and CT image quality considerably. In the pursuit of CBCT-based treatment adaptation, dedicated imaging protocols may be required

  18. An investigation of surface reconstruction from binocular disparity based on standard regularization theory: comparison between "membrane" and "thin-plate" potential energy models.

    Science.gov (United States)

    Shiraiwa, Aya; Hayashi, Takefumi

    2011-08-01

    Visible surfaces of three-dimensional objects are reconstructed from two-dimensional retinal images in the early stages of human visual processing. In the computational model of surface reconstruction based on the standard regularization theory, an energy function is minimized. Two types of model have been proposed, called "membrane" and "thin-plate" after their function formulas, in which the first or the second derivative of depth information is used. In this study, the threshold of surface reconstruction from binocular disparity was investigated using a sparse random dot stereogram, and the predictive accuracy of these models was evaluated. It was found that the thin-plate model reconstructed surfaces more accurately than the membrane model and showed good agreement with experimental results. The likelihood that these models imitate human processing of visual information is discussed in terms of the size of receptive fields in the visual pathways of the human cortex.

  19. A comparative study of three dimensional reconstructive images using computed tomograms of facial bone injuries

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Eun Suk; Koh, Kwang Joon [Dept. of Oral and Maxillofacial Radiology, College of Dentistry, Chonbuk National University, Chonju (Korea, Republic of)

    1994-08-15

    The purpose of this study was to clarify the spatial relationship in presurgical examination and to aid surgical planning and postoperative evaluation of patients with facial bone injury. For this study, three-dimensional images of facial bone fracture were reconstructed by computed image analysis system and three-dimensional reconstructive program integrated in computed tomography. The obtained results were as follows: 1. Serial conventional computed tomograms were value in accurately depicting the facial bone injuries and three-dimensional reconstructive images demonstrated an overall look. 2. The degree of deterioration of spatial resolution was proportional to the thickness of the slice. 3. Facial bone fractures were the most distinctly demonstrated on inferoanterior views of three dimensional reconstructive images. 4. Although three-dimensional reconstructive images made diagnosis of fracture lines, it was difficult to identify maxillary fractures. 5. The diagnosis of zygomatic fractures could be made equally well with computed image analysis system and three-dimensional reconstructive program integrated in computed tomography. 6. The diagnosis of mandibular fractures could be made equally well with computed image analysis system and three-dimensional reconstructive program integrated in computed tomography.

  20. Super-Resolution Reconstruction of High-Resolution Satellite ZY-3 TLC Images.

    Science.gov (United States)

    Li, Lin; Wang, Wei; Luo, Heng; Ying, Shen

    2017-05-07

    Super-resolution (SR) image reconstruction is a technique used to recover a high-resolution image using the cumulative information provided by several low-resolution images. With the help of SR techniques, satellite remotely sensed images can be combined to achieve a higher-resolution image, which is especially useful for a two- or three-line camera satellite, e.g., the ZY-3 high-resolution Three Line Camera (TLC) satellite. In this paper, we introduce the application of the SR reconstruction method, including motion estimation and the robust super-resolution technique, to ZY-3 TLC images. The results show that SR reconstruction can significantly improve both the resolution and image quality of ZY-3 TLC images.

  1. 3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine

    Science.gov (United States)

    Hamamoto, Kazuhiko; Sato, Motoyoshi

    3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.

  2. Multiple-image hiding using super resolution reconstruction in high-frequency domains

    Science.gov (United States)

    Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

    2017-12-01

    In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

  3. Improvement of the optical image reconstruction based on multiplexed quantum ghost images

    Science.gov (United States)

    Balakin, D. A.; Belinsky, A. V.; Chirkin, A. S.

    2017-08-01

    Ghost imaging allows one to obtain information on an object from the spatial correlation function between photons propagating through or reflected from the object and photons of the reference arm. In this case, detection in the object arm is performed over the entire aperture of the beam and, therefore, it does not give information on the object. The reference beam does not interact with the object, but is recorded with a scanning point detector or a CCD array permitting the measurement of the spatial correlation function of photons in two arms. The use of multimode entangled quantum light beams by illuminating the object by one beam and orienting other beams to reference arms makes it possible to obtain simultaneously several ghost images (GIs). Cross correlations of multiplexed GIs (MGIs) are determined by eighth-order field correlation functions. A special algorithm is developed for calculating higher-order correlations of Bose operators. The presence of GI cross correlations is used for improving the quality of the reconstructed object's image by their processing using the measurement reduction method. An example of the computer simulation of the image reconstruction by MGIs formed in the field of four-frequency entangled quantum states is considered. It is found that in this case the reduced GI has a signal-to-noise ratio several times higher than that of GIs.

  4. Image reconstruction method IRBis for optical/infrared long-baseline interferometry

    Science.gov (United States)

    Hofmann, Karl-Heinz; Heininger, Matthias; Schertl, Dieter; Weigelt, Gerd; Millour, Florentin; Berio, Philippe

    2016-07-01

    IRBis is an image reconstruction method for optical/infrared long-baseline interferometry. IRBis can reconstruct images from (a) measured visibilities and closure phases, or from (b) measured complex visibilities (i.e. the Fourier phases and visibilities). The applied optimization routine ASA CG is based on conjugate gradients. The method allows the user to implement different regularizers, as for example, maximum entropy, smoothness, total variation, etc., and apply residual ratios as an additional metric for goodness-of-fit. In addition, IRBis allows the user to change the following reconstruction parameters: (a) FOV of the area to be reconstructed, (b) the size of the pixel-grid used, (c) size of a binary mask in image space allowing reconstructed intensities real astronomical objects: (a) We have investigated image reconstruction experiments of MATISSE target candidates by computer simulations. We have modeled gaps in a disk of a young stellar object and have simulated interferometric data (squared visibilities and closure phases) with a signal-to-noise ratio as expected for MATISSE observations. We have performed image reconstruction experiments with this model for different flux levels of the target and different amount of observing time, that is, with different uv coverages. As expected, the quality of the reconstructions clearly depends on the flux of the source and the completeness of the uv coverage. (b) We also discuss reconstructions of the Luminous Blue Variable η Carinae obtained from AMBER observations in the high spectral resolution mode in the K band. The images were reconstruction (1) using the closure phases and (2) using the absolute phases derived from the measured wavelength-differential phases and the closure phase reconstruction in the continuum.

  5. On the Reconstruction of a Weak Phase-Amplitude Object. IV New Sampling Theorems for Object Reconstruction even for Non-Isoplanatic Imaging. I. One Dimensional Object Reconstruction

    NARCIS (Netherlands)

    Ferwerda, H.A.; Hoenders, B.J.

    1974-01-01

    New inversion procedures are derived for one-dimensional object reconstruction which use sampling values of known distributions. Whittaker-Shannon sampling is derived as a special case. The theorems apply to optical imaging with aberrations which violate the isoplanacy condition. Also a

  6. Comparative assessment of three image reconstruction techniques for image quality and radiation dose in patients undergoing abdominopelvic multidetector CT examinations

    Science.gov (United States)

    Desai, G S; Thabet, A; Elias, A Y A; Sahani, D V

    2013-01-01

    Objective To compare image quality and radiation dose of abdominal CT examinations reconstructed with three image reconstruction techniques. Methods In this Institutional Review Board-approved study, contrast-enhanced (CE) abdominopelvic CT scans from 23 patients were reconstructed using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASiR) and iterative reconstruction in image space (IRIS) and were reviewed by two blinded readers. Subjective (acceptability, sharpness, noise and artefacts) and objective (noise) measures of image quality were recorded for each image data set. Radiation doses in CT dose index (CTDI) dose–length product were also calculated for each examination type and compared. Imaging parameters were compared using the Wilcoxon signed rank test and a paired t-test. Results All 69 CECT examinations were of diagnostic quality and similar for overall acceptability (mean grade for ASiR, 3.9±0.3; p=0.2 for Readers 1 and 2; IRIS, 3.9±0.4, p=0.2; FBP, 3.8±0.9). Objective noise was considerably lower with both iterative techniques (pASiR and IRIS). Recorded mean radiation dose, i.e. CTDIvol, was 24% and 10% less with ASiR (11.4±3.4 mGy; preconstructed with ASiR and IRIS provide diagnostic images with reduced image noise and 10–24% lower radiation dose than FBP. Advances in knowledge CT images reconstructed with FBP are frequently noisy on lowering the radiation dose. Newer iterative reconstruction techniques have different approaches to produce images with less noise; ASiR and IRIS provide diagnostic abdominal CT images with reduced image noise and radiation dose compared with FBP. This has been documented in this study. PMID:23255538

  7. GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging.

    Science.gov (United States)

    Wen, Tiexiang; Li, Ling; Zhu, Qingsong; Qin, Wenjian; Gu, Jia; Yang, Feng; Xie, Yaoqin

    2017-07-01

    Volume reconstruction method plays an important role in improving reconstructed volumetric image quality for freehand three-dimensional (3D) ultrasound imaging. By utilizing the capability of programmable graphics processing unit (GPU), we can achieve a real-time incremental volume reconstruction at a speed of 25-50 frames per second (fps). After incremental reconstruction and visualization, hole-filling is performed on GPU to fill remaining empty voxels. However, traditional pixel nearest neighbor-based hole-filling fails to reconstruct volume with high image quality. On the contrary, the kernel regression provides an accurate volume reconstruction method for 3D ultrasound imaging but with the cost of heavy computational complexity. In this paper, a GPU-based fast kernel regression method is proposed for high-quality volume after the incremental reconstruction of freehand ultrasound. The experimental results show that improved image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of [Formula: see text] and kernel bandwidth of 1.0. The computational performance of the proposed GPU-based method can be over 200 times faster than that on central processing unit (CPU), and the volume with size of 50 million voxels in our experiment can be reconstructed within 10 seconds.

  8. Image quality assesment using NEMA NU 4/2008 standards in small animal PET scanner

    Energy Technology Data Exchange (ETDEWEB)

    Gontijo, Rodrigo M.G.; Ferreira, Andréa V.; Silva, Juliana B.; Mamede, Marcelo, E-mail: rodrigo.gontijo@cdtn.br, E-mail: rodrigogadelhagontijo1@hotmail.com [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)

    2017-07-01

    In Brazil, there are few micro PET in use and a quality control protocols standardization are needed to harmonize their use in the research field. Thus, the purpose of this study is to characterize the image quality performance of the micro PET scanner (Lab PET 4, GE healthcare Technologies, Waukesha, WI) using the NEMA NU 4/ 2008 standards and specific phantom. The NEMA image-quality (IQ) phantom consists of 3 different regions to analyze distinct characteristics: image noise (%SD), expressed as percentage SD in a uniform region (%SD), recovery coefficient (RC) and Spill-over (SOR) in air and water. The IQ phantom was filled with {sup 18}F-FDG calibrated at the beginning of acquisition, placed in the center of the field-of-view (FOV) and measured with the typical whole body imaging protocol. The images were reconstructed with different reconstruction methods (FBP-2D; MLEM-3D and OSEM-3D); with and without high resolution (HR) when possible. The results were compared. The LabPET 4 system produces appropriate image and with performance according to the literature. The present study is an initial step to verify the NEMA NU 4/2008 use in the Brazilian scenario for further standardization. (author)

  9. Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

    Energy Technology Data Exchange (ETDEWEB)

    Tao, Yinghua [Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Chen, Guang-Hong [Department of Medical Physics and Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States); Hacker, Timothy A.; Raval, Amish N. [Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53792 (United States); Van Lysel, Michael S.; Speidel, Michael A., E-mail: speidel@wisc.edu [Department of Medical Physics and Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53705 (United States)

    2014-07-15

    .9% for the 500 mA FBP, 25 mA SIR, and 25 mA FBP, respectively. In numerical simulations, SIR mitigated streak artifacts in the low dose data and yielded flow maps with mean error <7% and standard deviation <9% of mean, for 30×30 pixel ROIs (12.9 × 12.9 mm{sup 2}). In comparison, low dose FBP flow errors were −38% to +258%, and standard deviation was 6%–93%. Additionally, low dose SIR achieved 4.6 times improvement in flow map CNR{sup 2} per unit input dose compared to low dose FBP. Conclusions: SIR reconstruction can reduce image noise and mitigate streaking artifacts caused by photon starvation in dynamic CT myocardial perfusion data sets acquired at low dose (low tube current), and improve perfusion map quality in comparison to FBP reconstruction at the same dose.

  10. Anatomical based registration of multi-sector x-ray images for panorama reconstruction

    Science.gov (United States)

    Ben-Zikri, Yehuda Kfir; Mendez, Stacy; Linte, Cristian A.

    2017-03-01

    Accurate measurement of long limb alignment is an essential stage of the pre-operative planning of realignment surgery. This alignment is quantified according to the hip-knee-ankle (HKA) angle of the mechanical axis of the lower extremity and is measured based on a full-length weight-bearing X-ray or standard computed radiography (CR) image of the patient in standing position. Due to the limited field-of-view of the traditionally employed digital X-ray imaging systems, several sector images are required to capture the posture of a standing individual. These sector images need to then be "stitched" together to reconstruct the standing posture. To eliminate user-induced variability and time constraints associated with the traditional manual "stitching" protocol, we have created an image processing application to automate the stitching process, when there are no reliable external markers available in the images, by only relying on the most reliable anatomical content of the image. The application starts with a rough segmentation of the tibia and the sector images are then registered by evaluating the DICE coefficient between the edges of these corresponding bones along the medial edge. The identified translations are then used to register the original sector images into the standing panorama image. To test the robustness of our method, we randomly selected 40 datasets from a variant database consisting of nearly 100 patient X-ray images acquired for patient screening as part of a multi-site clinical trial. The resulting horizontal and vertical translation values from the automated registration were compared to the homologous translations recorded during the manual panorama generation conducted by a knowledgeable X-ray imaging technician. The mean and standard deviation of the differences for the horizontal translation parameters was -0:27+/-1:14 mm and 0:31+/-1:86 mm for the left and right tibia, respectively. The vertical translation differences for the left and

  11. Paediatric cardiac CT examinations: impact of the iterative reconstruction method ASIR on image quality--preliminary findings.

    Science.gov (United States)

    Miéville, Frédéric A; Gudinchet, François; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Bochud, François O; Verdun, Francis R

    2011-09-01

    Radiation dose exposure is of particular concern in children due to the possible harmful effects of ionizing radiation. The adaptive statistical iterative reconstruction (ASIR) method is a promising new technique that reduces image noise and produces better overall image quality compared with routine-dose contrast-enhanced methods. To assess the benefits of ASIR on the diagnostic image quality in paediatric cardiac CT examinations. Four paediatric radiologists based at two major hospitals evaluated ten low-dose paediatric cardiac examinations (80 kVp, CTDI(vol) 4.8-7.9 mGy, DLP 37.1-178.9 mGy·cm). The average age of the cohort studied was 2.6 years (range 1 day to 7 years). Acquisitions were performed on a 64-MDCT scanner. All images were reconstructed at various ASIR percentages (0-100%). For each examination, radiologists scored 19 anatomical structures using the relative visual grading analysis method. To estimate the potential for dose reduction, acquisitions were also performed on a Catphan phantom and a paediatric phantom. The best image quality for all clinical images was obtained with 20% and 40% ASIR (p ASIR above 50%, image quality significantly decreased (p ASIR, a strong noise-free appearance of the structures reduced image conspicuity. A potential for dose reduction of about 36% is predicted for a 2- to 3-year-old child when using 40% ASIR rather than the standard filtered back-projection method. Reconstruction including 20% to 40% ASIR slightly improved the conspicuity of various paediatric cardiac structures in newborns and children with respect to conventional reconstruction (filtered back-projection) alone.

  12. Whole-body CT for lymphoma staging: Feasibility of halving radiation dose and risk by iterative image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Meyer, M., E-mail: mathias.meyer@medma.uni-heidelberg.de [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Klein, S.A., E-mail: stefan.klein@umm.de [Department of Hematology and Oncology, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Brix, G., E-mail: gbrix@bfs.de [Department of Medical and Occupational Radiation Protection, Federal Office for Radiation Protection, Ingolstädter Landstraße 1, D-85764 Neuherberg (Germany); Fink, C., E-mail: Christian.Fink@medma.uni-heidelberg.de [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Pilz, L., E-mail: lothar.pilz@medma.uni-heidelberg.de [Department of Biostatistics, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Jafarov, H., E-mail: Hashim.Jafarov@umm.de [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Hofmann, W.K., E-mail: w.k.hofmann@umm.de [Department of Hematology and Oncology, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoenberg, S.O., E-mail: Stefan.Schoenberg@umm.de [Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); and others

    2014-02-15

    Objectives: Patients with lymphoma are at higher-risk of secondary malignancies mainly due to effects of cancer therapy as well as frequent radiological surveillance. We thus aimed to investigate the objective and subjective image quality as well as radiation exposure and risk of full-dose standard (FDS), full-dose iterative (FDI), and half-dose iterative (HDI) image reconstruction in patients with lymphoma. Material and methods: In 100 lymphoma patients, contrast-enhanced whole-body staging was performed on a dual-source CT. To acquire full-dose and half-dose CT data simultaneously, the total current-time product was equally distributed on both tubes operating at 120 kV. HDI reconstructions were calculated by using only data from one tube. Quantitative image quality was assessed by measuring image noise in different tissues of the neck, thorax, and abdomen. Overall diagnostic image quality was assessed using a 5-point Likert scale. Radiation doses and risks were estimated for a male and female reference person. Results: For all anatomical regions apart from the lungs image noise was significantly lower and the overall subjective image quality significantly better when using FDI and HDI instead of FDS reconstruction (p < 0.05). For the half-dose protocol, the risk to develop a radiation-induced cancer was estimated to be less than 0.11/0.19% for an adult male/female. Conclusions: Image quality of FDI and more importantly of HDI is superior to FDS reconstruction, thus enabling to halve radiation dose and risk to lymphoma patients.

  13. Accurate image reconstruction in CT from projection data taken at few-views

    Science.gov (United States)

    Sidky, Emil Y.; Kao, Chien-Min; Pan, Xiaochuan

    2006-03-01

    Image reconstruction from few-view CT is of interest because of the potential to reduce scanning time and radiation dose. The challenge of few-view CT for image reconstruction is essentially a problem of interpolation from under-sampled data. Recently, a new algorithm for inverting the Fourier transform from under-sampled data has been developed by Candes et al. IEEE Trans. Inf. Theory , 52 489 (2006). This algorithm can be directly applied to image reconstruction in 2D parallel-beam CT because of the central slice theorem. This article presents a discussion of the new algorithm, showing examples for different degrees of under-sampling.

  14. Incorporation of local dependent reliability information into the Prior Image Constrained Compressed Sensing (PICCS) reconstruction algorithm

    Energy Technology Data Exchange (ETDEWEB)

    Vaegler, Sven; Sauer, Otto [Wuerzburg Univ. (Germany). Dept. of Radiation Oncology; Stsepankou, Dzmitry; Hesser, Juergen [University Medical Center Mannheim, Mannheim (Germany). Dept. of Experimental Radiation Oncology

    2015-07-01

    The reduction of dose in cone beam computer tomography (CBCT) arises from the decrease of the tube current for each projection as well as from the reduction of the number of projections. In order to maintain good image quality, sophisticated image reconstruction techniques are required. The Prior Image Constrained Compressed Sensing (PICCS) incorporates prior images into the reconstruction algorithm and outperforms the widespread used Feldkamp-Davis-Kress-algorithm (FDK) when the number of projections is reduced. However, prior images that contain major variations are not appropriately considered so far in PICCS. We therefore propose the partial-PICCS (pPICCS) algorithm. This framework is a problem-specific extension of PICCS and enables the incorporation of the reliability of the prior images additionally. We assumed that the prior images are composed of areas with large and small deviations. Accordingly, a weighting matrix considered the assigned areas in the objective function. We applied our algorithm to the problem of image reconstruction from few views by simulations with a computer phantom as well as on clinical CBCT projections from a head-and-neck case. All prior images contained large local variations. The reconstructed images were compared to the reconstruction results by the FDK-algorithm, by Compressed Sensing (CS) and by PICCS. To show the gain of image quality we compared image details with the reference image and used quantitative metrics (root-mean-square error (RMSE), contrast-to-noise-ratio (CNR)). The pPICCS reconstruction framework yield images with substantially improved quality even when the number of projections was very small. The images contained less streaking, blurring and inaccurately reconstructed structures compared to the images reconstructed by FDK, CS and conventional PICCS. The increased image quality is also reflected in large RMSE differences. We proposed a modification of the original PICCS algorithm. The pPICCS algorithm

  15. Registration-based regional lung mechanical analysis: retrospectively reconstructed dynamic imaging versus static breath-hold image acquisition

    Science.gov (United States)

    Ding, Kai; Cao, Kunlin; Christensen, Gary E.; Hoffman, Eric A.; Reinhardt, Joseph M.

    2009-02-01

    The lungs undergo expansion and contraction during the respiratory cycle. Since many disease or injury conditions are associated with the biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung ventilation and regional mechanical changes. We describe a technique that uses multiple respiratory-gated CT images and non-rigid 3D image registration to make local estimates of lung tissue expansion. The degree of regional lung expansion is measured using the Jacobian (a function of local partial derivatives) of the registration displacement field. We compare the ventral-dorsal patterns of lung expansion estimated in both retrospectively reconstructed dynamic scans and static breath-hold scans to a xenon CT based measure of specific ventilation and a semi-automatic reference standard in four anesthetized sheep studied in the supine orientation. The regional lung expansion estimated by 3D image registration of images acquired at 50% and 75% phase points of the inspiratory portion of the respiratory cycle and 20 cm H2O and 25 cm H2O airway pressures gave the best match between the average Jacobian and the xenon CT specific ventilation respectively (linear regression, average r2 = 0.85 and r2 = 0.84). The registration accuracy assessed by 200 semi-automatically matched landmarks in both the dynamic and static scans show landmark error on the order of 2 mm.

  16. Image-Based 3d Reconstruction and Analysis for Orthodontia

    Science.gov (United States)

    Knyaz, V. A.

    2012-08-01

    Among the main tasks of orthodontia are analysis of teeth arches and treatment planning for providing correct position for every tooth. The treatment plan is based on measurement of teeth parameters and designing perfect teeth arch curve which teeth are to create after treatment. The most common technique for teeth moving uses standard brackets which put on teeth and a wire of given shape which is clamped by these brackets for producing necessary forces to every tooth for moving it in given direction. The disadvantages of standard bracket technique are low accuracy of tooth dimensions measurements and problems with applying standard approach for wide variety of complex orthodontic cases. The image-based technique for orthodontic planning, treatment and documenting aimed at overcoming these disadvantages is proposed. The proposed approach provides performing accurate measurements of teeth parameters needed for adequate planning, designing correct teeth position and monitoring treatment process. The developed technique applies photogrammetric means for teeth arch 3D model generation, brackets position determination and teeth shifting analysis.

  17. Automatic magnification determination of electron cryomicroscopy images using apoferritin as a standard.

    Science.gov (United States)

    Wasilewski, Sebastian; Karelina, Darya; Berriman, John A; Rosenthal, Peter B

    2012-10-01

    Interpretation of the structural information in cryomicroscopy images recorded on film or CCD camera requires a precise knowledge of the electron microscope parameters that affect image features such as magnification and defocus. Magnification must be determined in order to combine data from different images in a three-dimensional reconstruction and to accurately scale reconstructions for fitting with atomic resolution models. A method is described for estimating the absolute magnification of an electron micrograph of a frozen-hydrated specimen using horse spleen apoferritin as a standard. Apoferritin is a widely available protein complex of known structure that may be included with the specimen of interest and imaged under conditions identical to those used for imaging other biological specimens by cryomicroscopy. The sum of the structure factor intensities of images of randomly-oriented apoferritin particles shows three low resolution peaks to 25Å that arise from the hollow ball structure of apoferritin. Comparison of peak positions of the experimental intensities with structure factor intensities of an atomic model of apoferritin determined by X-ray crystallography provides a scale factor for estimating the absolute magnification of the micrograph. We compare the magnification estimate using apoferritin to that obtained with tobacco mosaic virus, another common magnification standard for cryomicroscopy. We verify the precision of the method by acquiring images with a systematic variation of magnification. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. Parallel Algorithm for Reconstruction of TAC Images; Algoritmo Paralelo de Reconstruccion de Imagenes TAC

    Energy Technology Data Exchange (ETDEWEB)

    Vidal Gimeno, V.

    2012-07-01

    The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.

  19. Investigation of Iterative Image Reconstruction in Low-dose Breast CT

    Science.gov (United States)

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

    2014-01-01

    Interest exists in developing computed tomography (CT) dedicated for breast-cancer imaging. Because breast tissues are radiation-sensitive, the total radiation exposure in a breast-CT scan is kept low, often comparable to a typical two-view mammography exam, thus resulting in a challenging low-dose-data-reconstruction problem. In recent years, evidence exists suggesting that iterative reconstruction may yield images of improved quality from low-dose data. In this work, based upon the constrained image-total-variation (TV) minimization program and its numerical solver, i.e., the adaptive steepest descent-projection onto the convex set (ASD-POCS), we investigate and evaluate iterative image reconstructions from low-dose breast-CT data of patients, with focuses on identifying and determining key reconstruction parameters, devising surrogate utility metrics for characterizing reconstruction quality, and tailoring the program and ASD-POCS to the specific reconstruction task under consideration. The ASD-POCS reconstructions appear to outperform the corresponding clinical FDK reconstructions, in terms of subjective visualization and surrogate utility metrics. PMID:24786683

  20. Accelerated gradient methods for total-variation-based CT image reconstruction

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Heide; Jensen, Tobias Lindstrøm; Hansen, Per Christian

    2011-01-01

    reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton’s method. The simple gradient method has much lower memory requirements, but exhibits slow convergence...

  1. The quality of three-dimensional images reconstructed with volume-scan CT

    Energy Technology Data Exchange (ETDEWEB)

    Shimbashi, Takeshi; Sakurai, Nobuaki; Watanabe, Norimitsu (Jikei Univ., Tokyo (Japan). School of Medicine); Takagi, Hiroshi; Takeuchi, Yutaka

    1993-05-01

    Volume-scan CT is based on slip-ring technology which leads to continuous scanning. It permits remarkable reduction in scanning time, which is especially meaningful where children and elderly patients are concerned. One scan takes one second, with a maximum continuous time of 50 seconds. Slice widths of 2, 3, 5 and 100 mm can be selected and table changed from 1.5 to 20 mm/second. The reconstruction index is 1 to 10 mm, and reconstruction time about 10 seconds. As both the patient and table are moved simultaneously, it is possible to scan a wide area in a short time. Volume-scan CT is suitable for three-dimensional (3-D) images because of the good continuity of slices. The authors reconstructed 3-D phantom images using both ordinary CT and volume-scan CT, and then compared the quality of these images. Under the condition of 3 mm slice width and 3 mm/sec table speed, the 3-D images reconstructed with volume-scan CT were clearly better than those reconstructed using ordinary CT. The quality of both has improved after interpolation. In particular, the periorbital and zygomatic areas of 3-D images reconstructed with volume-scan CT are quite natural. When a phantom was scanned under the condition of 10 mm slice width and 10 mm/sec table speed, the quality of 3-D image reconstructed with ordinary CT was not sufficient to be distinct. Even under interpolation, the quality of image was not natural. Useful images could not be obtained when the phantom was moving. It was found that volume-scan CT is suitable for reconstruction of 3-D images. (author).

  2. Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional computed tomography in a porcine model.

    Science.gov (United States)

    Thürk, Florian; Boehme, Stefan; Mudrak, Daniel; Kampusch, Stefan; Wielandner, Alice; Prosch, Helmut; Braun, Christina; Toemboel, Frédéric P R; Hofmanninger, Johannes; Kaniusas, Eugenijus

    2017-01-01

    Electrical impedance tomography (EIT) is a promising imaging technique for bedside monitoring of lung function. It is easily applicable, cheap and requires no ionizing radiation, but clinical interpretation of EIT-images is still not standardized. One of the reasons for this is the ill-posed nature of EIT, allowing a range of possible images to be produced-rather than a single explicit solution. Thus, to further advance the EIT technology for clinical application, thorough examinations of EIT-image reconstruction settings-i.e., mathematical parameters and addition of a priori (e.g., anatomical) information-is essential. In the present work, regional ventilation distribution profiles derived from different EIT finite-element reconstruction models and settings (for GREIT and Gauss Newton) were compared to regional aeration profiles assessed by the gold-standard of 4-dimensional computed tomography (4DCT) by calculating the root mean squared error (RMSE). Specifically, non-individualized reconstruction models (based on circular and averaged thoracic contours) and individualized reconstruction models (based on true thoracic contours) were compared. Our results suggest that GREIT with noise figure of 0.15 and non-uniform background works best for the assessment of regional ventilation distribution by EIT, as verified versus 4DCT. Furthermore, the RMSE of anteroposterior ventilation profiles decreased from 2.53±0.62% to 1.67±0.49% while correlation increased from 0.77 to 0.89 after embedding anatomical information into the reconstruction models. In conclusion, the present work reveals that anatomically enhanced EIT-image reconstruction is superior to non-individualized reconstruction models, but further investigations in humans, so as to standardize reconstruction settings, is warranted.

  3. Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional computed tomography in a porcine model.

    Directory of Open Access Journals (Sweden)

    Florian Thürk

    Full Text Available Electrical impedance tomography (EIT is a promising imaging technique for bedside monitoring of lung function. It is easily applicable, cheap and requires no ionizing radiation, but clinical interpretation of EIT-images is still not standardized. One of the reasons for this is the ill-posed nature of EIT, allowing a range of possible images to be produced-rather than a single explicit solution. Thus, to further advance the EIT technology for clinical application, thorough examinations of EIT-image reconstruction settings-i.e., mathematical parameters and addition of a priori (e.g., anatomical information-is essential. In the present work, regional ventilation distribution profiles derived from different EIT finite-element reconstruction models and settings (for GREIT and Gauss Newton were compared to regional aeration profiles assessed by the gold-standard of 4-dimensional computed tomography (4DCT by calculating the root mean squared error (RMSE. Specifically, non-individualized reconstruction models (based on circular and averaged thoracic contours and individualized reconstruction models (based on true thoracic contours were compared. Our results suggest that GREIT with noise figure of 0.15 and non-uniform background works best for the assessment of regional ventilation distribution by EIT, as verified versus 4DCT. Furthermore, the RMSE of anteroposterior ventilation profiles decreased from 2.53±0.62% to 1.67±0.49% while correlation increased from 0.77 to 0.89 after embedding anatomical information into the reconstruction models. In conclusion, the present work reveals that anatomically enhanced EIT-image reconstruction is superior to non-individualized reconstruction models, but further investigations in humans, so as to standardize reconstruction settings, is warranted.

  4. Suppression of zero order diffraction from the reconstructed images in digital holography

    Directory of Open Access Journals (Sweden)

    M R Rashidian Vaziri

    2016-02-01

    Full Text Available The numerically reconstructed images in digital holography contain two undesirable features. After reconstruction, the zero order diffraction as well as the complex conjugate image will be present in pictures and drastically reduce their qualities. Practical applications of digital holography in the context of characterization and measuring the physical properties of objects require the suppression of these two features, before starting the reconstruction phase. In this work, using the required mathematical functions for suppressing the zero order diffraction and by transforming them to their discrete form, numerical filters for passing over the CCD images have been constructed. After passing these filters over the experimentally recorded CCD images, the reconstruction phase has been completed applying the discrete Fresnel transform. Carefully investigating the quality of various reconstructed images, we came to the conclusion that if a filter covers a smaller neighborhood of the recorded CCD images, it will have a better performance in suppressing the zero order diffraction. Among the used filters in this work, a 3×3 average filter showed the best performance in suppressing the zero order diffraction from the reconstructed images.

  5. Monte Carlo SURE-based parameter selection for parallel magnetic resonance imaging reconstruction.

    Science.gov (United States)

    Weller, Daniel S; Ramani, Sathish; Nielsen, Jon-Fredrik; Fessler, Jeffrey A

    2014-05-01

    Regularizing parallel magnetic resonance imaging (MRI) reconstruction significantly improves image quality but requires tuning parameter selection. We propose a Monte Carlo method for automatic parameter selection based on Stein's unbiased risk estimate that minimizes the multichannel k-space mean squared error (MSE). We automatically tune parameters for image reconstruction methods that preserve the undersampled acquired data, which cannot be accomplished using existing techniques. We derive a weighted MSE criterion appropriate for data-preserving regularized parallel imaging reconstruction and the corresponding weighted Stein's unbiased risk estimate. We describe a Monte Carlo approximation of the weighted Stein's unbiased risk estimate that uses two evaluations of the reconstruction method per candidate parameter value. We reconstruct images using the denoising sparse images from GRAPPA using the nullspace method (DESIGN) and L1 iterative self-consistent parallel imaging (L1 -SPIRiT). We validate Monte Carlo Stein's unbiased risk estimate against the weighted MSE. We select the regularization parameter using these methods for various noise levels and undersampling factors and compare the results to those using MSE-optimal parameters. Our method selects nearly MSE-optimal regularization parameters for both DESIGN and L1 -SPIRiT over a range of noise levels and undersampling factors. The proposed method automatically provides nearly MSE-optimal choices of regularization parameters for data-preserving nonlinear parallel MRI reconstruction methods. Copyright © 2013 Wiley Periodicals, Inc.

  6. Magni: A Python Package for Compressive Sampling and Reconstruction of Atomic Force Microscopy Images

    DEFF Research Database (Denmark)

    Oxvig, Christian Schou; Pedersen, Patrick Steffen; Arildsen, Thomas

    2014-01-01

    Magni is an open source Python package that embraces compressed sensing and Atomic Force Microscopy (AFM) imaging techniques. It provides AFM-specific functionality for undersampling and reconstructing images from AFM equipment and thereby accelerating the acquisition of AFM images. Magni also...

  7. Skeletal camera network embedded structure-from-motion for 3D scene reconstruction from UAV images.

    NARCIS (Netherlands)

    Xu, Z.; Wu, L.; Gerke, M.; Wang, R.; Yang, H.

    2016-01-01

    Structure-from-Motion (SfM) techniques have been widely used for 3D scene reconstruction from multi-view images. However, due to the large computational costs of SfM methods there is a major challenge in processing highly overlapping images, e.g. images from unmanned aerial vehicles (UAV). This

  8. A comparison of reconstruction methods for undersampled atomic force microscopy images

    Science.gov (United States)

    Luo, Yufan; Andersson, Sean B.

    2015-12-01

    Non-raster scanning and undersampling of atomic force microscopy (AFM) images is a technique for improving imaging rate and reducing the amount of tip-sample interaction needed to produce an image. Generation of the final image can be done using a variety of image processing techniques based on interpolation or optimization. The choice of reconstruction method has a large impact on the quality of the recovered image and the proper choice depends on the sample under study. In this work we compare interpolation through the use of inpainting algorithms with reconstruction based on optimization through the use of the basis pursuit algorithm commonly used for signal recovery in compressive sensing. Using four different sampling patterns found in non-raster AFM, namely row subsampling, spiral scanning, Lissajous scanning, and random scanning, we subsample data from existing images and compare reconstruction performance against the original image. The results illustrate that inpainting generally produces superior results when the image contains primarily low frequency content while basis pursuit is better when the images have mixed, but sparse, frequency content. Using support vector machines, we then classify images based on their frequency content and sparsity and, from this classification, develop a fast decision strategy to select a reconstruction algorithm to be used on subsampled data. The performance of the classification and decision test are demonstrated on test AFM images.

  9. Z-Index Parameterization for Volumetric CT Image Reconstruction via 3-D Dictionary Learning.

    Science.gov (United States)

    Bai, Ti; Yan, Hao; Jia, Xun; Jiang, Steve; Wang, Ge; Mou, Xuanqin

    2017-12-01

    Despite the rapid developments of X-ray cone-beam CT (CBCT), image noise still remains a major issue for the low dose CBCT. To suppress the noise effectively while retain the structures well for low dose CBCT image, in this paper, a sparse constraint based on the 3-D dictionary is incorporated into a regularized iterative reconstruction framework, defining the 3-D dictionary learning (3-DDL) method. In addition, by analyzing the sparsity level curve associated with different regularization parameters, a new adaptive parameter selection strategy is proposed to facilitate our 3-DDL method. To justify the proposed method, we first analyze the distributions of the representation coefficients associated with the 3-D dictionary and the conventional 2-D dictionary to compare their efficiencies in representing volumetric images. Then, multiple real data experiments are conducted for performance validation. Based on these results, we found: 1) the 3-D dictionary-based sparse coefficients have three orders narrower Laplacian distribution compared with the 2-D dictionary, suggesting the higher representation efficiencies of the 3-D dictionary; 2) the sparsity level curve demonstrates a clear Z-shape, and hence referred to as Z-curve, in this paper; 3) the parameter associated with the maximum curvature point of the Z-curve suggests a nice parameter choice, which could be adaptively located with the proposed Z-index parameterization (ZIP) method; 4) the proposed 3-DDL algorithm equipped with the ZIP method could deliver reconstructions with the lowest root mean squared errors and the highest structural similarity index compared with the competing methods; 5) similar noise performance as the regular dose FDK reconstruction regarding the standard deviation metric could be achieved with the proposed method using (1/2)/(1/4)/(1/8) dose level projections. The contrast-noise ratio is improved by ~2.5/3.5 times with respect to two different cases under the (1/8) dose level compared

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

    Science.gov (United States)

    Li, Liang; Wang, Bigong; Wang, Ge

    2016-01-01

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

  11. A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data.

    Science.gov (United States)

    Luo, Jianhua; Mou, Zhiying; Qin, Binjie; Li, Wanqing; Ogunbona, Philip; Robini, Marc C; Zhu, Yuemin

    2017-12-09

    Reconstructing magnetic resonance images from undersampled k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from undersampled k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from undersampled k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the undersampling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the undersampled k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.

  12. Imaging of limb salvage surgery and pelvic reconstruction following resection of malignant bone tumours

    Energy Technology Data Exchange (ETDEWEB)

    Tan, Tien Jin, E-mail: tien_jin_tan@cgh.com.sg [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Aljefri, Ahmad M. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada); Clarkson, Paul W.; Masri, Bassam A. [Department of Orthopaedics, University of British Columbia, Vancouver, BC (Canada); Ouellette, Hugue A.; Munk, Peter L.; Mallinson, Paul I. [Department of Radiology, Vancouver General Hospital, Vancouver, BC (Canada)

    2015-09-15

    Highlights: • Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. • The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. • This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases. • By being aware of the various types of reconstructive techniques used in limb salvage surgery as well as the potential complications, the reporting radiologist should possess greater confidence in making an accurate assessment of the expected post-operative imaging findings in the management of such cases. - Abstract: Advances in reconstructive orthopaedic techniques now allow for limb salvage and prosthetic reconstruction procedures to be performed on patients who would otherwise be required to undergo debilitating limb amputations for malignant bone tumours. The resulting post-operative imaging of such cases can be daunting for the radiologist to interpret, particularly in the presence of distorted anatomy and unfamiliar hardware. This article reviews the indications for limb salvage surgery, prosthetic reconstruction devices involved, expected post-operative imaging findings, as well as the potential hardware related complications that may be encountered in the management of such cases.

  13. Genetic algorithms applied to reconstructing coded imaging of neutrons and analysis of residual watermark.

    Science.gov (United States)

    Zhang, Tiankui; Hu, Huasi; Jia, Qinggang; Zhang, Fengna; Chen, Da; Li, Zhenghong; Wu, Yuelei; Liu, Zhihua; Hu, Guang; Guo, Wei

    2012-11-01

    Monte-Carlo simulation of neutron coded imaging based on encoding aperture for Z-pinch of large field-of-view with 5 mm radius has been investigated, and then the coded image has been obtained. Reconstruction method of source image based on genetic algorithms (GA) has been established. "Residual watermark," which emerges unavoidably in reconstructed image, while the peak normalization is employed in GA fitness calculation because of its statistical fluctuation amplification, has been discovered and studied. Residual watermark is primarily related to the shape and other parameters of the encoding aperture cross section. The properties and essential causes of the residual watermark were analyzed, while the identification on equivalent radius of aperture was provided. By using the equivalent radius, the reconstruction can also be accomplished without knowing the point spread function (PSF) of actual aperture. The reconstruction result is close to that by using PSF of the actual aperture.

  14. Clinical impact of model-based type iterative reconstruction with fast reconstruction time on image quality of low-dose screening chest CT.

    Science.gov (United States)

    Yuki, Hideaki; Oda, Seitaro; Utsunomiya, Daisuke; Funama, Yoshinori; Kidoh, Masafumi; Namimoto, Tomohiro; Katahira, Kazuhiro; Honda, Keiichi; Tokuyasu, Shinichi; Yamashita, Yasuyuki

    2016-03-01

    Model-based type iterative reconstruction algorithms with fast reconstruction times are now available. The clinical feasibility of their reconstruction has not been evaluated adequately. To investigate the effects of model-based type iterative reconstruction, i.e. iterative model reconstruction (IMR), with fast reconstruction time on the qualitative and quantitative image quality at low-dose chest computed tomography (CT). Thirty-one patients undergoing low-dose screening chest CT were enrolled. Images were reconstructed using filtered back projection (FBP), hybrid iterative reconstruction (HIR), and IMR algorithms. The CT attenuation and image noise for all reconstructions were calculated at the lung apex, middle, and base. Using a 4-point scale, two reviewers visually evaluated the image quality with respect to vessel sharpness, streak artifact, the mediastinum, and the overall image quality of each reconstruction method. The mean estimated effective dose was 1.0 ± 0.3 mSv. There was no significant difference in the CT attenuation among the three reconstructions. The mean image noise of FBP, HIR, and IMR images was 124.3 ± 57.3, 34.8 ± 10.2, and 22.9 ± 5.8 HU, respectively. There were significant differences for all comparison combinations among the three methods (P reconstruction time for IMR was within 3 min in all cases. At low-dose chest CT, IMR can improve the qualitative and quantitative visualization of both lung and mediastinal structures especially in the lung apex at a clinically acceptable reconstruction time. Its application may improve diagnostic performance. © The Foundation Acta Radiologica 2015.

  15. Fat-constrained 18F-FDG PET reconstruction in hybrid PET/MR imaging.

    Science.gov (United States)

    Prevrhal, Sven; Heinzer, Susanne; Wülker, Christian; Renisch, Steffen; Ratib, Osman; Börnert, Peter

    2014-10-01

    Fusion of information from PET and MR imaging can increase the diagnostic value of both modalities. This work sought to improve (18)F FDG PET image quality by using MR Dixon fat-constrained images to constrain PET image reconstruction to low-fat regions, with the working hypothesis that fatty tissue metabolism is low in glucose consumption. A novel constrained PET reconstruction algorithm was implemented via a modification of the system matrix in list-mode time-of-flight ordered-subsets expectation maximization reconstruction, similar to the way time-of-flight weighting is incorporated. To demonstrate its use in PET/MR imaging, we modeled a constraint based on fat/water-separating Dixon MR images that shift activity away from regions of fat tissue during PET image reconstruction. PET and MR imaging scans of a modified National Electrical Manufacturers Association/International Electrotechnical Commission body phantom simulating body fat/water composition and in vivo experiments on 2 oncology patients were performed on a commercial time-of-flight PET/MR imaging system. Fat-constrained PET reconstruction visibly and quantitatively increased resolution and contrast between high-uptake and fatty-tissue regions without significantly affecting the images in nonfat regions. The incorporation of MR tissue information, such as fat, in image reconstruction can improve the quality of PET images. The combination of a variety of potential other MR tissue characteristics with PET represents a further justification for merging MR data with PET data in hybrid systems. © 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  16. Pictorial essay of ultrasound-reconstructed coronal plane images of the uterus in different uterine pathologies.

    Science.gov (United States)

    Grigore, Mihaela; Grigore, Anamaria; Gafitanu, Dumitru; Furnica, Cristina

    2017-12-11

    Imaging in the major planes (horizontal, coronal, and sagittal) of the uterus is important for determining anatomy and allowing the findings to be standardized, and for evaluating and diagnosing different pathological conditions in clinical practice. Examination of the coronal plane is an important step in identifying uterine pathologies and their relationships to the endometrial canal. Three-dimensional (3D) ultrasound reveals the normal anatomy better and improves the depiction of abnormal anatomy, as the coronal plane of the uterus can easily be obtained using 3D reconstruction techniques. Our pictorial essay demonstrates that adding 3D ultrasound to a routine gynecological workup can be beneficial for clinicians, enabling a precise diagnosis to be made. In addition, the volumes obtained and stored by 3D ultrasound can allow students or residents to become more familiar with normal and abnormal pelvic structures. Clin. Anat, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  17. CT for evaluation of urolithiasis: image quality of ultralow-dose (Sub mSv) CT with knowledge-based iterative reconstruction and diagnostic performance of low-dose CT with statistical iterative reconstruction.

    Science.gov (United States)

    Hur, Joonho; Park, Sung Bin; Lee, Jong Beum; Park, Hyun Jeong; Chang, In Ho; Kwon, Jong Kyou; Kim, Yang Soo

    2015-10-01

    To compare radiation dose and image quality in regular, low, and ultralow-dose CT protocols, and to evaluate diagnostic performance of low-dose CT for urolithiasis. Sixty-five patients with suspected urolithiasis underwent three different scans under the regular, low, and ultralow-dose protocols. The regular dose scans were reconstructed using filtered back projection and the low-dose scans were reconstructed using a statistical iterative reconstruction. The ultralow-dose scans were reconstructed using both techniques in addition to a knowledge-based IR. Effective radiation doses were compared. Objective image noise was assessed by measuring standard deviation of HU and subjective image assessment was performed with a 3- or 5-point scale. Diagnostic performance of the low-dose image was evaluated, using the regular dose image as a standard reference and the interobserver agreement between two reviewers with different levels of experience was calculated. The effective radiation dose was significantly different in each protocol (p iterative reconstruction algorithm showed poorer subjective image quality than the regular and low-dose protocols, but it also had the least objective image noise. Overall, the low-dose image set showed a greater than 84% concordance rate and 100% in ureter stones larger than 3 mm. Interobserver agreement was substantial (kappa value = 0.61). The knowledge-based IR can provide a better quality image while reducing radiation exposure under the same protocol. Furthermore, the diagnostic performance of the low-dose CT protocol is comparable to the regular dose scan.

  18. Prospective Randomized Trial on Radiation Dose Estimates of CT Angiography Applying Iterative Image Reconstruction: The PROTECTION V Study.

    Science.gov (United States)

    Deseive, Simon; Chen, Marcus Y; Korosoglou, Grigorios; Leipsic, Jonathon; Martuscelli, Eugenio; Carrascosa, Patricia; Mirsadraee, Saeed; White, Charles; Hadamitzky, Martin; Martinoff, Stefan; Menges, Anna-Leonie; Bischoff, Bernhard; Massberg, Steffen; Hausleiter, Jörg

    2015-08-01

    The purpose of this study was to assess the potential of iterative image reconstruction (IR) of images for radiation dose reduction in coronary computed tomography angiography (CTA). Therefore, IR in combination with 30% tube current reduction was compared with standard scanning with filtered back projection (FBP) reconstruction. Lately, new IR techniques with advanced raw data processing have been introduced by different computed tomography vendors, thus allowing for either image noise reduction at unchanged radiation dose levels or radiation dose reductions at comparable image noise levels. In this prospective, multicenter, multivendor noninferiority trial, we randomized 400 consecutive patients to 1 of 2 groups: a control group using standard FBP image reconstruction and standard tube current or an interventional group using IR technique and 30% tube current reduction. The primary endpoint was to demonstrate noninferiority in image quality (IQ) in the IR group. IQ was assessed on a 4-point scale (1, nondiagnostic IQ; 4, excellent IQ). Secondary endpoints included total radiation dose estimates and the rate of downstream testing during 30-day follow-up. Median IQ in the IR group was noninferior compared with the conventional FBP group (IR, 3.5 [interquartile range: 3.0 to 4.0]; FBP, 3.4 [interquartile range: 2.8 to 4.0], p for noninferiority <0.016). The radiation exposure was significantly lower in the IR group (median dose-length-product 157 [interquartile range: 114 to 239] mGy·cm vs. 222 [interquartile range: 141 to 319] mGy·cm for IR vs. FBP, respectively, p < 0.0001). The rate of downstream testing did not differ significantly (7.7% vs. 7.9% for IR vs. FBP, respectively, p = 0.94). Coronary CTA image quality is maintained with the combined use of a 30% reduced tube current and IR algorithms when compared with conventional FBP image reconstruction techniques and standard tube current. (Prospective Randomized Trial On RadiaTion Dose Estimates Of CT Ang

  19. Comparative analysis of iterative reconstruction algorithms with resolution recovery and new solid state cameras dedicated to myocardial perfusion imaging.

    Science.gov (United States)

    Brambilla, Marco; Lecchi, Michela; Matheoud, Roberta; Leva, Lucia; Lucignani, Giovanni; Marcassa, Claudio; Zoccarato, Orazio

    2017-09-01

    New technologies are available in myocardial perfusion imaging. They include new software that recovers image resolution and limits image noise, multifocal collimators and dedicated cardiac cameras in which solid-state detectors are used and all available detectors are constrained to imaging just the cardiac field of view. These innovations resulted in shortened study times or reduced administered activity to patients, while preserving image quality. Many single center and some multicenter studies have been published during the introduction of these innovations in the clinical practice. Most of these studies were lead in the framework of "agreement studies" between different methods of clinical measurement. They aimed to demonstrate that these new software/hardware solutions allow the acquisition of images with reduced acquisition time or administered activity with comparable results (as for image quality, image interpretation, perfusion defect quantification, left ventricular volumes and ejection fraction) to the standard-time or standard-dose SPECT acquired with a conventional gamma camera and reconstructed with the traditional FBP method, considered as the gold standard. The purpose of this review is to provide the reader with a comprehensive understanding of the pro and cons of the different approaches summarizing the achievements reached so far and the issues that need further investigations. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  20. Attenuation-based automatic kilovoltage selection and sonogram-affirmed iterative reconstruction: Effects on radiation exposure and image quality of portal-phase liver CT

    Energy Technology Data Exchange (ETDEWEB)

    Song, Ji Soo; Choi, Eun Jung; Kim, Eun Young; Kwak, Hyo Sung; Han, Young Min [Dept. of Radiology, Chonbuk National University Medical School and Hospital, Biomedical Research Institute of Chonbuk National University Hospital, Jeonju (Korea, Republic of)

    2015-02-15

    To compare the radiation dose and image quality between standard-dose CT and a low-dose CT obtained with the combined use of an attenuation-based automatic kilovoltage (kV) selection tool (CARE kV) and sonogram-affirmed iterative reconstruction (SAFIRE) for contrast-enhanced CT examination of the liver. We retrospectively reviewed 67 patients with chronic liver disease in whom both, standard-dose CT with 64-slice multidetector-row CT (MDCT) (protocol A), and low-dose CT with 128-slice MDCT using CARE kV and SAFIRE (protocol B) were performed. Images from protocol B during the portal phase were reconstructed using either filtered back projection or SAFIRE with 5 different iterative reconstruction (IR) strengths. We performed qualitative and quantitative analyses to select the appropriate IR strength. Reconstructed images were then qualitatively and quantitatively compared with protocol A images. Qualitative and quantitative analysis of protocol B demonstrated that SAFIRE level 2 (S2) was most appropriate in our study. Qualitative and quantitative analysis comparing S2 images from protocol B with images from protocol A, showed overall good diagnostic confidence of S2 images despite a significant radiation dose reduction (47% dose reduction, p < 0.001). Combined use of CARE kV and SAFIRE allowed significant reduction in radiation exposure while maintaining image quality in contrast-enhanced liver CT.

  1. Bilateral bad pixel and Stokes image reconstruction for microgrid polarimetric imagers

    Science.gov (United States)

    LeMaster, Daniel A.; Ratliff, Bradley M.

    2015-09-01

    Uncorrected or poorly corrected bad pixels reduce the effectiveness of polarimetric clutter suppression. In conventional microgrid processing, bad pixel correction is accomplished as a separate step from Stokes image reconstruction. Here, these two steps are combined to speed processing and provide better estimates of the entire image, including missing samples. A variation on the bilateral filter enables both edge preservation in the Stokes imagery and bad pixel suppression. Understanding the newly presented filter requires two key insights. First, the adaptive nature of the bilateral filter is extended to correct for bad pixels by simply incorporating a bad pixel mask. Second, the bilateral filter for Stokes estimation is the sum of the normalized bilateral filters for estimating each analyzer channel individually. This paper describes the new approach and compares it to our legacy method using simulated imagery.

  2. System and method for three-dimensional image reconstruction using an absolute orientation sensor

    KAUST Repository

    Giancola, Silvio

    2018-01-18

    A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image capture device and records IMU data associated with the image data. The image processor includes one or more processing units and memory for storing instructions that are executed by the one or more processing units, wherein the image processor receives the image data and the IMU data as inputs and utilizes the IMU data to pre-align the first image and the second image, and wherein the image processor utilizes a registration algorithm to register the pre-aligned first and second images.

  3. The 2011 WPATH Standards of Care and Penile Reconstruction in Female-to-Male Transsexual Individuals

    Science.gov (United States)

    Selvaggi, Gennaro; Dhejne, Cecilia; Landen, Mikael; Elander, Anna

    2012-01-01

    The World Professional Association for Transgender Health (WPATH) currently publishes the Standards of Care (SOC), to provide clinical guidelines for health care of transsexual, transgender and gender non-conforming persons in order to maximize health and well-being by revealing gender dysphoria. An updated version (7th version, 2011) of the WPATH SOC is currently available. Differences between the 6th and the 7th versions of the SOC are shown; the SOC relevant to penile reconstruction in female-to-male (FtM) persons are emphasized, and we analyze how the 2011 WPATH SOC is influencing the daily practice of physicians involved in performing a penile reconstruction procedure for these patients. Depending by an individual's goals and expectations, the most appropriate surgical technique should be performed: the clinic performing penile reconstruction should be able to offer the whole range of techniques, such as: metoidioplasty, pedicle and free flaps phalloplasty procedures. The goals that physicians and health care institutions should achieve in the next years, in order to improve the care of female-to-male persons, consist in: informing in details the individuals applying for penile reconstruction about all the implications; referring specific individuals to centers capable to deliver a particular surgical technique; implementing the surgery with the most updated refinements. PMID:22654902

  4. The 2011 WPATH Standards of Care and Penile Reconstruction in Female-to-Male Transsexual Individuals

    Directory of Open Access Journals (Sweden)

    Gennaro Selvaggi

    2012-01-01

    Full Text Available The World Professional Association for Transgender Health (WPATH currently publishes the Standards of Care (SOC, to provide clinical guidelines for health care of transsexual, transgender and gender non-conforming persons in order to maximize health and well-being by revealing gender dysphoria. An updated version (7th version, 2011 of the WPATH SOC is currently available. Differences between the 6th and the 7th versions of the SOC are shown; the SOC relevant to penile reconstruction in female-to-male (FtM persons are emphasized, and we analyze how the 2011 WPATH SOC is influencing the daily practice of physicians involved in performing a penile reconstruction procedure for these patients. Depending by an individual’s goals and expectations, the most appropriate surgical technique should be performed: the clinic performing penile reconstruction should be able to offer the whole range of techniques, such as: metoidioplasty, pedicle and free flaps phalloplasty procedures. The goals that physicians and health care institutions should achieve in the next years, in order to improve the care of female-to-male persons, consist in: informing in details the individuals applying for penile reconstruction about all the implications; referring specific individuals to centers capable to deliver a particular surgical technique; implementing the surgery with the most updated refinements.

  5. The 2011 WPATH Standards of Care and Penile Reconstruction in Female-to-Male Transsexual Individuals.

    Science.gov (United States)

    Selvaggi, Gennaro; Dhejne, Cecilia; Landen, Mikael; Elander, Anna

    2012-01-01

    The World Professional Association for Transgender Health (WPATH) currently publishes the Standards of Care (SOC), to provide clinical guidelines for health care of transsexual, transgender and gender non-conforming persons in order to maximize health and well-being by revealing gender dysphoria. An updated version (7th version, 2011) of the WPATH SOC is currently available. Differences between the 6th and the 7th versions of the SOC are shown; the SOC relevant to penile reconstruction in female-to-male (FtM) persons are emphasized, and we analyze how the 2011 WPATH SOC is influencing the daily practice of physicians involved in performing a penile reconstruction procedure for these patients. Depending by an individual's goals and expectations, the most appropriate surgical technique should be performed: the clinic performing penile reconstruction should be able to offer the whole range of techniques, such as: metoidioplasty, pedicle and free flaps phalloplasty procedures. The goals that physicians and health care institutions should achieve in the next years, in order to improve the care of female-to-male persons, consist in: informing in details the individuals applying for penile reconstruction about all the implications; referring specific individuals to centers capable to deliver a particular surgical technique; implementing the surgery with the most updated refinements.

  6. Efficient discrete cosine transform model-based algorithm for photoacoustic image reconstruction

    Science.gov (United States)

    Zhang, Yan; Wang, Yuanyuan; Zhang, Chen

    2013-06-01

    The model-based algorithm is an effective reconstruction method for photoacoustic imaging (PAI). Compared with the analytical reconstruction algorithms, the model-based algorithm is able to provide a more accurate and high-resolution reconstructed image. However, the relatively heavy computational complexity and huge memory storage requirement often impose restrictions on its applications. We incorporate the discrete cosine transform (DCT) in PAI reconstruction and establish a new photoacoustic model. With this new model, an efficient algorithm is proposed for PAI reconstruction. Relatively significant DCT coefficients of the measured signals are used to reconstruct the image. As a result, the calculation can be saved. The theoretical computation complexity of the proposed algorithm is figured out and it is proved that the proposed method is efficient in calculation. The proposed algorithm is also verified through the numerical simulations and in vitro experiments. Compared with former developed model-based methods, the proposed algorithm is able to provide an equivalent reconstruction with the cost of much less time. From the theoretical analysis and the experiment results, it would be concluded that the model-based PAI reconstruction can be accelerated by using the proposed algorithm, so that the practical applicability of PAI may be enhanced.

  7. Wavelet sparse transform optimization in image reconstruction based on compressed sensing

    Science.gov (United States)

    Ziran, Wei; Huachuang, Wang; Jianlin, Zhang

    2017-06-01

    The high image sparsity is very important to improve the accuracy of compressed sensing reconstruction image, and the wavelet transform can make the image sparse obviously. This paper is the optimization method based on wavelet sparse transform in image reconstruction based on compressed sensing, and we have designed a restraining matrix to optimize the wavelet sparse transform. Firstly, the wavelet coefficients are obtained by wavelet transform of the original signal data, and the wavelet coefficients have a tendency of decreasing gradually. The restraining matrix is used to restrain the small coefficients and is a part of image sparse transform, so as to make the wavelet coefficients more sparse. When the sampling rate is between 0. 15 and 0. 45, the simulation results show that the quality promotion of the reconstructed image is the best, and the peak signal to noise ratio (PSNR) is increased by about 0.5dB to 1dB. At the same time, it is more obvious to improve the reconstruction accuracy of the fingerprint texture image, which to some extent makes up for the shortcomings that reconstruction of texture image by compressed sensing based on the wavelet transform has the low accuracy.

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

    Science.gov (United States)

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

    2017-03-01

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

  9. 3D morphology reconstruction using linear array CCD binocular stereo vision imaging system

    Science.gov (United States)

    Pan, Yu; Wang, Jinjiang

    2018-01-01

    Binocular vision imaging system, which has a small field of view, cannot reconstruct the 3-D shape of the dynamic object. We found a linear array CCD binocular vision imaging system, which uses different calibration and reconstruct methods. On the basis of the binocular vision imaging system, the linear array CCD binocular vision imaging systems which has a wider field of view can reconstruct the 3-D morphology of objects in continuous motion, and the results are accurate. This research mainly introduces the composition and principle of linear array CCD binocular vision imaging system, including the calibration, capture, matching and reconstruction of the imaging system. The system consists of two linear array cameras which were placed in special arrangements and a horizontal moving platform that can pick up objects. The internal and external parameters of the camera are obtained by calibrating in advance. And then using the camera to capture images of moving objects, the results are then matched and 3-D reconstructed. The linear array CCD binocular vision imaging systems can accurately measure the 3-D appearance of moving objects, this essay is of great significance to measure the 3-D morphology of moving objects.

  10. A new approach to solving the prior image constrained compressed sensing (PICCS) with applications in CT image reconstruction

    Science.gov (United States)

    Tang, Yuchao; Zong, Chunxiang

    2017-03-01

    Reduce does exposure in computed tomography (CT) scan has been received much attention in recent years. It is reasonable to reduce the number of projections for reducing does. However, conventional CT image reconstruction methods will lead to streaking artifact due to few-view data. Inspired by the theory of compressive sensing, the total variation minimization method was widely studied in the CT image reconstruction from few-view and limited-angle data. It takes full advantage of the sparsity in the image gradient magnitude. In this paper, we propose a general prior image constrained compressed sensing model and develop an efficient iterative algorithm to solve it. The main idea of our approach is to reformulate the optimization problem as an unconstrained optimization problem with the sum of two convex functions. Then we derive the iterative algorithm by use of the primal dual proximity method. The prior image is reconstructed by a conventional analytic algorithm such as filtered backprojection (FBP) or from a dynamic CT image sequences. We demonstrate the performance of the proposed iterative algorithm in a quite few-view projection data with just 3 percent of the reconstructed image size. The numerical simulation results show that the proposed reconstruction algorithm outperforms the commonly used total variation minimization method.

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

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Heide; Sidky, Emil Y.; Pan, Xiaochuan

    2013-01-01

    Iterative image reconstruction with sparsity-exploiting methods, such as total variation (TV) minimization, investigated in compressive sensing claim potentially large reductions in sampling requirements. Quantifying this claim for computed tomography (CT) is nontrivial, because both full sampling...... of a linear imaging model and address invertibility and stability. In the example application of breast CT, the SSCs are used as reference points of full sampling for quantifying the undersampling admitted by reconstruction through TV-minimization. In numerical simulations, factors affecting admissible...... undersampling are studied. Differences between few-view and few-detector bin reconstruction as well as a relation between object sparsity and admitted undersampling are quantified....

  12. Photon-counting passive 3D image sensing for reconstruction and recognition of partially occluded objects.

    Science.gov (United States)

    Yeom, Seokwon; Javidi, Bahram; Lee, Chae-Wook; Watson, Edward

    2007-11-26

    In this paper, we discuss the reconstruction and the recognition of partially occluded objects using photon counting integral imaging (II). Irradiance scenes are numerically reconstructed for the reference target in three-dimensional (3D) space. Photon counting scenes are estimated for unknown input objects using maximum likelihood estimation (MLE) of Poisson parameter. We propose nonlinear matched filtering in 3D space to recognize partially occluded targets. The recognition performance is substantially improved from the nonlinear matched filtering of elemental images without 3D reconstruction. The discrimination capability is analyzed in terms of Fisher ratio (FR) and receiver operating characteristic (ROC) curves.

  13. Body image investment in breast cancer patients undergoing reconstruction: taking a closer look at the Appearance Schemas Inventory-Revised.

    Science.gov (United States)

    Chua, Alicia S; DeSantis, Stacia M; Teo, Irene; Fingeret, Michelle Cororve

    2015-03-01

    Breast cancer and its treatment can significantly affect a woman's body image. As such, it would be useful to understand the importance or value these patients place on their appearance. We evaluated the factor structure of the Appearance Schemas Inventory-Revised (ASI-R), a measure of body image investment, with a sample of 356 breast cancer patients undergoing mastectomy and breast reconstruction. Using confirmatory and exploratory factor analyses, we found that a three-factor model demonstrated an improvement in fit over the original two-factor structure of the ASI-R. These factors were named Appearance Self-Evaluation, Appearance Power/Control, and Appearance Standards and Behavior. The three aforementioned factors demonstrated acceptable internal consistency reliabilities. Our findings have implications for the use of the ASI-R in an oncology setting, specifically for breast cancer patients undergoing reconstruction. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Ultralow dose dentomaxillofacial CT imaging and iterative reconstruction techniques: variability of Hounsfield units and contrast-to-noise ratio

    Science.gov (United States)

    Bischel, Alexander; Stratis, Andreas; Kakar, Apoorv; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

    2016-01-01

    Objective: The aim of this study was to evaluate whether application of ultralow dose protocols and iterative reconstruction technology (IRT) influence quantitative Hounsfield units (HUs) and contrast-to-noise ratio (CNR) in dentomaxillofacial CT imaging. Methods: A phantom with inserts of five types of materials was scanned using protocols for (a) a clinical reference for navigated surgery (CT dose index volume 36.58 mGy), (b) low-dose sinus imaging (18.28 mGy) and (c) four ultralow dose imaging (4.14, 2.63, 0.99 and 0.53 mGy). All images were reconstructed using: (i) filtered back projection (FBP); (ii) IRT: adaptive statistical iterative reconstruction-50 (ASIR-50), ASIR-100 and model-based iterative reconstruction (MBIR); and (iii) standard (std) and bone kernel. Mean HU, CNR and average HU error after recalibration were determined. Each combination of protocols was compared using Friedman analysis of variance, followed by Dunn's multiple comparison test. Results: Pearson's sample correlation coefficients were all >0.99. Ultralow dose protocols using FBP showed errors of up to 273 HU. Std kernels had less HU variability than bone kernels. MBIR reduced the error value for the lowest dose protocol to 138 HU and retained the highest relative CNR. ASIR could not demonstrate significant advantages over FBP. Conclusions: Considering a potential dose reduction as low as 1.5% of a std protocol, ultralow dose protocols and IRT should be further tested for clinical dentomaxillofacial CT imaging. Advances in knowledge: HU as a surrogate for bone density may vary significantly in CT ultralow dose imaging. However, use of std kernels and MBIR technology reduce HU error values and may retain the highest CNR. PMID:26859336

  15. Accelerated three-dimensional cine phase contrast imaging using randomly undersampled echo planar imaging with compressed sensing reconstruction.

    Science.gov (United States)

    Basha, Tamer A; Akçakaya, Mehmet; Goddu, Beth; Berg, Sophie; Nezafat, Reza

    2015-01-01

    The aim of this study was to implement and evaluate an accelerated three-dimensional (3D) cine phase contrast MRI sequence by combining a randomly sampled 3D k-space acquisition sequence with an echo planar imaging (EPI) readout. An accelerated 3D cine phase contrast MRI sequence was implemented by combining EPI readout with randomly undersampled 3D k-space data suitable for compressed sensing (CS) reconstruction. The undersampled data were then reconstructed using low-dimensional structural self-learning and thresholding (LOST). 3D phase contrast MRI was acquired in 11 healthy adults using an overall acceleration of 7 (EPI factor of 3 and CS rate of 3). For comparison, a single two-dimensional (2D) cine phase contrast scan was also performed with sensitivity encoding (SENSE) rate 2 and approximately at the level of the pulmonary artery bifurcation. The stroke volume and mean velocity in both the ascending and descending aorta were measured and compared between two sequences using Bland-Altman plots. An average scan time of 3 min and 30 s, corresponding to an acceleration rate of 7, was achieved for 3D cine phase contrast scan with one direction flow encoding, voxel size of 2 × 2 × 3 mm(3) , foot-head coverage of 6 cm and temporal resolution of 30 ms. The mean velocity and stroke volume in both the ascending and descending aorta were statistically equivalent between the proposed 3D sequence and the standard 2D cine phase contrast sequence. The combination of EPI with a randomly undersampled 3D k-space sampling sequence using LOST reconstruction allows a seven-fold reduction in scan time of 3D cine phase contrast MRI without compromising blood flow quantification. Copyright © 2014 John Wiley & Sons, Ltd.

  16. MODIS Level-3 Standard Mapped Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — NOAA CoastWatch distributes chlorophyll-a concentration data from NASA's Aqua Spacecraft. Measurements are gathered by the Moderate Resolution Imaging...

  17. Metrology Standards for Quantitative Imaging Biomarkers.

    Science.gov (United States)

    Sullivan, Daniel C; Obuchowski, Nancy A; Kessler, Larry G; Raunig, David L; Gatsonis, Constantine; Huang, Erich P; Kondratovich, Marina; McShane, Lisa M; Reeves, Anthony P; Barboriak, Daniel P; Guimaraes, Alexander R; Wahl, Richard L

    2015-12-01

    Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies.

  18. Semiquantitative evaluation of {sup 99}mTctrodat1 binding potential by two methods of SPECT image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Leite, Melissa Furlaneto Lellis; Reis, Marilia Alves dos; Oliveira, Cassio Miri; Castiglioni, Mario Luiz Vieira; Bressan, Rodrigo Affonseca, E-mail: mefurlaneto@hotmail.com, E-mail: rodrigoabressan@gmail.com, E-mail: mario.castiglioni@uol.com.br [Universidade Federal de Sao Paulo (UNIFESP), SP (Brazil)

    2017-11-01

    TRODAT-1 is a radiopharmaceutical derived from tropane and linked to Technetium-99m ([{sup 99m}Tc] TRODAT-1) has been used in studies of dopamine transporter (DAT) in central nervous system. Associated with the SPECT technique of acquisition, is able to detect changes in neurological disorders like Parkinson´s disease, evaluating the binding potential (BP) of DAT. The aim of this study was to evaluate the influence of the image reconstruction methods, Filtered Back Projection (FBP) and iterative reconstruction (OSEM), in BP values at the striatal region in 30 healthy volunteers. Images were analyzed by visual inspection and semi-quantitative analysis. Regions of interest (ROI) were made over striatal areas on both sides. Nonparametric Wilcoxon statistical analysis was performed between the BP values from the FBP and OSEM methods. Our results showed that the reconstruction methods have a statistical significant BP values difference in the total striatum (Z = -2,2787 p = 0.005), right striatum (Z = -2,602 p = 0.009) and left striatum (Z= 2,746 p = 0.006). The effect size was calculated to see if there influence in this test: the 'large effect size' for all measurements was observed (total striatum r= -0.51; right striatum r= -0.48; left striatum r= -0.50). FBP is the usual method of reconstruction for brain SPECT images, and our results showed influence of the OSEM method in BP. It is concluded that the method of image reconstruction adopted should be standardized to avoid incorrect evaluations of BP values using [{sup 99m}Tc]TRODAT-1. (author)

  19. A robust state-space kinetics-guided framework for dynamic PET image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Tong, S; Alessio, A M; Kinahan, P E [Department of Radiology, University of Washington, Seattle, WA 98195 (United States); Liu, H; Shi, P, E-mail: saratong@u.washington.edu [Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY 14623 (United States)

    2011-04-21

    Dynamic PET image reconstruction is a challenging issue due to the low SNR and the large quantity of spatio-temporal data. We propose a robust state-space image reconstruction (SSIR) framework for activity reconstruction in dynamic PET. Unlike statistically-based frame-by-frame methods, tracer kinetic modeling is incorporated to provide physiological guidance for the reconstruction, harnessing the temporal information of the dynamic data. Dynamic reconstruction is formulated in a state-space representation, where a compartmental model describes the kinetic processes in a continuous-time system equation, and the imaging data are expressed in a discrete measurement equation. Tracer activity concentrations are treated as the state variables, and are estimated from the dynamic data. Sampled-data H{sub {infinity}} filtering is adopted for robust estimation. H{sub {infinity}} filtering makes no assumptions on the system and measurement statistics, and guarantees bounded estimation error for finite-energy disturbances, leading to robust performance for dynamic data with low SNR and/or errors. This alternative reconstruction approach could help us to deal with unpredictable situations in imaging (e.g. data corruption from failed detector blocks) or inaccurate noise models. Experiments on synthetic phantom and patient PET data are performed to demonstrate feasibility of the SSIR framework, and to explore its potential advantages over frame-by-frame statistical reconstruction approaches.

  20. GPU-Based 3D Cone-Beam CT Image Reconstruction for Large Data Volume

    Directory of Open Access Journals (Sweden)

    Xing Zhao

    2009-01-01

    Full Text Available Currently, 3D cone-beam CT image reconstruction speed is still a severe limitation for clinical application. The computational power of modern graphics processing units (GPUs has been harnessed to provide impressive acceleration of 3D volume image reconstruction. For extra large data volume exceeding the physical graphic memory of GPU, a straightforward compromise is to divide data volume into blocks. Different from the conventional Octree partition method, a new partition scheme is proposed in this paper. This method divides both projection data and reconstructed image volume into subsets according to geometric symmetries in circular cone-beam projection layout, and a fast reconstruction for large data volume can be implemented by packing the subsets of projection data into the RGBA channels of GPU, performing the reconstruction chunk by chunk and combining the individual results in the end. The method is evaluated by reconstructing 3D images from computer-simulation data and real micro-CT data. Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.

  1. Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

    Science.gov (United States)

    Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

    2017-09-20

    The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P image noise was significantly lower (P image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.

  2. Nonlinear PET parametric image reconstruction with MRI information using kernel method

    Science.gov (United States)

    Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

    2017-03-01

    Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

  3. Reconstruction of Computerized Tomography Images on a Cell Broadband Engine using Ray based Interpolation

    DEFF Research Database (Denmark)

    Jørgensen, M. E.; Vinter, Brian

    2009-01-01

    This paper presents a modified version of the filtered backprojection algorithm for reconstruction of images from CT-scanned data [ 2 ]. The algorithm is parallelized and implemented on the Cell Broadband Engine and tested with various densities in data. The original filtered backprojection...... describes a loop through each pixel in the image, locating the nearest rays for the corresponding pixel. The modified version however uses each ray as the center of attention. These are traced through the image, adding to the pixels that are intersected. Due to this modification, the image can...... be reconstructed entirely by the use of integers. To further optimize, the image is divided in sixteen squares and each square is reconstructed by a synergistic processing element (SPE). For the cases where the numbers of SPEs are less than sixteen, a static division of the squares is implemented...

  4. Spectral bidirectional texture function reconstruction by fusing multiple-color and spectral images.

    Science.gov (United States)

    Dong, Wei; Shen, Hui-Liang; Du, Xin; Shao, Si-Jie; Xin, John H

    2016-12-20

    Spectral bidirectional texture function (BTF) is essential for accurate reproduction of material appearance due to its nature of conveying both spatial and spectral information. A practical issue is that the acquisition of raw spectral BTFs is time-consuming. To resolve the limitation, this paper proposes a novel framework for efficient spectral BTF acquisition and reconstruction. The framework acquires red-green-blue (RGB) BTF images and just one spectral image. The full spectral BTFs are reconstructed by fusing the RGB and spectral images based on nonnegative matrix factorization (NMF). Experimental results indicate that the accuracy of spectral reflectance reconstruction is higher than that of existing algorithms. With the reconstructed spectral BTFs, the material appearance can be reproduced with high fidelity under various illumination conditions.

  5. Experimental characterization of the quality of image reconstruction from a chromotomographic system

    Science.gov (United States)

    Dufaud, Kyle J.; Hawks, Michael R.; Tervo, Ryan

    2014-06-01

    A fieldable hyperspectral chromotomographic imager has been developed at the Air Force Institute of Technology to refine component requirements for a space-based system. The imager uses a high speed visible band camera behind a direct-vision prism to simultaneously record two spatial dimensions and the spectral dimension. Capturing all three dimensions simultaneously allows for the hyperspectral imaging of transient events. The prism multiplexes the spectral and spatial information, so a tomographic reconstruction algorithm is required to separate hyperspectral channels. The fixed dispersion of the prism limits the available projections, leading to artifacts in the reconstruction which limit the image quality and spectrometric accuracy of the reconstructions. The amount of degradation is highly dependent on the content of the scene. Experiments were conducted to characterize the image and spectral quality as a function of spatial, spectral, and temporal complexity. We find that in general, image quality degrades as the source bandwidth increases. Spectra estimated from the reconstructed data cube are generally best for point-like sources, and can be highly inaccurate for extended scenes. In other words, the spatial accuracy varies inversely with the spectral width, and the spectral accuracy varies inversely with the spatial width. Experiment results also demonstrate the ability to reconstruct hyperspectral images from transient combustion events.

  6. Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

    Directory of Open Access Journals (Sweden)

    Hongyang Lu

    2016-06-01

    Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

  7. AN IMAGE-BASED TECHNIQUE FOR 3D BUILDING RECONSTRUCTION USING MULTI-VIEW UAV IMAGES

    Directory of Open Access Journals (Sweden)

    F. Alidoost

    2015-12-01

    Full Text Available Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  8. An Image-Based Technique for 3d Building Reconstruction Using Multi-View Uav Images

    Science.gov (United States)

    Alidoost, F.; Arefi, H.

    2015-12-01

    Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

  9. Improved proton computed tomography by dual modality image reconstruction

    DEFF Research Database (Denmark)

    Hansen, David Christoffer; Bassler, Niels; Petersen, Jørgen B.B.

    2014-01-01

    360◦ rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom...... nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully...... power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT...

  10. OpenCL: a viable solution for high-performance medical image reconstruction?

    Science.gov (United States)

    Siegl, Christian; Hofmann, H. G.; Keck, B.; Prümmer, M.; Hornegger, J.

    2011-03-01

    Reconstruction of 3-D volumetric data from C-arm CT projections is a computationally demanding task. For interventional image reconstruction, hardware optimization is mandatory. Manufacturers of medical equipment use a variety of high-performance computing (HPC) platforms, like FPGAs, graphics cards, or multi-core CPUs. A problem of this diversity is that many different frameworks and (vendor-specific) programming languages are used. Furthermore, it is costly to switch the platform, since the code has to be re-written, verified, and optimized. OpenCL, a relatively new industry standard for HPC, promises to enable portable code. Its key idea is to abstract hardware in a way that allows an efficient mapping onto real CPUs, GPUs, and other hardware. The code is compiled for the actual target by the device driver. In this work we investigated the suitability of OpenCL as a tool to write portable code that runs efficiently across different hardware. The problems chosen are back- and forward-projection, the most time-consuming parts of (iterative) reconstruction. We present results on three platforms, a multi-core CPU system and two GPUs, and compare them against manually optimized native implementations. We found that OpenCL allows to share a common framework in one language across platforms. However, considering differences in the underlying architecture, a hardware-oblivious implementation cannot be expected to deliver maximal performance. By optimizing the OpenCL code for the specific hardware we reached over 90% of native performance for both problems, back- and forward-projection, on all platforms.

  11. Direct Parametric Image Reconstruction in Reduced Parameter Space for Rapid Multi-Tracer PET Imaging.

    Science.gov (United States)

    Cheng, Xiaoyin; Li, Zhoulei; Liu, Zhen; Navab, Nassir; Huang, Sung-Cheng; Keller, Ulrich; Ziegler, Sibylle; Shi, Kuangyu

    2015-02-12

    The separation of multiple PET tracers within an overlapping scan based on intrinsic differences of tracer pharmacokinetics is challenging, due to limited signal-to-noise ratio (SNR) of PET measurements and high complexity of fitting models. In this study, we developed a direct parametric image reconstruction (DPIR) method for estimating kinetic parameters and recovering single tracer information from rapid multi-tracer PET measurements. This is achieved by integrating a multi-tracer model in a reduced parameter space (RPS) into dynamic image reconstruction. This new RPS model is reformulated from an existing multi-tracer model and contains fewer parameters for kinetic fitting. Ordered-subsets expectation-maximization (OSEM) was employed to approximate log-likelihood function with respect to kinetic parameters. To incorporate the multi-tracer model, an iterative weighted nonlinear least square (WNLS) method was employed. The proposed multi-tracer DPIR (MTDPIR) algorithm was evaluated on dual-tracer PET simulations ([18F]FDG and [11C]MET) as well as on preclinical PET measurements ([18F]FLT and [18F]FDG). The performance of the proposed algorithm was compared to the indirect parameter estimation method with the original dual-tracer model. The respective contributions of the RPS technique and the DPIR method to the performance of the new algorithm were analyzed in detail. For the preclinical evaluation, the tracer separation results were compared with single [18F]FDG scans of the same subjects measured 2 days before the dual-tracer scan. The results of the simulation and preclinical studies demonstrate that the proposed MT-DPIR method can improve the separation of multiple tracers for PET image quantification and kinetic parameter estimations.

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

    Science.gov (United States)

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

    2017-03-01

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

  13. A comparison of manual neuronal reconstruction from biocytin histology or 2-photon imaging: morphometry and computer modeling

    National Research Council Canada - National Science Library

    Blackman, Arne V; Grabuschnig, Stefan; Legenstein, Robert; Sjöström, P Jesper

    2014-01-01

    .... Reconstructions are typically created using Neurolucida after biocytin histology (BH). An alternative inexpensive and fast method is to use freeware such as Neuromantic to reconstruct from fluorescence imaging (FI...

  14. Sigma-delta receive beamformer based on cascaded reconstruction for ultrasound imaging application.

    Science.gov (United States)

    Cheong, Jia Hao; Lam, Yvonne Ying Hung; Tiew, Kei Tee; Koh, Liang Mong

    2008-09-01

    A pre-delay reconstruction sigma-delta beamformer (SDBF) was recently proposed to achieve a higher level of integration in ultrasound imaging systems. Nevertheless, the high-order reconstruction filter used in each channel of SDBF makes the beamformer highly complex. The beamformer can be simplified by reconstructing the signal after the delay-and-sum process with only one filter. However, this post-delay reconstruction-based design degrades image quality when dynamic focusing is performed. This paper shows that employing a simple pre-delay filter is sufficient to achieve similar performance as conventional pre-delay reconstruction SDBF, as long as the pre-delay filter provides the required pre-delay signal to-quantization noise ratio (SQNR). Based on this finding, we proposed a cascaded reconstruction beamformer that uses a boxcar filter as the pre-delay filter in each channel. Simulations using real phantom data demonstrate that the proposed beamforming method can achieve a contrast resolution comparable to that of the pre-delay reconstruction beamforming method. In addition, the hardware can be greatly simplified compared with the pre-delay reconstruction beamformers.

  15. A novel neural network based image reconstruction model with scale and rotation invariance for target identification and classification for Active millimetre wave imaging

    Science.gov (United States)

    Agarwal, Smriti; Bisht, Amit Singh; Singh, Dharmendra; Pathak, Nagendra Prasad

    2014-12-01

    Millimetre wave imaging (MMW) is gaining tremendous interest among researchers, which has potential applications for security check, standoff personal screening, automotive collision-avoidance, and lot more. Current state-of-art imaging techniques viz. microwave and X-ray imaging suffers from lower resolution and harmful ionizing radiation, respectively. In contrast, MMW imaging operates at lower power and is non-ionizing, hence, medically safe. Despite these favourable attributes, MMW imaging encounters various challenges as; still it is very less explored area and lacks suitable imaging methodology for extracting complete target information. Keeping in view of these challenges, a MMW active imaging radar system at 60 GHz was designed for standoff imaging application. A C-scan (horizontal and vertical scanning) methodology was developed that provides cross-range resolution of 8.59 mm. The paper further details a suitable target identification and classification methodology. For identification of regular shape targets: mean-standard deviation based segmentation technique was formulated and further validated using a different target shape. For classification: probability density function based target material discrimination methodology was proposed and further validated on different dataset. Lastly, a novel artificial neural network based scale and rotation invariant, image reconstruction methodology has been proposed to counter the distortions in the image caused due to noise, rotation or scale variations. The designed neural network once trained with sample images, automatically takes care of these deformations and successfully reconstructs the corrected image for the test targets. Techniques developed in this paper are tested and validated using four different regular shapes viz. rectangle, square, triangle and circle.

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

    Science.gov (United States)

    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

  17. Total variation based gradient descent algorithm for sparse-view photoacoustic image reconstruction.

    Science.gov (United States)

    Zhang, Yan; Wang, Yuanyuan; Zhang, Chen

    2012-12-01

    In photoacoustic imaging (PAI), reconstruction from sparse-view sampling data is a remaining challenge in the cases of fast or real-time imaging. In this paper, we present our study on a total variation based gradient descent (TV-GD) algorithm for sparse-view PAI reconstruction. This algorithm involves the total variation (TV) method in compressed sensing (CS) theory. The objective function of the algorithm is modified by adding the TV value of the reconstructed image. With this modification, the reconstructed image could be closer to the real optical energy distribution map. Additionally in the proposed algorithm, the photoacoustic data is processed and the image is updated individually at each detection point. In this way, the calculation with large matrix can be avoided and a more frequent image update can be obtained. Through the numerical simulations, the proposed algorithm is verified and compared with other reconstruction algorithms which have been widely used in PAI. The peak signal-to-noise ratio (PSNR) of the image reconstructed by this algorithm is higher than those by the other algorithms. Additionally, the convergence of the algorithm, the robustness to noise and the tunable parameter are further discussed. The TV-based algorithm is also implemented in the in vitro experiment. The better performance of the proposed method is revealed in the experiments results. From the results, it is seen that the TV-GD algorithm may be a practical and efficient algorithm for sparse-view PAI reconstruction. Copyright © 2012 Elsevier B.V. All rights reserved.

  18. Optimal image reconstruction intervals for non-invasive coronary angiography with 64-slice CT

    Energy Technology Data Exchange (ETDEWEB)

    Leschka, Sebastian; Husmann, Lars; Desbiolles, Lotus M.; Boehm, Thomas; Marincek, Borut; Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic Radiology, Zurich (Switzerland); Gaemperli, Oliver; Schepis, Tiziano; Koepfli, Pascal [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiovascular Center, Zurich (Switzerland); University of Zurich, Center for Integrative Human Physiology, Zurich (Switzerland)

    2006-09-15

    The reconstruction intervals providing best image quality for non-invasive coronary angiography with 64-slice computed tomography (CT) were evaluated. Contrast-enhanced, retrospectively electrocardiography (ECG)-gated 64-slice CT coronary angiography was performed in 80 patients (47 male, 33 female; mean age 62.1{+-}10.6 years). Thirteen data sets were reconstructed in 5% increments from 20 to 80% of the R-R interval. Depending on the average heart rate during scanning, patients were grouped as <65 bpm (n=49) and {>=}65 bpm (n=31). Two blinded and independent readers assessed the image quality of each coronary segment with a diameter {>=}1.5 mm using the following scores: 1, no motion artifacts; 2, minor artifacts; 3, moderate artifacts; 4, severe artifacts; and 5, not evaluative. The average heart rate was 63.3{+-}13.1 bpm (range 38-102). Acceptable image quality (scores 1-3) was achieved in 99.1% of all coronary segments (1,162/1,172; mean image quality score 1.55{+-}0.77) in the best reconstruction interval. Best image quality was found at 60% and 65% of the R-R interval for all patients and for each heart rate subgroup, whereas motion artifacts occurred significantly more often (P<0.01) at other reconstruction intervals. At heart rates <65 bpm, acceptable image quality was found in all coronary segments at 60%. At heart rates {>=}65 bpm, the whole coronary artery tree could be visualized with acceptable image quality in 87% (27/31) of the patients at 60%, while ten segments in four patients were rated as non-diagnostic (scores 4-5) at any reconstruction interval. In conclusion, 64-slice CT coronary angiography provides best overall image quality in mid-diastole. At heart rates <65 bpm, diagnostic image quality of all coronary segments can be obtained at a single reconstruction interval of 60%. (orig.)

  19. Importance of the grayscale in early assessment of image quality gains with iterative CT reconstruction

    Science.gov (United States)

    Noo, F.; Hahn, K.; Guo, Z.

    2016-03-01

    Iterative reconstruction methods have become an important research topic in X-ray computed tomography (CT), due to their ability to yield improvements in image quality in comparison with the classical filtered bacprojection method. There are many ways to design an effective iterative reconstruction method. Moreover, for each design, there may be a large number of parameters that can be adjusted. Thus, early assessment of image quality, before clinical deployment, plays a large role in identifying and refining solutions. Currently, there are few publications reporting on early, task-based assessment of image quality achieved with iterative reconstruction methods. We report here on such an assessment, and we illustrate at the same time the importance of the grayscale used for image display when conducting this type of assessment. Our results further support observations made by others that the edge preserving penalty term used in iterative reconstruction is a key ingredient to improving image quality in terms of detection task. Our results also provide a clear demonstration of an implication made in one of our previous publications, namely that the grayscale window plays an important role in image quality comparisons involving iterative CT reconstruction methods.

  20. Systematized methods of surface reconstruction from the serial sectioned images of a cadaver head.

    Science.gov (United States)

    Shin, Dong Sun; Chung, Min Suk; Park, Jin Seo

    2012-01-01

    Three-dimensional models have played important roles in medical simulation and education. Surface models can be manipulated in real time and even online; surface models have significant features for an interactive simulation system. The objective surface models are obtainable from accumulation of each structure's outlines, followed by surface reconstruction. The aim of this research was to suggest the arranged methods of surface reconstruction, which might be applied to building surface models from serial images, such as computed tomographic scans and magnetic resonance images. We used recent state-of-the-art sectioned images of a cadaver head in which several structures were delineated. Four reconstruction methods were regulated according to the structure's morphology: all outlines of a structure are overlapped and singular (method 1), overlapped and not singular (method 2), not overlapped but singular (method 3), and neither overlapped nor singular (method 4). From the trials with various kinds of head structures, we strongly suggested methods 1 and 2, in which volume reconstruction before surface reconstruction accelerated the processing speed on 3D-DOCTOR. So as to use methods 1 and 2, how to make the neighboring outlines overlapped in advance was discussed. The surface models of detailed head structures prepared in this investigation will hopefully contribute to various simulations for clinical practice. The value of the surface models are enhanced if they are placed over the original sectioned images, outlined images, and magnetic resonance images of the same cadaver.

  1. A physics-based intravascular ultrasound image reconstruction method for lumen segmentation.

    Science.gov (United States)

    Mendizabal-Ruiz, Gerardo; Kakadiaris, Ioannis A

    2016-08-01

    Intravascular ultrasound (IVUS) refers to the medical imaging technique consisting of a miniaturized ultrasound transducer located at the tip of a catheter that can be introduced in the blood vessels providing high-resolution, cross-sectional images of their interior. Current methods for the generation of an IVUS image reconstruction from radio frequency (RF) data do not account for the physics involved in the interaction between the IVUS ultrasound signal and the tissues of the vessel. In this paper, we present a novel method to generate an IVUS image reconstruction based on the use of a scattering model that considers the tissues of the vessel as a distribution of three-dimensional point scatterers. We evaluated the impact of employing the proposed IVUS image reconstruction method in the segmentation of the lumen/wall interface on 40MHz IVUS data using an existing automatic lumen segmentation method. We compared the results with those obtained using the B-mode reconstruction on 600 randomly selected frames from twelve pullback sequences acquired from rabbit aortas and different arteries of swine. Our results indicate the feasibility of employing the proposed IVUS image reconstruction for the segmentation of the lumen. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Radar Imaging of Building Interiors using Sparse Reconstruction

    NARCIS (Netherlands)

    Rossum, W.L. van; Wit, J.J.M. de; Tan, R.G.

    2012-01-01

    At TNO an innovative concept to obtain inside building awareness with stand-off, through-the-wall radar has been developed: SAPPHIRE. The system concept exploits particular phase behavior in the 3D radar data to extract dominant scatterers inside a building. These scatterers can be reconstructed

  3. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2016-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  4. CT imaging of congenital lung lesions: effect of iterative reconstruction on diagnostic performance and radiation dose.

    Science.gov (United States)

    Haggerty, Jay E; Smith, Ethan A; Kunisaki, Shaun M; Dillman, Jonathan R

    2015-07-01

    Different iterative reconstruction techniques are available for use in pediatric computed tomography (CT), but these techniques have not been systematically evaluated in infants. To determine the effect of iterative reconstruction on diagnostic performance, image quality and radiation dose in infants undergoing CT evaluation for congenital lung lesions. A retrospective review of contrast-enhanced chest CT in infants (reconstruction method. CTDIvol was used to calculate size-specific dose estimates (SSDE). CT findings were correlated with intraoperative and histopathological findings. Analysis of variance and the Student's t-test were used to compare image noise measurements and radiation dose estimates between groups. Fifteen CT examinations used filtered back projection (FBP; mean age: 84 days), 15 used adaptive statistical iterative reconstruction (ASiR; mean age: 93 days), and 11 used model-based iterative reconstruction (MBIR; mean age: 98 days). Compared to operative findings, 13/15 (87%), 14/15 (93%) and 11/11 (100%) lesions were correctly characterized using FBP, ASiR and MBIR, respectively. Arterial anatomy was correctly identified in 12/15 (80%) using FBP, 13/15 (87%) using ASiR and 11/11 (100%) using MBIR. Image noise was less for MBIR vs. ASiR (P iterative CT reconstruction techniques while maintaining image quality and lowering radiation dose.

  5. Effect of iterative reconstruction on image quality of low-dose chest computed tomography.

    Science.gov (United States)

    Pavarani, Antonio; Martini, Chiara; Gafa', Veronica; Bini, Paola; Silva, Mario; Ghetti, Caterina; Sverzellati, Nicola

    2016-09-13

    To assess quality and radiologists' preference of low-dose computed tomography (LDCT) reconstructed with filtered back projection (FBP) or Iterative Reconstruction. Thin-section LDCTs (1-mm thick contiguous images; 120 kVp; 30 mAs) of 38 consecutive unselected patients, evaluated for various clinical indications, were reconstructed by four different reconstruction algorithms: FBP and Sinogram-AFfirmed Iterative Reconstruction (SAFIRE) with three different strengths, from 2 to 4 (i.e. S2, S3, S4). The image noise was recorded. Two thoracic radiologists visually compared both anatomic structures (interlobular septa, lung fissures, centrilobular artery, bronchial wall, and small vessels) and lung abnormalities (intralobular reticular opacities, nodules, emphysema, cystic lung disease, decreased-attenuation areas related to constrictive obliterans bronchiolitis, patchy ground-glass opacity, consolidation, and bronchiectasis) using a qualitative four-point scale grading system of the image quality. A lower amount of noise was recorded for LDCTs reformatted with any SAFIRE algorithm, as compared to FBP (P Iterative reconstructions showed lower image noise but did not provide any real improvement for the radiologists' evaluation of thin-section LDCT of the lung.

  6. Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging

    Science.gov (United States)

    Almansouri, Hani; Clayton, Dwight; Kisner, Roger; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

    2016-02-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well's health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.1

  7. Image reconstruction from partial pseudo polar Fourier sampling based on alternating direction total variation minimization

    Science.gov (United States)

    Liu, Qiu-hong; Shu, Fan; Zhang, Wen-kun; Cai, Ai-long; Li, Lei; Yan, Bin

    2013-08-01

    Linear scan Computed Tomography (LCT) has emerged as a promising technique in fields like industrial scanning and security inspection due to its straight-line source trajectory and high scanning speed. However, in practical applications of LCT, the ordinary algorithms suffer from serious artifacts owing to the limited-angle and insufficient data. In this paper, a new method which reconstructs image from partial Fourier data sampled in pseudo polar grid based on alternating direction anisometric total variation minimization has been proposed. The main idea is to reform the image reconstruction problem into solving an under-determined linear equation, and then reconstruct image by applying the popular total variation (TV) minimization to reform an unconstraint optimization by means of augmented Lagrange method and using the alternating minimization method of multiplier (ADMM) which contributes to the fast convergence. The proposed method is practical in the large-scale task of reconstruction due to its algorithmic simplicity and computational efficiency and reconstructs better images. The results of the numerical simulations and pseudo real data reconstructions from the linear scan validate that the proposed method is both efficient and accurate.

  8. Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Almansouri, Hani [Purdue University; Clayton, Dwight A [ORNL; Kisner, Roger A [ORNL; Polsky, Yarom [ORNL; Bouman, Charlie [Purdue University; Santos-Villalobos, Hector J [ORNL

    2015-01-01

    Ultrasound signals have been used extensively for non-destructive evaluation (NDE). However, typical reconstruction techniques, such as the synthetic aperture focusing technique (SAFT), are limited to quasi-homogenous thin media. New ultrasonic systems and reconstruction algorithms are in need for one-sided NDE of non-homogenous thick objects. An application example space is imaging of reinforced concrete structures for commercial nuclear power plants (NPPs). These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Another example is geothermal and oil/gas production wells. These multi-layered structures are composed of steel, cement, and several types of soil and rocks. Ultrasound systems with greater penetration range and image quality will allow for better monitoring of the well s health and prediction of high-pressure hydraulic fracturing of the rock. These application challenges need to be addressed with an integrated imaging approach, where the application, hardware, and reconstruction software are highly integrated and optimized. Therefore, we are developing an ultrasonic system with Model-Based Iterative Reconstruction (MBIR) as the image reconstruction backbone. As the first implementation of MBIR for ultrasonic signals, this paper document the first implementation of the algorithm and show reconstruction results for synthetically generated data.

  9. Region-Based 4D Tomographic Image Reconstruction: Application to Cardiac X-ray CT

    NARCIS (Netherlands)

    G. Van Eyndhoven (Geert); K.J. Batenburg (Joost); J. Sijbers (Jan)

    2015-01-01

    htmlabstractX-ray computed tomography (CT) is a powerful tool for noninvasive cardiac imaging. However, radiation dose is a major issue. In this paper, we propose an iterative reconstruction method that reduces the radiation dose without compromising image quality. This is achieved by exploiting

  10. Remote Sensing Images Super Resolution Reconstruction Based on Multi-scale Detail Enhancement

    Directory of Open Access Journals (Sweden)

    ZHU Hong

    2016-09-01

    Full Text Available The existing methods are hard to highlight the details after super resolution reconstruction, so it is proposed a super-resolution model frame to enhance the multi-scale details. Firstly, the sequence images are multi-scale deposed to keep the edge structure and the deposed multi-scale image information are differenced. Then, the smoothing information and detail information are interpolated, and a texture detail enhancement function is built to improve the scope of small details. Finally, the coarse-scale image information and small-medium-scale information are confused to get the premier super-resolution reconstruction result, and a local optimizing model is built to further promote the premier image quality. The experiments on the same period and different period remote sensing images show that the objective evaluation index are both largely improved comparing with the interpolation method, traditional total variation(TVmethod,and maximum a posterior(MAP method. The details of the reconstruction image are improved distinctly. The reconstruction image produced using the proposed method provides more high frequency details, and the method proves to be robust and universal for different kinds of satellite remote sensing images.

  11. Algorithms and software for total variation image reconstruction via first-order methods

    DEFF Research Database (Denmark)

    Dahl, Joahim; Hansen, Per Christian; Jensen, Søren Holdt

    2010-01-01

    This paper describes new algorithms and related software for total variation (TV) image reconstruction, more specifically: denoising, inpainting, and deblurring. The algorithms are based on one of Nesterov's first-order methods, tailored to the image processing applications in such a way that...

  12. Three-dimensional photoacoustic tomography through coherent-weighted focal-line-based image reconstruction

    Science.gov (United States)

    Wang, Depeng; Wang, Yuehang; Zhou, Yang; Lovell, Jonathan F.; Xia, Jun

    2017-03-01

    Here, we introduce a new image reconstruction algorithm that combines coherent weighting with focal-line-based three-dimensional image reconstruction. The new algorithm addresses the major limitation of a linear ultrasound transducer array, i.e., the poor elevation resolution, and does not require any modification to the imaging system or the scanning geometry. We first numerically validated our approach through simulation and then experimentally tested it in phantom and in vivo. Both simulation and experimental results proved that the method can significantly improve the elevation resolution (up to 3.4 times in our experiment) and enhance object contrast.

  13. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm.

    Science.gov (United States)

    Sidky, Emil Y; Jørgensen, Jakob H; Pan, Xiaochuan

    2012-05-21

    The primal-dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1-26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity x-ray illumination is presented.

  14. Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

    DEFF Research Database (Denmark)

    Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...

  15. Sparse image reconstruction on the sphere: implications of a new sampling theorem.

    Science.gov (United States)

    McEwen, Jason D; Puy, Gilles; Thiran, Jean-Philippe; Vandergheynst, Pierre; Van De Ville, Dimitri; Wiaux, Yves

    2013-06-01

    We study the impact of sampling theorems on the fidelity of sparse image reconstruction on the sphere. We discuss how a reduction in the number of samples required to represent all information content of a band-limited signal acts to improve the fidelity of sparse image reconstruction, through both the dimensionality and sparsity of signals. To demonstrate this result, we consider a simple inpainting problem on the sphere and consider images sparse in the magnitude of their gradient. We develop a framework for total variation inpainting on the sphere, including fast methods to render the inpainting problem computationally feasible at high resolution. Recently a new sampling theorem on the sphere was developed, reducing the required number of samples by a factor of two for equiangular sampling schemes. Through numerical simulations, we verify the enhanced fidelity of sparse image reconstruction due to the more efficient sampling of the sphere provided by the new sampling theorem.

  16. Model-based reconstruction for illumination variation in face images

    NARCIS (Netherlands)

    Boom, B.J.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2008-01-01

    We propose a novel method to correct for arbitrary illumination variation in the face images. The main purpose is to improve recognition results of face images taken under uncontrolled illumination conditions. We correct the illumination variation in the face images using a face shape model, which

  17. Image reconstruction in a passive element enriched photoacoustic tomography setup

    NARCIS (Netherlands)

    Willemink, Rene

    2010-01-01

    Photoacoustic imaging is a relatively new imaging technology, in which an object is illuminated with optical energy and where in return measurements are taken in the acoustical domain, in order to image the optical absorption distribution inside the object. In this thesis we focus on an experimental

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

    Science.gov (United States)

    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. Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology

    Directory of Open Access Journals (Sweden)

    Vollmer Ekkehard

    2008-04-01

    Full Text Available Abstract Background Progress in automated image analysis, virtual microscopy, hospital information systems, and interdisciplinary data exchange require image standards to be applied in tissue-based diagnosis. Aims To describe the theoretical background, practical experiences and comparable solutions in other medical fields to promote image standards applicable for diagnostic pathology. Theory and experiences Images used in tissue-based diagnosis present with pathology – specific characteristics. It seems appropriate to discuss their characteristics and potential standardization in relation to the levels of hierarchy in which they appear. All levels can be divided into legal, medical, and technological properties. Standards applied to the first level include regulations or aims to be fulfilled. In legal properties, they have to regulate features of privacy, image documentation, transmission, and presentation; in medical properties, features of disease – image combination, human – diagnostics, automated information extraction, archive retrieval and access; and in technological properties features of image acquisition, display, formats, transfer speed, safety, and system dynamics. The next lower second level has to implement the prescriptions of the upper one, i.e. describe how they are implemented. Legal aspects should demand secure encryption for privacy of all patient related data, image archives that include all images used for diagnostics for a period of 10 years at minimum, accurate annotations of dates and viewing, and precise hardware and software information. Medical aspects should demand standardized patients' files such as DICOM 3 or HL 7 including history and previous examinations, information of image display hardware and software, of image resolution and fields of view, of relation between sizes of biological objects and image sizes, and of access to archives and retrieval. Technological aspects should deal with image

  20. Quantitatively assessed CT imaging measures of pulmonary interstitial pneumonia: Effects of reconstruction algorithms on histogram parameters

    Energy Technology Data Exchange (ETDEWEB)

    Koyama, Hisanobu [Department of Radiology, Hyogo Kaibara Hospital, 5208-1 Kaibara, Kaibara-cho, Tanba 669-3395 (Japan)], E-mail: hisanobu19760104@yahoo.co.jp; Ohno, Yoshiharu [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: yosirad@kobe-u.ac.jp; Yamazaki, Youichi [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: y.yamazk@sahs.med.osaka-u.ac.jp; Nogami, Munenobu [Division of PET, Institute of Biomedical Research and Innovation, 2-2 MInamimachi, Minatojima, Chu0-ku, Kobe 650-0047 (Japan)], E-mail: aznogami@fbri.org; Kusaka, Akiko [Division of Radiology, Kobe University Hospital, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: a.kusaka@hosp.kobe-u.ac.jp; Murase, Kenya [Department of Medical Physics and Engineering, Faculty of Health Sciences, Graduate School of Medicine, Osaka University, 1-7 Yamadaoka, Suita 565-0871 (Japan)], E-mail: murase@sahs.med.osaka-u.ac.jp; Sugimura, Kazuro [Department of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017 (Japan)], E-mail: sugimura@med.kobe-u.ac.jp

    2010-04-15

    This study aimed the influences of reconstruction algorithm for quantitative assessments in interstitial pneumonia patients. A total of 25 collagen vascular disease patients (nine male patients and 16 female patients; mean age, 57.2 years; age range 32-77 years) underwent thin-section MDCT examinations, and MDCT data were reconstructed with three kinds of reconstruction algorithm (two high-frequencies [A and B] and one standard [C]). In reconstruction algorithm B, the effect of low- and middle-frequency space was suppressed compared with reconstruction algorithm A. As quantitative CT parameters, kurtosis, skewness, and mean lung density (MLD) were acquired from a frequency histogram of the whole lung parenchyma in each reconstruction algorithm. To determine the difference of quantitative CT parameters affected by reconstruction algorithms, these parameters were compared statistically. To determine the relationships with the disease severity, these parameters were correlated with PFTs. In the results, all the histogram parameters values had significant differences each other (p < 0.0001) and those of reconstruction algorithm C were the highest. All MLDs had fair or moderate correlation with all parameters of PFT (-0.64 < r < -0.45, p < 0.05). Though kurtosis and skewness in high-frequency reconstruction algorithm A had significant correlations with all parameters of PFT (-0.61 < r < -0.45, p < 0.05), there were significant correlations only with diffusing capacity of carbon monoxide (DLco) and total lung capacity (TLC) in reconstruction algorithm C and with forced expiratory volume in 1 s (FEV1), DLco and TLC in reconstruction algorithm B. In conclusion, reconstruction algorithm has influence to quantitative assessments on chest thin-section MDCT examination in interstitial pneumonia patients.

  1. Fast 3D Variable-FOV Reconstruction for Parallel Imaging with Localized Sensitivities

    CERN Document Server

    Can, Yiğit Baran; Çukur, Tolga

    2016-01-01

    Several successful iterative approaches have recently been proposed for parallel-imaging reconstructions of variable-density (VD) acquisitions, but they often induce substantial computational burden for non-Cartesian data. Here we propose a generalized variable-FOV PILS reconstruction 3D VD Cartesian and non-Cartesian data. The proposed method separates k-space into non-intersecting annuli based on sampling density, and sets the 3D reconstruction FOV for each annulus based on the respective sampling density. The variable-FOV method is compared against conventional gridding, PILS, and ESPIRiT reconstructions. Results indicate that the proposed method yields better artifact suppression compared to gridding and PILS, and improves noise conditioning relative to ESPIRiT, enabling fast and high-quality reconstructions of 3D datasets.

  2. Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera

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    Yufu Qu

    2018-01-01

    Full Text Available In order to reconstruct three-dimensional (3D structures from an image sequence captured by unmanned aerial vehicles’ camera (UAVs and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth–map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

  3. Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

    Science.gov (United States)

    Qu, Yufu; Huang, Jianyu; Zhang, Xuan

    2018-01-14

    In order to reconstruct three-dimensional (3D) structures from an image sequence captured by unmanned aerial vehicles' camera (UAVs) and improve the processing speed, we propose a rapid 3D reconstruction method that is based on an image queue, considering the continuity and relevance of UAV camera images. The proposed approach first compresses the feature points of each image into three principal component points by using the principal component analysis method. In order to select the key images suitable for 3D reconstruction, the principal component points are used to estimate the interrelationships between images. Second, these key images are inserted into a fixed-length image queue. The positions and orientations of the images are calculated, and the 3D coordinates of the feature points are estimated using weighted bundle adjustment. With this structural information, the depth maps of these images can be calculated. Next, we update the image queue by deleting some of the old images and inserting some new images into the queue, and a structural calculation of all the images can be performed by repeating the previous steps. Finally, a dense 3D point cloud can be obtained using the depth-map fusion method. The experimental results indicate that when the texture of the images is complex and the number of images exceeds 100, the proposed method can improve the calculation speed by more than a factor of four with almost no loss of precision. Furthermore, as the number of images increases, the improvement in the calculation speed will become more noticeable.

  4. Electrical CT image reconstruction technique for powder flow in petroleum refinery process

    Science.gov (United States)

    Takei, Masahiro; Doh, Deog-Hee; Ochi, Mitsuaki

    2008-03-01

    A new reconstruction method called sampled pattern matching (SPM) was applied to the image reconstruction of an electrical capacitance computed tomography in powder flow in a vertical pipe for petroleum refinery process. This new method is able to achieve stable convergence without the use of an empirical value. Experiments were carried out using fluid catalytic cracking (FCC) catalysts as powder with two air volume flow rates and four powder volume flow rates to measure the capacitance of a pipe cross section. The SPM method is compared with conventional methods in terms of volume fraction, residual capacitance, and correlation capacitance. Overall, the SPM method proved superior to conventional methods without any empirical value because SPM achieves accurate reconstruction by using an objective function that is calculated as the inner product calculation between the experimental capacitance and the reconstructed image capacitance.

  5. MO-DE-BRA-06: 3D Image Acquisition and Reconstruction Explained with Online Animations

    Energy Technology Data Exchange (ETDEWEB)

    Kesner, A

    2016-06-15

    Purpose: Understanding the principles of 3D imaging and image reconstruction is fundamental to the field of medical imaging. Clinicians, technologists, physicists, patients, students, and inquisitive minds all stand to benefit from greater comprehension of the supporting technologies. To help explain the basic principles of 3D imaging, we developed multi-frame animations that convey the concepts of tomographic imaging. The series of free (gif) animations are accessible online, and provide a multimedia introduction to the main concepts of image reconstruction. Methods: Text and animations were created to convey the principles of analytic tomography in CT, PET, and SPECT. Specific topics covered included: principles of sinograms/image data storage, forward projection, principles of PET acquisitions, and filtered backprojection. A total of 8 animations were created and presented for CT, PET, and digital phantom formats. In addition, a free executable is also provided to allow users to create their own tomographic animations – providing an opportunity for interaction and personalization to help foster user interest. Results: Tutorial text and animations have been posted online, freely available to view or download. The animations are in first position in a google search of “image reconstruction animations”. The website currently receives approximately 200 hits/month, from all over the world, and the usage is growing. Positive feedback has been collected from users. Conclusion: We identified a need for improved teaching tools to help visualize the (temporally variant) concepts of image reconstruction, and have shown that animations can be a useful tool for this aspect of education. Furthermore, posting animations freely on the web has shown to be a good way to maximize their impact in the community. In future endeavors, we hope to expand this animated content, to cover principles of iterative reconstruction, as well as other phenomena relating to imaging.

  6. A New Method for Superresolution Image Reconstruction Based on Surveying Adjustment

    Directory of Open Access Journals (Sweden)

    Jianjun Zhu

    2014-01-01

    Full Text Available A new method for superresolution image reconstruction based on surveying adjustment method is described in this paper. The main idea of such new method is that a sequence of low-resolution images are taken firstly as observations, and then observation equations are established for the superresolution image reconstruction. The gray function of the object surface can be found by using surveying adjustment method from the observation equations. High-resolution pixel value of the corresponding area can be calculated by using the gray function. The results show that the proposed algorithm converges much faster than that of conventional superresolution image reconstruction method. By using the new method, the visual feeling of reconstructed image can be greatly improved compared to that of iterative back projection algorithm, and its peak signal-to-noise ratio can also be improved by nearly 1 dB higher than the projection onto convex sets algorithm. Furthermore, this method can successfully avoid the ill-posed problems in reconstruction process.

  7. Joint reconstruction via coupled Bregman iterations with applications to PET-MR imaging

    Science.gov (United States)

    Rasch, Julian; Brinkmann, Eva-Maria; Burger, Martin

    2018-01-01

    Joint reconstruction has recently attracted a lot of attention, especially in the field of medical multi-modality imaging such as PET-MRI. Most of the developed methods rely on the comparison of image gradients, or more precisely their location, direction and magnitude, to make use of structural similarities between the images. A challenge and still an open issue for most of the methods is to handle images in entirely different scales, i.e. different magnitudes of gradients that cannot be dealt with by a global scaling of the data. We propose the use of generalized Bregman distances and infimal convolutions thereof with regard to the well-known total variation functional. The use of a total variation subgradient respectively the involved vector field rather than an image gradient naturally excludes the magnitudes of gradients, which in particular solves the scaling behavior. Additionally, the presented method features a weighting that allows to control the amount of interaction between channels. We give insights into the general behavior of the method, before we further tailor it to a particular application, namely PET-MRI joint reconstruction. To do so, we compute joint reconstruction results from blurry Poisson data for PET and undersampled Fourier data from MRI and show that we can gain a mutual benefit for both modalities. In particular, the results are superior to the respective separate reconstructions and other joint reconstruction methods.

  8. A comparison framework for temporal image reconstructions in electrical impedance tomography.

    Science.gov (United States)

    Gagnon, Hervé; Grychtol, Bartłomiej; Adler, Andy

    2015-06-01

    Electrical impedance tomography (EIT) provides low-resolution images of internal conductivity distributions, but is able to achieve relatively high temporal resolutions. Most EIT image reconstruction algorithms do not explicitly account for the temporal constraints on the measurements or physiological processes under investigation. Instead, algorithms typically assume both that the conductivity distribution does not change during the acquisition of each EIT data frame, and that frames can be reconstructed independently, without consideration of the correlation between images. A failure to account for these temporal effects will result in aliasing-related artefacts in images. Several methods have been proposed to compensate for these effects, including interpolation of raw data, and reconstruction algorithms using Kalman and temporal filtering. However, no systematic work has been performed to understand the severity of the temporal artefacts nor the extent to which algorithms can account for them. We seek to address this need by developing a temporal comparison framework and figures of merit to assess the ability of reconstruction algorithms to account for temporal effects. Using this approach, we compare combinations of three reconstruction algorithms using three EIT data frame types: perfect, realistic and interpolated. The results show that, without accounting for temporal effects, artefacts are present in images for dynamic conductivity contrasts at frequencies 10-20 times slower than the frame rate. The proposed methods show some improvements in reducing these artefacts.

  9. THREE-DIMENSIONAL BUILDING RECONSTRUCTION USING IMAGES OBTAINED BY UNMANNED AERIAL VEHICLES

    Directory of Open Access Journals (Sweden)

    C. Wefelscheid

    2012-09-01

    Full Text Available Unmanned Aerial Vehicles (UAVs offer several new possibilities in a wide range of applications. One example is the 3D reconstruction of buildings. In former times this was either restricted by earthbound vehicles to the reconstruction of facades or by air-borne sensors to generate only very coarse building models. This paper describes an approach for fully automatic image-based 3D reconstruction of buildings using UAVs. UAVs are able to observe the whole 3D scene and to capture images of the object of interest from completely different perspectives. The platform used by this work is a Falcon 8 octocopter from Ascending Technologies. A slightly modified high-resolution consumer camera serves as sensor for data acquisition. The final 3D reconstruction is computed offline after image acquisition and follows a reconstruction process originally developed for image sequences obtained by earthbound vehicles. The per- formance of the described method is evaluated on benchmark datasets showing that the achieved accuracy is high and even comparable with Light Detection and Ranging (LIDAR. Additionally, the results of the application of the complete processing-chain starting at image acquisition and ending in a dense surface-mesh are presented and discussed.

  10. Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images

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    Vibha Tiwari

    2015-12-01

    Full Text Available Compressive sensing theory enables faithful reconstruction of signals, sparse in domain $ \\Psi $, at sampling rate lesser than Nyquist criterion, while using sampling or sensing matrix $ \\Phi $ which satisfies restricted isometric property. The role played by sensing matrix $ \\Phi $ and sparsity matrix $ \\Psi $ is vital in faithful reconstruction. If the sensing matrix is dense then it takes large storage space and leads to high computational cost. In this paper, effort is made to design sparse sensing matrix with least incurred computational cost while maintaining quality of reconstructed image. The design approach followed is based on sparse block circulant matrix (SBCM with few modifications. The other used sparse sensing matrix consists of 15 ones in each column. The medical images used are acquired from US, MRI and CT modalities. The image quality measurement parameters are used to compare the performance of reconstructed medical images using various sensing matrices. It is observed that, since Gram matrix of dictionary matrix ($ \\Phi \\Psi \\mathrm{} $ is closed to identity matrix in case of proposed modified SBCM, therefore, it helps to reconstruct the medical images of very good quality.

  11. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Chong Fan

    2017-03-01

    Full Text Available A sub-block algorithm is usually applied in the super-resolution (SR reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  12. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images.

    Science.gov (United States)

    Fan, Chong; Chen, Xushuai; Zhong, Lei; Zhou, Min; Shi, Yun; Duan, Yulin

    2017-03-18

    A sub-block algorithm is usually applied in the super-resolution (SR) reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  13. 4D-CBCT reconstruction using MV portal imaging during volumetric modulated arc therapy.

    Science.gov (United States)

    Kida, Satoshi; Saotome, Naoya; Masutani, Yoshitaka; Yamashita, Hideomi; Ohtomo, Kuni; Nakagawa, Keiichi; Sakumi, Akira; Haga, Akihiro

    2011-09-01

    Recording target motion during treatment is important for verifying the irradiated region. Recently, cone-beam computed tomography (CBCT) reconstruction from portal images acquired during volumetric modulated arc therapy (VMAT), known as VMAT-CBCT, has been investigated. In this study, we developed a four-dimensional (4D) version of the VMAT-CBCT. The MV portal images were sequentially acquired from an electronic portal imaging device. The flex, background, monitor unit, field size, and multi-leaf collimator masking corrections were considered during image reconstruction. A 4D VMAT-CBCT requires a respiratory signal during image acquisition. An image-based phase recognition (IBPR) method was performed using normalised cross correlation to extract a respiratory signal from the series of portal images. Our original IBPR method enabled us to reconstruct 4D VMAT-CBCT with no external devices. We confirmed that 4D VMAT-CBCT was feasible for two patients and in good agreement with in-treatment 4D kV-CBCT. The visibility of the anatomy in 4D VMAT-CBCT reconstruction for lung cancer patients has the potential of using 4D VMAT-CBCT as a tool for verifying relative positions of tumour for each respiratory phase. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  14. 3D Surface Reconstruction From 2D Binary Images

    Science.gov (United States)

    Raviv, D.; Pao, Y. H.; Loparo, K.

    1987-01-01

    We introduce methods for reconstruction of three dimensional surfaces. They are based on moving the light source relative to an object whose shape is to be determined. Using a camera which is placed above the object and a moving light source, the shadows cast by the object at each angle are recorded and analyzed. In one method, the light source is rotated in a horizontal plane; this method is a simple way to get segmentation between different surfaces. The second method uses a light source which is rotated in a vertical plane. For each section of the object a shadow diagram (Shadowgram) is formed and analyzed to get the third dimension. The Shadowgram has some features which make the reconstruction very simple. By looking at some curves of the Shadowgram, invisible surfaces can be partially reconstructed. The above methods can be combined to achieve simple solutions for problems in the robotics area e.g., the bin-picking problem. A set of experimental results demonstrates the robustness and usefulness of the methods.

  15. Ill-posed problem and regularization in reconstruction of radiobiological parameters from serial tumor imaging data

    Science.gov (United States)

    Chvetsov, Alevei V.; Sandison, George A.; Schwartz, Jeffrey L.; Rengan, Ramesh

    2015-11-01

    The main objective of this article is to improve the stability of reconstruction algorithms for estimation of radiobiological parameters using serial tumor imaging data acquired during radiation therapy. Serial images of tumor response to radiation therapy represent a complex summation of several exponential processes as treatment induced cell inactivation, tumor growth rates, and the rate of cell loss. Accurate assessment of treatment response would require separation of these processes because they define radiobiological determinants of treatment response and, correspondingly, tumor control probability. However, the estimation of radiobiological parameters using imaging data can be considered an inverse ill-posed problem because a sum of several exponentials would produce the Fredholm integral equation of the first kind which is ill posed. Therefore, the stability of reconstruction of radiobiological parameters presents a problem even for the simplest models of tumor response. To study stability of the parameter reconstruction problem, we used a set of serial CT imaging data for head and neck cancer and a simplest case of a two-level cell population model of tumor response. Inverse reconstruction was performed using a simulated annealing algorithm to minimize a least squared objective function. Results show that the reconstructed values of cell surviving fractions and cell doubling time exhibit significant nonphysical fluctuations if no stabilization algorithms are applied. However, after applying a stabilization algorithm based on variational regularization, the reconstruction produces statistical distributions for survival fractions and doubling time that are comparable to published in vitro data. This algorithm is an advance over our previous work where only cell surviving fractions were reconstructed. We conclude that variational regularization allows for an increase in the number of free parameters in our model which enables development of more

  16. Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT

    Science.gov (United States)

    Dunet, Vincent; Hachulla, Anne-Lise; Grimm, Jochen; Beigelman-Aubry, Catherine

    2016-01-01

    Background Model-based iterative reconstruction (MBIR) reduces image noise and improves image quality (IQ) but its influence on post-processing tools including maximal intensity projection (MIP) and minimal intensity projection (mIP) remains unknown. Purpose To evaluate the influence on IQ of MBIR on native, mIP, MIP axial and coronal reformats of reduced dose computed tomography (RD-CT) chest acquisition. Material and Methods Raw data of 50 patients, who underwent a standard dose CT (SD-CT) and a follow-up RD-CT with a CT dose index (CTDI) of 2–3 mGy, were reconstructed by MBIR and FBP. Native slices, 4-mm-thick MIP, and 3-mm-thick mIP axial and coronal reformats were generated. The relative IQ, subjective IQ, image noise, and number of artifacts were determined in order to compare different reconstructions of RD-CT with reference SD-CT. Results The lowest noise was observed with MBIR. RD-CT reconstructed by MBIR exhibited the best relative and subjective IQ on coronal view regardless of the post-processing tool. MBIR generated the lowest rate of artefacts on coronal mIP/MIP reformats and the highest one on axial reformats, mainly represented by distortions and stairsteps artifacts. Conclusion The MBIR algorithm reduces image noise but generates more artifacts than FBP on axial mIP and MIP reformats of RD-CT. Conversely, it significantly improves IQ on coronal views, without increasing artifacts, regardless of the post-processing technique. PMID:27635253

  17. Prior image guided undersampled dual energy reconstruction with piecewise polynomial function constraint.

    Science.gov (United States)

    Wu, Dufan; Zhang, Li; Li, Liang; Shen, Le; Xing, Yuxiang

    2013-01-01

    Dual energy CT has the ability to give more information about the test object by reconstructing the attenuation factors under different energies. These images under different energies share identical structures but different attenuation factors. By referring to the fully sampled low-energy image, we show that it is possible to greatly reduce the sampling rate of the high-energy image in order to lower dose. To compensate the attenuation factor difference between the two modalities, we use piecewise polynomial fitting to fit the low-energy image to the high-energy image. During the reconstruction, the result is constrained by its distance to the fitted image, and the structural information thus can be preserved. An ASD-POCS-based optimization schedule is proposed to solve the problem, and numerical simulations are taken to verify the algorithm.

  18. Prior Image Guided Undersampled Dual Energy R