Parallel Reconstruction Using Null Operations (PRUNO)

PubMed Central

Zhang, Jian; Liu, Chunlei; Moseley, Michael E.

2011-01-01

A novel iterative k-space data-driven technique, namely Parallel Reconstruction Using Null Operations (PRUNO), is presented for parallel imaging reconstruction. In PRUNO, both data calibration and image reconstruction are formulated into linear algebra problems based on a generalized system model. An optimal data calibration strategy is demonstrated by using Singular Value Decomposition (SVD). And an iterative conjugate- gradient approach is proposed to efficiently solve missing k-space samples during reconstruction. With its generalized formulation and precise mathematical model, PRUNO reconstruction yields good accuracy, flexibility, stability. Both computer simulation and in vivo studies have shown that PRUNO produces much better reconstruction quality than autocalibrating partially parallel acquisition (GRAPPA), especially under high accelerating rates. With the aid of PRUO reconstruction, ultra high accelerating parallel imaging can be performed with decent image quality. For example, we have done successful PRUNO reconstruction at a reduction factor of 6 (effective factor of 4.44) with 8 coils and only a few autocalibration signal (ACS) lines. PMID:21604290

Full field image reconstruction is suitable for high-pitch dual-source computed tomography.

PubMed

Mahnken, Andreas H; Allmendinger, Thomas; Sedlmair, Martin; Tamm, Miriam; Reinartz, Sebastian D; Flohr, Thomas

2012-11-01

The field of view (FOV) in high-pitch dual-source computed tomography (DSCT) is limited by the size of the second detector. The goal of this study was to develop and evaluate a full FOV image reconstruction technique for high-pitch DSCT. For reconstruction beyond the FOV of the second detector, raw data of the second system were extended to the full dimensions of the first system, using the partly existing data of the first system in combination with a very smooth transition weight function. During the weighted filtered backprojection, the data of the second system were applied with an additional weighting factor. This method was tested for different pitch values from 1.5 to 3.5 on a simulated phantom and on 25 high-pitch DSCT data sets acquired at pitch values of 1.6, 2.0, 2.5, 2.8, and 3.0. Images were reconstructed with FOV sizes of 260 × 260 and 500 × 500 mm. Image quality was assessed by 2 radiologists using a 5-point Likert scale and analyzed with repeated-measure analysis of variance. In phantom and patient data, full FOV image quality depended on pitch. Where complete projection data from both tube-detector systems were available, image quality was unaffected by pitch changes. Full FOV image quality was not compromised at pitch values of 1.6 and remained fully diagnostic up to a pitch of 2.0. At higher pitch values, there was an increasing difference in image quality between limited and full FOV images (P = 0.0097). With this new image reconstruction technique, full FOV image reconstruction can be used up to a pitch of 2.0.

Volume reconstruction optimization for tomo-PIV algorithms applied to experimental data

NASA Astrophysics Data System (ADS)

Martins, Fabio J. W. A.; Foucaut, Jean-Marc; Thomas, Lionel; Azevedo, Luis F. A.; Stanislas, Michel

2015-08-01

Tomographic PIV is a three-component volumetric velocity measurement technique based on the tomographic reconstruction of a particle distribution imaged by multiple camera views. In essence, the performance and accuracy of this technique is highly dependent on the parametric adjustment and the reconstruction algorithm used. Although synthetic data have been widely employed to optimize experiments, the resulting reconstructed volumes might not have optimal quality. The purpose of the present study is to offer quality indicators that can be applied to data samples in order to improve the quality of velocity results obtained by the tomo-PIV technique. The methodology proposed can potentially lead to significantly reduction in the time required to optimize a tomo-PIV reconstruction, also leading to better quality velocity results. Tomo-PIV data provided by a six-camera turbulent boundary-layer experiment were used to optimize the reconstruction algorithms according to this methodology. Velocity statistics measurements obtained by optimized BIMART, SMART and MART algorithms were compared with hot-wire anemometer data and velocity measurement uncertainties were computed. Results indicated that BIMART and SMART algorithms produced reconstructed volumes with equivalent quality as the standard MART with the benefit of reduced computational time.

Full-color large-scaled computer-generated holograms using RGB color filters.

PubMed

Tsuchiyama, Yasuhiro; Matsushima, Kyoji

2017-02-06

A technique using RGB color filters is proposed for creating high-quality full-color computer-generated holograms (CGHs). The fringe of these CGHs is composed of more than a billion pixels. The CGHs reconstruct full-parallax three-dimensional color images with a deep sensation of depth caused by natural motion parallax. The simulation technique as well as the principle and challenges of high-quality full-color reconstruction are presented to address the design of filter properties suitable for large-scaled CGHs. Optical reconstructions of actual fabricated full-color CGHs are demonstrated in order to verify the proposed techniques.

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

PubMed

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 μV rms ± 6.1 μV rms and 7.5 μV rms ± 5.9 μV rms ) 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.

Reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning.

PubMed

Song, Ying; Zhu, Zhen; Lu, Yang; Liu, Qiegen; Zhao, Jun

2014-03-01

To improve the magnetic resonance imaging (MRI) data acquisition speed while maintaining the reconstruction quality, a novel method is proposed for multislice MRI reconstruction from undersampled k-space data based on compressed-sensing theory using dictionary learning. There are two aspects to improve the reconstruction quality. One is that spatial correlation among slices is used by extending the atoms in dictionary learning from patches to blocks. The other is that the dictionary-learning scheme is used at two resolution levels; i.e., a low-resolution dictionary is used for sparse coding and a high-resolution dictionary is used for image updating. Numerical experiments are carried out on in vivo 3D MR images of brains and abdomens with a variety of undersampling schemes and ratios. The proposed method (dual-DLMRI) achieves better reconstruction quality than conventional reconstruction methods, with the peak signal-to-noise ratio being 7 dB higher. The advantages of the dual dictionaries are obvious compared with the single dictionary. Parameter variations ranging from 50% to 200% only bias the image quality within 15% in terms of the peak signal-to-noise ratio. Dual-DLMRI effectively uses the a priori information in the dual-dictionary scheme and provides dramatically improved reconstruction quality. Copyright © 2013 Wiley Periodicals, Inc.

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

PubMed

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

2011-04-01

We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). 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. 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 (p<0.01). Contrast medium in the injection syringe was scanned to analyse image quality; ASIR did not suppress the severe artefacts of contrast medium. 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.

A Regularized Volumetric Fusion Framework for Large-Scale 3D Reconstruction

NASA Astrophysics Data System (ADS)

Rajput, Asif; Funk, Eugen; Börner, Anko; Hellwich, Olaf

2018-07-01

Modern computational resources combined with low-cost depth sensing systems have enabled mobile robots to reconstruct 3D models of surrounding environments in real-time. Unfortunately, low-cost depth sensors are prone to produce undesirable estimation noise in depth measurements which result in either depth outliers or introduce surface deformations in the reconstructed model. Conventional 3D fusion frameworks integrate multiple error-prone depth measurements over time to reduce noise effects, therefore additional constraints such as steady sensor movement and high frame-rates are required for high quality 3D models. In this paper we propose a generic 3D fusion framework with controlled regularization parameter which inherently reduces noise at the time of data fusion. This allows the proposed framework to generate high quality 3D models without enforcing additional constraints. Evaluation of the reconstructed 3D models shows that the proposed framework outperforms state of art techniques in terms of both absolute reconstruction error and processing time.

Single image super-resolution reconstruction algorithm based on eage selection

NASA Astrophysics Data System (ADS)

Zhang, Yaolan; Liu, Yijun

2017-05-01

Super-resolution (SR) has become more important, because it can generate high-quality high-resolution (HR) images from low-resolution (LR) input images. At present, there are a lot of work is concentrated on developing sophisticated image priors to improve the image quality, while taking much less attention to estimating and incorporating the blur model that can also impact the reconstruction results. We present a new reconstruction method based on eager selection. This method takes full account of the factors that affect the blur kernel estimation and accurately estimating the blur process. When comparing with the state-of-the-art methods, our method has comparable performance.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed Central

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 (p<0.01). Contrast medium in the injection syringe was scanned to analyse image quality; ASIR 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

Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging.

PubMed

Wen, Qiuting; Kodiweera, Chandana; Dale, Brian M; Shivraman, Giri; Wu, Yu-Chien

2018-01-01

To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments. A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions. The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm 2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion. RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Improved parallel image reconstruction using feature refinement.

PubMed

Cheng, Jing; Jia, Sen; Ying, Leslie; Liu, Yuanyuan; Wang, Shanshan; Zhu, Yanjie; Li, Ye; Zou, Chao; Liu, Xin; Liang, Dong

2018-07-01

The aim of this study was to develop a novel feature refinement MR reconstruction method from highly undersampled multichannel acquisitions for improving the image quality and preserve more detail information. The feature refinement technique, which uses a feature descriptor to pick up useful features from residual image discarded by sparsity constrains, is applied to preserve the details of the image in compressed sensing and parallel imaging in MRI (CS-pMRI). The texture descriptor and structure descriptor recognizing different types of features are required for forming the feature descriptor. Feasibility of the feature refinement was validated using three different multicoil reconstruction methods on in vivo data. Experimental results show that reconstruction methods with feature refinement improve the quality of reconstructed image and restore the image details more accurately than the original methods, which is also verified by the lower values of the root mean square error and high frequency error norm. A simple and effective way to preserve more useful detailed information in CS-pMRI is proposed. This technique can effectively improve the reconstruction quality and has superior performance in terms of detail preservation compared with the original version without feature refinement. Magn Reson Med 80:211-223, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

GRAPPA reconstructed wave-CAIPI MP-RAGE at 7 Tesla.

PubMed

Schwarz, Jolanda M; Pracht, Eberhard D; Brenner, Daniel; Reuter, Martin; Stöcker, Tony

2018-04-16

The aim of this project was to develop a GRAPPA-based reconstruction for wave-CAIPI data. Wave-CAIPI fully exploits the 3D coil sensitivity variations by combining corkscrew k-space trajectories with CAIPIRINHA sampling. It reduces artifacts and limits reconstruction induced spatially varying noise enhancement. The GRAPPA-based wave-CAIPI method is robust and does not depend on the accuracy of coil sensitivity estimations. We developed a GRAPPA-based, noniterative wave-CAIPI reconstruction algorithm utilizing multiple GRAPPA kernels. For data acquisition, we implemented a fast 3D magnetization-prepared rapid gradient-echo wave-CAIPI sequence tailored for ultra-high field application. The imaging results were evaluated by comparing the g-factor and the root mean square error to Cartesian CAIPIRINHA acquisitions. Additionally, to assess the performance of subcortical segmentations (calculated by FreeSurfer), the data were analyzed across five subjects. Sixteen-fold accelerated whole brain magnetization-prepared rapid gradient-echo data (1 mm isotropic resolution) were acquired in 40 seconds at 7T. A clear improvement in image quality compared to Cartesian CAIPIRINHA sampling was observed. For the chosen imaging protocol, the results of 16-fold accelerated wave-CAIPI acquisitions were comparable to results of 12-fold accelerated Cartesian CAIPIRINHA. In comparison to the originally proposed SENSitivity Encoding reconstruction of Wave-CAIPI data, the GRAPPA approach provided similar image quality. High-quality, wave-CAIPI magnetization-prepared rapid gradient-echo images can be reconstructed by means of a GRAPPA-based reconstruction algorithm. Even for high acceleration factors, the noniterative reconstruction is robust and does not require coil sensitivity estimations. By altering the aliasing pattern, ultra-fast whole-brain structural imaging becomes feasible. © 2018 International Society for Magnetic Resonance in Medicine.

Synthesis method from low-coherence digital holograms for improvement of image quality in holographic display.

PubMed

Mori, Yutaka; Nomura, Takanori

2013-06-01

In holographic displays, it is undesirable to observe the speckle noises with the reconstructed images. A method for improvement of reconstructed image quality by synthesizing low-coherence digital holograms is proposed. It is possible to obtain speckleless reconstruction of holograms due to low-coherence digital holography. An image sensor records low-coherence digital holograms, and the holograms are synthesized by computational calculation. Two approaches, the threshold-processing and the picking-a-peak methods, are proposed in order to reduce random noise of low-coherence digital holograms. The reconstructed image quality by the proposed methods is compared with the case of high-coherence digital holography. Quantitative evaluation is given to confirm the proposed methods. In addition, the visual evaluation by 15 people is also shown.

Influence of the Pixel Sizes of Reference Computed Tomography on Single-photon Emission Computed Tomography Image Reconstruction Using Conjugate-gradient Algorithm.

PubMed

Okuda, Kyohei; Sakimoto, Shota; Fujii, Susumu; Ida, Tomonobu; Moriyama, Shigeru

The frame-of-reference using computed-tomography (CT) coordinate system on single-photon emission computed tomography (SPECT) reconstruction is one of the advanced characteristics of the xSPECT reconstruction system. The aim of this study was to reveal the influence of the high-resolution frame-of-reference on the xSPECT reconstruction. 99m Tc line-source phantom and National Electrical Manufacturers Association (NEMA) image quality phantom were scanned using the SPECT/CT system. xSPECT reconstructions were performed with the reference CT images in different sizes of the display field-of-view (DFOV) and pixel. The pixel sizes of the reconstructed xSPECT images were close to 2.4 mm, which is acquired as originally projection data, even if the reference CT resolution was varied. The full width at half maximum (FWHM) of the line-source, absolute recovery coefficient, and background variability of image quality phantom were independent on the sizes of DFOV in the reference CT images. The results of this study revealed that the image quality of the reconstructed xSPECT images is not influenced by the resolution of frame-of-reference on SPECT reconstruction.

Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Kahler, Darren L.; Liu, Chihray; Lu, Bo

2015-11-01

Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically-reasonable image with 60 projections. Therefore, a clinically-viable, high-resolution head-and-neck CBCT image can be obtained while cutting the dose by 83%. Moreover, the image quality obtained using p-MGIR is better than the quality obtained using other algorithms. In this work, we propose a novel low-dose CBCT reconstruction algorithm called p-MGIR. It can be potentially used as a CBCT reconstruction algorithm with low dose scan requests

Interleaved diffusion-weighted EPI improved by adaptive partial-Fourier and multi-band multiplexed sensitivity-encoding reconstruction

PubMed Central

Chang, Hing-Chiu; Guhaniyogi, Shayan; Chen, Nan-kuei

2014-01-01

Purpose We report a series of techniques to reliably eliminate artifacts in interleaved echo-planar imaging (EPI) based diffusion weighted imaging (DWI). Methods First, we integrate the previously reported multiplexed sensitivity encoding (MUSE) algorithm with a new adaptive Homodyne partial-Fourier reconstruction algorithm, so that images reconstructed from interleaved partial-Fourier DWI data are free from artifacts even in the presence of either a) motion-induced k-space energy peak displacement, or b) susceptibility field gradient induced fast phase changes. Second, we generalize the previously reported single-band MUSE framework to multi-band MUSE, so that both through-plane and in-plane aliasing artifacts in multi-band multi-shot interleaved DWI data can be effectively eliminated. Results The new adaptive Homodyne-MUSE reconstruction algorithm reliably produces high-quality and high-resolution DWI, eliminating residual artifacts in images reconstructed with previously reported methods. Furthermore, the generalized MUSE algorithm is compatible with multi-band and high-throughput DWI. Conclusion The integration of the multi-band and adaptive Homodyne-MUSE algorithms significantly improves the spatial-resolution, image quality, and scan throughput of interleaved DWI. We expect that the reported reconstruction framework will play an important role in enabling high-resolution DWI for both neuroscience research and clinical uses. PMID:24925000

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

PubMed

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 indicate that CS and DCS techniques offer equivalent image reconstruction quality with simpler practical implementation. It would be a very promising approach in practical applications of modern biomedical imaging technology.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.

PubMed

De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc

2010-09-01

In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.

76 FR 16787 - Subcommittee for Dose Reconstruction Reviews (SDRR), Advisory Board on Radiation and Worker...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-25

... Evaluation Report: OCAS- PER-012--Evaluation of Highly Insoluble Plutonium Compounds; discussion of dose reconstruction cases under review (sets 7-9); OCAS dose reconstruction quality management and assurance... 30333, Telephone (513) 533-6800, Toll Free 1 (800) CDC-INFO, E-mail ocas@cdc.gov . The Director...

In induced reconstructions of Si(1 1 1) as superlattice matched epitaxial templates for InN growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuyyalil, Jithesh; Tangi, Malleswararao; Shivaprasad, S.M., E-mail: smsprasad@jncasr.ac.in

Graphical abstract: Display Omitted Highlights: ► A novel growth method to form InN at low growth temperatures. ► Use of Si reconstruction as a growth template for group III nitrides. ► Band gap variation of InN – Moss–Burstein shift – non-parabolic conduction band for InN. ► Super lattice matching epitaxy of metal induced reconstructions with III–V unit cell. -- Abstract: Indium induced surface reconstructions of Si(1 1 1)-7 × 7 are used as templates to grow high quality InN. We grow InN on Si(1 1 1)-7 × 7, Si(1 1 1)-4 × 1-In and Si(1 1 1)-1 × 1-In reconstructedmore » surfaces and study the quality of the films formed using complementary characterization tools. InN grown on Si(1 1 1)-1 × 1-In reconstruction shows superior film quality with lowest band-edge emission having a narrow full width at half maximum, intense and narrow 0 0 0 2 X-ray diffraction, low surface roughness and carrier concentration an order lower than other samples. We attribute the high quality of the film formed at 300 °C to the integral matching of InN and super lattice dimensions, we also study the reasons for the band gap variation of InN in the literature. Present study demonstrates the proposed Superlattice Matched Epitaxy can be a general approach to grow good quality InN at much lower growth temperature on compatible In induced reconstructions of the Si surface.« less

Comparison study of image quality and effective dose in dual energy chest digital tomosynthesis

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Choi, Sunghoon; Lee, Haenghwa; Kim, Dohyeon; Choi, Seungyeon; Kim, Hee-Joung

2018-07-01

The present study aimed to introduce a recently developed digital tomosynthesis system for the chest and describe the procedure for acquiring dual energy bone decomposed tomosynthesis images. Various beam quality and reconstruction algorithms were evaluated for acquiring dual energy chest digital tomosynthesis (CDT) images and the effective dose was calculated with ion chamber and Monte Carlo simulations. The results demonstrated that dual energy CDT improved visualization of the lung field by eliminating the bony structures. In addition, qualitative and quantitative image quality of dual energy CDT using iterative reconstruction was better than that with filtered backprojection (FBP) algorithm. The contrast-to-noise ratio and figure of merit values of dual energy CDT acquired with iterative reconstruction were three times better than those acquired with FBP reconstruction. The difference in the image quality according to the acquisition conditions was not noticeable, but the effective dose was significantly affected by the acquisition condition. The high energy acquisition condition using 130 kVp recorded a relatively high effective dose. We conclude that dual energy CDT has the potential to compensate for major problems in CDT due to decomposed bony structures, which induce significant artifacts. Although there are many variables in the clinical practice, our results regarding reconstruction algorithms and acquisition conditions may be used as the basis for clinical use of dual energy CDT imaging.

High-Pitch, Low-Voltage and Low-Iodine-Concentration CT Angiography of Aorta: Assessment of Image Quality and Radiation Dose with Iterative Reconstruction

PubMed Central

Shen, Yanguang; Sun, Zhonghua; Xu, Lei; Li, Yu; Zhang, Nan; Yan, Zixu; Fan, Zhanming

2015-01-01

Objective To assess the image quality of aorta obtained by dual-source computed tomography angiography (DSCTA), performed with high pitch, low tube voltage, and low iodine concentration contrast medium (CM) with images reconstructed using iterative reconstruction (IR). Methods One hundred patients randomly allocated to receive one of two types of CM underwent DSCTA with the electrocardiogram-triggered Flash protocol. In the low-iodine group, 50 patients received CM containing 270 mg I/mL and were scanned at low tube voltage (100 kVp). In the high-iodine CM group, 50 patients received CM containing 370 mg I/mL and were scanned at the tube voltage (120 kVp). The filtered back projection (FBP) algorithm was used for reconstruction in both groups. In addition, the IR algorithm was used in the low-iodine group. Image quality of the aorta was analyzed subjectively by a 3-point grading scale and objectively by measuring the CT attenuation in terms of the signal- and contrast-to-noise ratios (SNR and CNR, respectively). Radiation and CM doses were compared. Results The CT attenuation, subjective image quality assessment, SNR, and CNR of various aortic regions of interest did not differ significantly between two groups. In the low-iodine group, images reconstructed by FBP and IR demonstrated significant differences in image noise, SNR, and CNR (p<0.05). The low-iodine group resulted in 34.3% less radiation (4.4 ± 0.5 mSv) than the high-iodine group (6.7 ± 0.6 mSv), and 27.3% less iodine weight (20.36 ± 2.65 g) than the high-iodine group (28 ± 1.98 g). Observers exhibited excellent agreement on the aortic image quality scores (κ = 0.904). Conclusions CT images of aorta could be obtained within 2 s by using a DSCT Flash protocol with low tube voltage, IR, and low-iodine-concentration CM. Appropriate contrast enhancement was achieved while maintaining good image quality and decreasing the radiation and iodine doses. PMID:25643353

Neural network Hilbert transform based filtered backprojection for fast inline x-ray inspection

NASA Astrophysics Data System (ADS)

Janssens, Eline; De Beenhouwer, Jan; Van Dael, Mattias; De Schryver, Thomas; Van Hoorebeke, Luc; Verboven, Pieter; Nicolai, Bart; Sijbers, Jan

2018-03-01

X-ray imaging is an important tool for quality control since it allows to inspect the interior of products in a non-destructive way. Conventional x-ray imaging, however, is slow and expensive. Inline x-ray inspection, on the other hand, can pave the way towards fast and individual quality control, provided that a sufficiently high throughput can be achieved at a minimal cost. To meet these criteria, an inline inspection acquisition geometry is proposed where the object moves and rotates on a conveyor belt while it passes a fixed source and detector. Moreover, for this acquisition geometry, a new neural-network-based reconstruction algorithm is introduced: the neural network Hilbert transform based filtered backprojection. The proposed algorithm is evaluated both on simulated and real inline x-ray data and has shown to generate high quality reconstructions of 400  ×  400 reconstruction pixels within 200 ms, thereby meeting the high throughput criteria.

CT image reconstruction with half precision floating-point values.

PubMed

Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc

2011-07-01

Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow's reconstruction hardware (CPU and GPU) that allows implementing the forward projection and backprojection steps, which are the computationally most demanding parts of any reconstruction algorithm, much more efficiently. Instead of the standard 32 bit floating-point values (float), a recently standardized floating-point value with 16 bit (half) is adopted for data representation in image domain and in rawdata domain. The reduction in the total data amount reduces the traffic on the memory bus, which is the bottleneck of today's high-performance algorithms, by 50%. In CT simulations and CT measurements, float reconstructions (gold standard) and half reconstructions are visually compared via difference images and by quantitative image quality evaluation. This is done for analytical reconstruction (filtered backprojection) and iterative reconstruction (ordered subset SART). The magnitude of quantization noise, which is caused by a reduction in the data precision of both rawdata and image data during image reconstruction, is negligible. This is clearly shown for filtered backprojection and iterative ordered subset SART reconstruction. In filtered backprojection, the implementation of the backprojection should be optimized for low data precision if the image data are represented in half format. In ordered subset SART image reconstruction, no adaptations are necessary and the convergence speed remains unchanged. Half precision floating-point values allow to speed up CT image reconstruction without compromising image quality.

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

NASA Astrophysics Data System (ADS)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang-Hee

2014-03-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.

Highly undersampled MR image reconstruction using an improved dual-dictionary learning method with self-adaptive dictionaries.

PubMed

Li, Jiansen; Song, Ying; Zhu, Zhen; Zhao, Jun

2017-05-01

Dual-dictionary learning (Dual-DL) method utilizes both a low-resolution dictionary and a high-resolution dictionary, which are co-trained for sparse coding and image updating, respectively. It can effectively exploit a priori knowledge regarding the typical structures, specific features, and local details of training sets images. The prior knowledge helps to improve the reconstruction quality greatly. This method has been successfully applied in magnetic resonance (MR) image reconstruction. However, it relies heavily on the training sets, and dictionaries are fixed and nonadaptive. In this research, we improve Dual-DL by using self-adaptive dictionaries. The low- and high-resolution dictionaries are updated correspondingly along with the image updating stage to ensure their self-adaptivity. The updated dictionaries incorporate both the prior information of the training sets and the test image directly. Both dictionaries feature improved adaptability. Experimental results demonstrate that the proposed method can efficiently and significantly improve the quality and robustness of MR image reconstruction.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

PubMed

Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

2015-01-01

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P < 0.001). At qualitative analysis of the third study, it also showed that the images reconstructed using ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P < 0.001). Our phantom studies showed that ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Temporal compressive imaging for video

NASA Astrophysics Data System (ADS)

Zhou, Qun; Zhang, Linxia; Ke, Jun

2018-01-01

In many situations, imagers are required to have higher imaging speed, such as gunpowder blasting analysis and observing high-speed biology phenomena. However, measuring high-speed video is a challenge to camera design, especially, in infrared spectrum. In this paper, we reconstruct a high-frame-rate video from compressive video measurements using temporal compressive imaging (TCI) with a temporal compression ratio T=8. This means that, 8 unique high-speed temporal frames will be obtained from a single compressive frame using a reconstruction algorithm. Equivalently, the video frame rates is increased by 8 times. Two methods, two-step iterative shrinkage/threshold (TwIST) algorithm and the Gaussian mixture model (GMM) method, are used for reconstruction. To reduce reconstruction time and memory usage, each frame of size 256×256 is divided into patches of size 8×8. The influence of different coded mask to reconstruction is discussed. The reconstruction qualities using TwIST and GMM are also compared.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, C; Zhang, H; Chen, Y

Purpose: Recently, compressed sensing (CS) based iterative reconstruction (IR) method is receiving attentions to reconstruct high quality cone beam computed tomography (CBCT) images using sparsely sampled or noisy projections. The aim of this study is to develop a novel baseline algorithm called Mask Guided Image Reconstruction (MGIR), which can provide superior image quality for both low-dose 3DCBCT and 4DCBCT under single mathematical framework. Methods: In MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions where anatomical structures are 1) within the priori-defined mask and 2) outside the mask. Then we update each part of imagesmore » alternatively thorough solving minimization problems based on CS type IR. For low-dose 3DCBCT, the former region is defined as the anatomically complex region where it is focused to preserve edge information while latter region is defined as contrast uniform, and hence aggressively updated to remove noise/artifact. In 4DCBCT, the regions are separated as the common static part and moving part. Then, static volume and moving volumes were updated with global and phase sorted projection respectively, to optimize the image quality of both moving and static part simultaneously. Results: Examination of MGIR algorithm showed that high quality of both low-dose 3DCBCT and 4DCBCT images can be reconstructed without compromising the image resolution and imaging dose or scanning time respectively. For low-dose 3DCBCT, a clinical viable and high resolution head-and-neck image can be obtained while cutting the dose by 83%. In 4DCBCT, excellent quality 4DCBCT images could be reconstructed while requiring no more projection data and imaging dose than a typical clinical 3DCBCT scan. Conclusion: The results shown that the image quality of MGIR was superior compared to other published CS based IR algorithms for both 4DCBCT and low-dose 3DCBCT. This makes our MGIR algorithm potentially useful in various on-line clinical applications. Provisional Patent: UF#15476; WGS Ref. No. U1198.70067US00.« less

Nanoscale imaging with table-top coherent extreme ultraviolet source based on high harmonic generation

NASA Astrophysics Data System (ADS)

Ba Dinh, Khuong; Le, Hoang Vu; Hannaford, Peter; Van Dao, Lap

2017-08-01

A table-top coherent diffractive imaging experiment on a sample with biological-like characteristics using a focused narrow-bandwidth high harmonic source around 30 nm is performed. An approach involving a beam stop and a new reconstruction algorithm to enhance the quality of reconstructed the image is described.

Facial expression reconstruction on the basis of selected vertices of triangle mesh

NASA Astrophysics Data System (ADS)

Peszor, Damian; Wojciechowska, Marzena

2016-06-01

Facial expression reconstruction is an important issue in the field of computer graphics. While it is relatively easy to create an animation based on meshes constructed through video recordings, this kind of high-quality data is often not transferred to another model because of lack of intermediary, anthropometry-based way to do so. However, if a high-quality mesh is sampled with sufficient density, it is possible to use obtained feature points to encode the shape of surrounding vertices in a way that can be easily transferred to another mesh with corresponding feature points. In this paper we present a method used for obtaining information for the purpose of reconstructing changes in facial surface on the basis of selected feature points.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed

Cui, Xiaoming; Li, Tao; Li, Xin; Zhou, Weihua

2015-05-01

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. 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. 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. 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. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evaluation of Orthopedic Metal Artifact Reduction Application in Three-Dimensional Computed Tomography Reconstruction of Spinal Instrumentation: A Single Saudi Center Experience.

PubMed

Ali, Amir Monir

2018-01-01

The aim of the study was to evaluate the commercially available orthopedic metal artifact reduction (OMAR) technique in postoperative three-dimensional computed tomography (3DCT) reconstruction studies after spinal instrumentation and to investigate its clinical application. One hundred and twenty (120) patients with spinal metallic implants were included in the study. All had 3DCT reconstruction examinations using the OMAR software after obtaining the informed consents and approval of the Institution Ethical Committee. The degree of the artifacts, the related muscular density, the clearness of intermuscular fat planes, and definition of the adjacent vertebrae were qualitatively evaluated. The diagnostic satisfaction and quality of the 3D reconstruction images were thoroughly assessed. The majority (96.7%) of 3DCT reconstruction images performed were considered satisfactory to excellent for diagnosis. Only 3.3% of the reconstructed images had rendered unacceptable diagnostic quality. OMAR can effectively reduce metallic artifacts in patients with spinal instrumentation with highly diagnostic 3DCT reconstruction images.

SU-G-BRA-11: Tumor Tracking in An Iterative Volume of Interest Based 4D CBCT Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, R; Pan, T; Ahmad, M

2016-06-15

Purpose: 4D CBCT can allow evaluation of tumor motion immediately prior to radiation therapy, but suffers from heavy artifacts that limit its ability to track tumors. Various iterative and compressed sensing reconstructions have been proposed to reduce these artifacts, but are costly time-wise and can degrade the image quality of bony anatomy for alignment with regularization. We have previously proposed an iterative volume of interest (I4D VOI) method which minimizes reconstruction time and maintains image quality of bony anatomy by focusing a 4D reconstruction within a VOI. The purpose of this study is to test the tumor tracking accuracy ofmore » this method compared to existing methods. Methods: Long scan (8–10 mins) CBCT data with corresponding RPM data was collected for 12 lung cancer patients. The full data set was sorted into 8 phases and reconstructed using FDK cone beam reconstruction to serve as a gold standard. The data was reduced in way that maintains a normal breathing pattern and used to reconstruct 4D images using FDK, low and high regularization TV minimization (λ=2,10), and the proposed I4D VOI method with PTVs used for the VOI. Tumor trajectories were found using rigid registration within the VOI for each reconstruction and compared to the gold standard. Results: The root mean square error (RMSE) values were 2.70mm for FDK, 2.50mm for low regularization TV, 1.48mm for high regularization TV, and 2.34mm for I4D VOI. Streak artifacts in I4D VOI were reduced compared to FDK and images were less blurred than TV reconstructed images. Conclusion: I4D VOI performed at least as well as existing methods in tumor tracking, with the exception of high regularization TV minimization. These results along with the reconstruction time and outside VOI image quality advantages suggest I4D VOI to be an improvement over existing methods. Funding support provided by CPRIT grant RP110562-P2-01.« less

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, S; Zhang, Y; Ma, J

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinctmore » from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.« less

A framework for directional and higher-order reconstruction in photoacoustic tomography

NASA Astrophysics Data System (ADS)

Boink, Yoeri E.; Lagerwerf, Marinus J.; Steenbergen, Wiendelt; van Gils, Stephan A.; Manohar, Srirang; Brune, Christoph

2018-02-01

Photoacoustic tomography is a hybrid imaging technique that combines high optical tissue contrast with high ultrasound resolution. Direct reconstruction methods such as filtered back-projection, time reversal and least squares suffer from curved line artefacts and blurring, especially in the case of limited angles or strong noise. In recent years, there has been great interest in regularised iterative methods. These methods employ prior knowledge of the image to provide higher quality reconstructions. However, easy comparisons between regularisers and their properties are limited, since many tomography implementations heavily rely on the specific regulariser chosen. To overcome this bottleneck, we present a modular reconstruction framework for photoacoustic tomography, which enables easy comparisons between regularisers with different properties, e.g. nonlinear, higher-order or directional. We solve the underlying minimisation problem with an efficient first-order primal-dual algorithm. Convergence rates are optimised by choosing an operator-dependent preconditioning strategy. A variety of reconstruction methods are tested on challenging 2D synthetic and experimental data sets. They outperform direct reconstruction approaches for strong noise levels and limited angle measurements, offering immediate benefits in terms of acquisition time and quality. This work provides a basic platform for the investigation of future advanced regularisation methods in photoacoustic tomography.

Early experience in microtia reconstruction: the first 100 cases.

PubMed

Sabbagh, Walid

2011-04-01

Auricular reconstruction in Microtia is a challenging operation with a steep learning curve. In view its rarity attaining a high standard for new surgeons is extremely difficult. This study analyses the first 100 microtia cases looking at complications, technique, pattern of progress and aesthetic outcome. The author performed 100 autologous ear reconstructions for microtia over a period of 4 years utilizing the two stage technique popularised by Nagata and Firmin. In 11 cases a temroparietal fascial flap was utilised because of either a low hairline or scarring. Follow up ranged from 3 to 36 months. Data was collected prospectively. There were 7 cases of partial skin necrosis, 3 of which healed with conservative management. In early cases deficiencies were seen in the proportions of the reconstructed ear and the quality of definition. Better shape and definition were evident as more surgical experience was gained. This occurred as a result of increased appreciation of the ear proportions and improved framework carving. Although two stages were planned 21 cases required further procedures. The series demonstrates the early learning curve in microtia reconstruction and underlines the importance of appropriate training and case availability in achieving high quality results in autologous ear reconstruction. Copyright © 2010 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Clinical Feasibility of Free-Breathing Dynamic T1-Weighted Imaging With Gadoxetic Acid-Enhanced Liver Magnetic Resonance Imaging Using a Combination of Variable Density Sampling and Compressed Sensing.

PubMed

Yoon, Jeong Hee; Yu, Mi Hye; Chang, Won; Park, Jin-Young; Nickel, Marcel Dominik; Son, Yohan; Kiefer, Berthold; Lee, Jeong Min

2017-10-01

The purpose of the study was to investigate the clinical feasibility of free-breathing dynamic T1-weighted imaging (T1WI) using Cartesian sampling, compressed sensing, and iterative reconstruction in gadoxetic acid-enhanced liver magnetic resonance imaging (MRI). This retrospective study was approved by our institutional review board, and the requirement for informed consent was waived. A total of 51 patients at high risk of breath-holding failure underwent dynamic T1WI in a free-breathing manner using volumetric interpolated breath-hold (BH) examination with compressed sensing reconstruction (CS-VIBE) and hard gating. Timing, motion artifacts, and image quality were evaluated by 4 radiologists on a 4-point scale. For patients with low image quality scores (<3) on the late arterial phase, respiratory motion-resolved (extradimension [XD]) reconstruction was additionally performed and reviewed in the same manner. In addition, in 68.6% (35/51) patients who had previously undergone liver MRI, image quality and motion artifacts on dynamic phases using CS-VIBE were compared with previous BH-T1WIs. In all patients, adequate arterial-phase timing was obtained at least once. Overall image quality of free-breathing T1WI was 3.30 ± 0.59 on precontrast and 2.68 ± 0.70, 2.93 ± 0.65, and 3.30 ± 0.49 on early arterial, late arterial, and portal venous phases, respectively. In 13 patients with lower than average image quality (<3) on the late arterial phase, motion-resolved reconstructed T1WI (XD-reconstructed CS-VIBE) significantly reduced motion artifacts (P < 0.002-0.021) and improved image quality (P < 0.0001-0.002). In comparison with previous BH-T1WI, CS-VIBE with hard gating or XD reconstruction showed less motion artifacts and better image quality on precontrast, arterial, and portal venous phases (P < 0.0001-0.013). Volumetric interpolated breath-hold examination with compressed sensing has the potential to provide consistent, motion-corrected free-breathing dynamic T1WI for liver MRI in patients at high risk of breath-holding failure.

Medical image enhancement using resolution synthesis

NASA Astrophysics Data System (ADS)

Wong, Tak-Shing; Bouman, Charles A.; Thibault, Jean-Baptiste; Sauer, Ken D.

2011-03-01

We introduce a post-processing approach to improve the quality of CT reconstructed images. The scheme is adapted from the resolution-synthesis (RS)1 interpolation algorithm. In this approach, we consider the input image, scanned at a particular dose level, as a degraded version of a high quality image scanned at a high dose level. Image enhancement is achieved by predicting the high quality image by classification based linear regression. To improve the robustness of our scheme, we also apply the minimum description length principle to determine the optimal number of predictors to use in the scheme, and the ridge regression to regularize the design of the predictors. Experimental results show that our scheme is effective in reducing the noise in images reconstructed from filtered back projection without significant loss of image details. Alternatively, our scheme can also be applied to reduce dose while maintaining image quality at an acceptable level.

Multiview 3D sensing and analysis for high quality point cloud reconstruction

NASA Astrophysics Data System (ADS)

Satnik, Andrej; Izquierdo, Ebroul; Orjesek, Richard

2018-04-01

Multiview 3D reconstruction techniques enable digital reconstruction of 3D objects from the real world by fusing different viewpoints of the same object into a single 3D representation. This process is by no means trivial and the acquisition of high quality point cloud representations of dynamic 3D objects is still an open problem. In this paper, an approach for high fidelity 3D point cloud generation using low cost 3D sensing hardware is presented. The proposed approach runs in an efficient low-cost hardware setting based on several Kinect v2 scanners connected to a single PC. It performs autocalibration and runs in real-time exploiting an efficient composition of several filtering methods including Radius Outlier Removal (ROR), Weighted Median filter (WM) and Weighted Inter-Frame Average filtering (WIFA). The performance of the proposed method has been demonstrated through efficient acquisition of dense 3D point clouds of moving objects.

Iterative metal artifact reduction: evaluation and optimization of technique.

PubMed

Subhas, Naveen; Primak, Andrew N; Obuchowski, Nancy A; Gupta, Amit; Polster, Joshua M; Krauss, Andreas; Iannotti, Joseph P

2014-12-01

Iterative metal artifact reduction (IMAR) is a sinogram inpainting technique that incorporates high-frequency data from standard weighted filtered back projection (WFBP) reconstructions to reduce metal artifact on computed tomography (CT). This study was designed to compare the image quality of IMAR and WFBP in total shoulder arthroplasties (TSA); determine the optimal amount of WFBP high-frequency data needed for IMAR; and compare image quality of the standard 3D technique with that of a faster 2D technique. Eight patients with nine TSA underwent CT with standardized parameters: 140 kVp, 300 mAs, 0.6 mm collimation and slice thickness, and B30 kernel. WFBP, three 3D IMAR algorithms with different amounts of WFBP high-frequency data (IMARlo, lowest; IMARmod, moderate; IMARhi, highest), and one 2D IMAR algorithm were reconstructed. Differences in attenuation near hardware and away from hardware were measured and compared using repeated measures ANOVA. Five readers independently graded image quality; scores were compared using Friedman's test. Attenuation differences were smaller with all 3D IMAR techniques than with WFBP (p < 0.0063). With increasing high-frequency data, the attenuation difference increased slightly (differences not statistically significant). All readers ranked IMARmod and IMARhi more favorably than WFBP (p < 0.05), with IMARmod ranked highest for most structures. The attenuation difference was slightly higher with 2D than with 3D IMAR, with no significant reader preference for 3D over 2D. IMAR significantly decreases metal artifact compared to WFBP both objectively and subjectively in TSA. The incorporation of a moderate amount of WFBP high-frequency data and use of a 2D reconstruction technique optimize image quality and allow for relatively short reconstruction times.

A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging.

PubMed

Yan, Hao; Zhen, Xin; Folkerts, Michael; Li, Yongbao; Pan, Tinsu; Cervino, Laura; Jiang, Steve B; Jia, Xun

2014-07-01

4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is invented to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3-0.5 mm for patients 1-3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1-1.5 min per phase. High-quality 4D-CBCT imaging based on the clinically standard 1-min 3D CBCT scanning protocol is feasible via the proposed hybrid reconstruction algorithm.

Quality of reconstruction of compressed off-axis digital holograms by frequency filtering and wavelets.

PubMed

Cheremkhin, Pavel A; Kurbatova, Ekaterina A

2018-01-01

Compression of digital holograms can significantly help with the storage of objects and data in 2D and 3D form, its transmission, and its reconstruction. Compression of standard images by methods based on wavelets allows high compression ratios (up to 20-50 times) with minimum losses of quality. In the case of digital holograms, application of wavelets directly does not allow high values of compression to be obtained. However, additional preprocessing and postprocessing can afford significant compression of holograms and the acceptable quality of reconstructed images. In this paper application of wavelet transforms for compression of off-axis digital holograms are considered. The combined technique based on zero- and twin-order elimination, wavelet compression of the amplitude and phase components of the obtained Fourier spectrum, and further additional compression of wavelet coefficients by thresholding and quantization is considered. Numerical experiments on reconstruction of images from the compressed holograms are performed. The comparative analysis of applicability of various wavelets and methods of additional compression of wavelet coefficients is performed. Optimum parameters of compression of holograms by the methods can be estimated. Sizes of holographic information were decreased up to 190 times.

The artificial retina processor for track reconstruction at the LHC crossing rate

DOE PAGES

Abba, A.; Bedeschi, F.; Citterio, M.; ...

2015-03-16

We present results of an R&D study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. This is the first detailed demonstration of reconstruction of offline-quality tracks at 40 MHz and makes the device suitable for processing Large Hadron Collider events at the full crossing frequency.

Non-homogeneous updates for the iterative coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Yu, Zhou; Thibault, Jean-Baptiste; Bouman, Charles A.; Sauer, Ken D.; Hsieh, Jiang

2007-02-01

Statistical reconstruction methods show great promise for improving resolution, and reducing noise and artifacts in helical X-ray CT. In fact, statistical reconstruction seems to be particularly valuable in maintaining reconstructed image quality when the dosage is low and the noise is therefore high. However, high computational cost and long reconstruction times remain as a barrier to the use of statistical reconstruction in practical applications. Among the various iterative methods that have been studied for statistical reconstruction, iterative coordinate descent (ICD) has been found to have relatively low overall computational requirements due to its fast convergence. This paper presents a novel method for further speeding the convergence of the ICD algorithm, and therefore reducing the overall reconstruction time for statistical reconstruction. The method, which we call nonhomogeneous iterative coordinate descent (NH-ICD) uses spatially non-homogeneous updates to speed convergence by focusing computation where it is most needed. Experimental results with real data indicate that the method speeds reconstruction by roughly a factor of two for typical 3D multi-slice geometries.

Megahertz ultra-wide-field swept-source retina optical coherence tomography compared to current existing imaging devices.

PubMed

Reznicek, Lukas; Klein, Thomas; Wieser, Wolfgang; Kernt, Marcus; Wolf, Armin; Haritoglou, Christos; Kampik, Anselm; Huber, Robert; Neubauer, Aljoscha S

2014-06-01

To investigate the image quality of wide-angle cross-sectional and reconstructed fundus images based on ultra-megahertz swept-source Fourier domain mode locking (FDML) OCT compared to current generation diagnostic devices. A 1,050 nm swept-source FDML OCT system was constructed running at 1.68 MHz A-scan rate covering approximately 70° field of view. Twelve normal eyes were imaged with the device applying an isotropically dense sampling protocol (1,900 × 1,900 A-scans) with a fill factor of 100 %. Obtained OCT scan image quality was compared with two commercial OCT systems (Heidelberg Spectralis and Stratus OCT) of the same 12 eyes. Reconstructed en-face fundus images from the same FDML-OCT data set were compared to color fundus, infrared and ultra-wide-field scanning laser images (SLO). Comparison of cross-sectional scans showed a high overall image quality of the 15× averaged FDML images at 1.68 MHz [overall quality grading score: 8.42 ± 0.52, range 0 (bad)-10 (excellent)] comparable to current spectral-domain OCTs (overall quality grading score: 8.83 ± 0.39, p = 0.731). On FDML OCT, a dense 3D data set was obtained covering also the central and mid-peripheral retina. The reconstructed FDML OCT en-face fundus images had high image quality comparable to scanning laser ophthalmoscope (SLO) as judged from retinal structures such as vessels and optic disc. Overall grading score was 8.36 ± 0.51 for FDML OCT vs 8.27 ± 0.65 for SLO (p = 0.717). Ultra-wide-field megahertz 3D FDML OCT at 1.68 MHz is feasible, and provides cross-sectional image quality comparable to current spectral-domain OCT devices. In addition, reconstructed en-face visualization of fundus images result in a wide-field view with high image quality as compared to currently available fundus imaging devices. The improvement of >30× in imaging speed over commercial spectral-domain OCT technology enables high-density scan protocols leading to a data set for high quality cross-sectional and en-face images of the posterior segment.

Blind compressed sensing image reconstruction based on alternating direction method

NASA Astrophysics Data System (ADS)

Liu, Qinan; Guo, Shuxu

2018-04-01

In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

WE-G-18A-01: JUNIOR INVESTIGATOR WINNER - Low-Dose C-Arm Cone-Beam CT with Model-Based Image Reconstruction for High-Quality Guidance of Neurosurgical Intervention

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, A; Stayman, J; Otake, Y

Purpose: To address the challenges of image quality, radiation dose, and reconstruction speed in intraoperative cone-beam CT (CBCT) for neurosurgery by combining model-based image reconstruction (MBIR) with accelerated algorithmic and computational methods. Methods: Preclinical studies involved a mobile C-arm for CBCT imaging of two anthropomorphic head phantoms that included simulated imaging targets (ventricles, soft-tissue structures/bleeds) and neurosurgical procedures (deep brain stimulation (DBS) electrode insertion) for assessment of image quality. The penalized likelihood (PL) framework was used for MBIR, incorporating a statistical model with image regularization via an edgepreserving penalty. To accelerate PL reconstruction, the ordered-subset, separable quadratic surrogates (OS-SQS) algorithmmore » was modified to incorporate Nesterov's method and implemented on a multi-GPU system. A fair comparison of image quality between PL and conventional filtered backprojection (FBP) was performed by selecting reconstruction parameters that provided matched low-contrast spatial resolution. Results: CBCT images of the head phantoms demonstrated that PL reconstruction improved image quality (∼28% higher CNR) even at half the radiation dose (3.3 mGy) compared to FBP. A combination of Nesterov's method and fast projectors yielded a PL reconstruction run-time of 251 sec (cf., 5729 sec for OS-SQS, 13 sec for FBP). Insertion of a DBS electrode resulted in severe metal artifact streaks in FBP reconstructions, whereas PL was intrinsically robust against metal artifact. The combination of noise and artifact was reduced from 32.2 HU in FBP to 9.5 HU in PL, thereby providing better assessment of device placement and potential complications. Conclusion: The methods can be applied to intraoperative CBCT for guidance and verification of neurosurgical procedures (DBS electrode insertion, biopsy, tumor resection) and detection of complications (intracranial hemorrhage). Significant improvement in image quality, dose reduction, and reconstruction time of ∼4 min will enable practical deployment of low-dose C-arm CBCT within the operating room. AAPM Research Seed Funding (2013-2014); NIH Fellowship F32EB017571; Siemens Healthcare (XP Division)« less

Full-color high-definition CGH reconstructing hybrid scenes of physical and virtual objects

NASA Astrophysics Data System (ADS)

Tsuchiyama, Yasuhiro; Matsushima, Kyoji; Nakahara, Sumio; Yamaguchi, Masahiro; Sakamoto, Yuji

2017-03-01

High-definition CGHs can reconstruct high-quality 3D images that are comparable to that in conventional optical holography. However, it was difficult to exhibit full-color images reconstructed by these high-definition CGHs, because three CGHs for RGB colors and a bulky image combiner were needed to produce full-color images. Recently, we reported a novel technique for full-color reconstruction using RGB color filters, which are similar to that used for liquid-crystal panels. This technique allows us to produce full-color high-definition CGHs composed of a single plate and place them on exhibition. By using the technique, we demonstrate full-color CGHs that reconstruct hybrid scenes comprised of real-existing physical objects and CG-modeled virtual objects in this paper. Here, the wave field of the physical object are obtained from dense multi-viewpoint images by employing the ray-sampling (RS) plane technique. In addition to the technique for full-color capturing and reconstruction of real object fields, the principle and simulation technique for full- color CGHs using RGB color filters are presented.

Incomplete projection reconstruction of computed tomography based on the modified discrete algebraic reconstruction technique

NASA Astrophysics Data System (ADS)

Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei

2018-02-01

Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.

SU-D-206-01: Employing a Novel Consensus Optimization Strategy to Achieve Iterative Cone Beam CT Reconstruction On a Multi-GPU Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Southern Medical University, Guangzhou, Guangdong; Tian, Z

Purpose: While compressed sensing-based cone-beam CT (CBCT) iterative reconstruction techniques have demonstrated tremendous capability of reconstructing high-quality images from undersampled noisy data, its long computation time still hinders wide application in routine clinic. The purpose of this study is to develop a reconstruction framework that employs modern consensus optimization techniques to achieve CBCT reconstruction on a multi-GPU platform for improved computational efficiency. Methods: Total projection data were evenly distributed to multiple GPUs. Each GPU performed reconstruction using its own projection data with a conventional total variation regularization approach to ensure image quality. In addition, the solutions from GPUs were subjectmore » to a consistency constraint that they should be identical. We solved the optimization problem with all the constraints considered rigorously using an alternating direction method of multipliers (ADMM) algorithm. The reconstruction framework was implemented using OpenCL on a platform with two Nvidia GTX590 GPU cards, each with two GPUs. We studied the performance of our method and demonstrated its advantages through a simulation case with a NCAT phantom and an experimental case with a Catphan phantom. Result: Compared with the CBCT images reconstructed using conventional FDK method with full projection datasets, our proposed method achieved comparable image quality with about one third projection numbers. The computation time on the multi-GPU platform was ∼55 s and ∼ 35 s in the two cases respectively, achieving a speedup factor of ∼ 3.0 compared with single GPU reconstruction. Conclusion: We have developed a consensus ADMM-based CBCT reconstruction method which enabled performing reconstruction on a multi-GPU platform. The achieved efficiency made this method clinically attractive.« less

Comparison of computation time and image quality between full-parallax 4G-pixels CGHs calculated by the point cloud and polygon-based method

NASA Astrophysics Data System (ADS)

Nakatsuji, Noriaki; Matsushima, Kyoji

2017-03-01

Full-parallax high-definition CGHs composed of more than billion pixels were so far created only by the polygon-based method because of its high performance. However, GPUs recently allow us to generate CGHs much faster by the point cloud. In this paper, we measure computation time of object fields for full-parallax high-definition CGHs, which are composed of 4 billion pixels and reconstruct the same scene, by using the point cloud with GPU and the polygon-based method with CPU. In addition, we compare the optical and simulated reconstructions between CGHs created by these techniques to verify the image quality.

Synthetic Augmented Suture Anchor Reconstruction for a Complete Traumatic Distal Triceps Tendon Rupture in a Male Professional Bodybuilder with Postoperative Biomechanical Assessment

PubMed Central

Nikolaidou, Maria-Elissavet; Banke, Ingo J.; Laios, Thomas; Petsogiannis, Konstantinos; Mourikis, Anastasios

2014-01-01

Bodybuilding is a high-risk sport for distal triceps tendon ruptures. Management, especially in high-demanding athletes, is operative with suture anchor refixation technique being frequently used. However, the rate of rerupture is high due to underlying poor tendon quality. Thus, additional augmentation could be useful. This case report presents a reconstruction technique for a complete traumatic distal triceps tendon rupture in a bodybuilder with postoperative biomechanical assessment. A 28-year-old male professional bodybuilder was treated with a synthetic augmented suture anchor reconstruction for a complete triceps tendon rupture of his right dominant elbow. Postoperative biomechanical assessment included isokinetic elbow strength and endurance testing by using multiple angular velocities to simulate the “off-season” and “precompetition” phases of training. Eighteen months postoperatively and after full return to training, the biomechanical assessment indicated that the strength and endurance of the operated elbow joint was fully restored with even higher ratings compared to the contralateral healthy arm. The described reconstruction technique can be considered as an advisable option in high-performance athletes with underlying poor tendon quality due to high tensile strength and lack of donor site morbidity, thus enabling them to restore preinjury status and achieve safe return to sports. PMID:24711944

DOE Office of Scientific and Technical Information (OSTI.GOV)

A.S. Larin; V.V. Demenko; V.L. Voitanik

In recent Giprokoks designs for the reconstruction of coke-sorting systems, high-productivity vibrational-inertial screens have been employed. This permits single-stage screening and reduction in capital and especially operating expenditures, without loss of coke quality. In two-stage screening, >80 mm coke (for foundry needs) is additionally separated, with significant improvement in quality of the metallurgical coke (25-80 mm). New designs for the reconstruction of coke-sorting systems employ mechanical treatment of the coke outside the furnace, which offers new scope for stabilization of coke quality and permits considerable improvement in mechanical strength and granulometric composition of the coke by mechanical crushing.

Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging.

PubMed

Holdsworth, Samantha J; Aksoy, Murat; Newbould, Rexford D; Yeom, Kristen; Van, Anh T; Ooi, Melvyn B; Barnes, Patrick D; Bammer, Roland; Skare, Stefan

2012-10-01

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion. The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation. This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data. Copyright © 2012 Wiley Periodicals, Inc.

Investigation of Image Reconstruction Parameters of the Mediso nanoScan PC Small-Animal PET/CT Scanner for Two Different Positron Emitters Under NEMA NU 4-2008 Standards.

PubMed

Gaitanis, Anastasios; Kastis, George A; Vlastou, Elena; Bouziotis, Penelope; Verginis, Panayotis; Anagnostopoulos, Constantinos D

2017-08-01

The Tera-Tomo 3D image reconstruction algorithm (a version of OSEM), provided with the Mediso nanoScan® PC (PET8/2) small-animal positron emission tomograph (PET)/x-ray computed tomography (CT) scanner, has various parameter options such as total level of regularization, subsets, and iterations. Also, the acquisition time in PET plays an important role. This study aims to assess the performance of this new small-animal PET/CT scanner for different acquisition times and reconstruction parameters, for 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) and Ga-68, under the NEMA NU 4-2008 standards. Various image quality metrics were calculated for different realizations of [ 18 F]FDG and Ga-68 filled image quality (IQ) phantoms. [ 18 F]FDG imaging produced improved images over Ga-68. The best compromise for the optimization of all image quality factors is achieved for at least 30 min acquisition and image reconstruction with 52 iteration updates combined with a high regularization level. A high regularization level at 52 iteration updates and 30 min acquisition time were found to optimize most of the figures of merit investigated.

Imaging the Parasinus Region with a Third-Generation Dual-Source CT and the Effect of Tin Filtration on Image Quality and Radiation Dose.

PubMed

Lell, M M; May, M S; Brand, M; Eller, A; Buder, T; Hofmann, E; Uder, M; Wuest, W

2015-07-01

CT is the imaging technique of choice in the evaluation of midface trauma or inflammatory disease. We performed a systematic evaluation of scan protocols to optimize image quality and radiation exposure on third-generation dual-source CT. CT protocols with different tube voltage (70-150 kV), current (25-300 reference mAs), prefiltration, pitch value, and rotation time were systematically evaluated. All images were reconstructed with iterative reconstruction (Advanced Modeled Iterative Reconstruction, level 2). To individually compare results with otherwise identical factors, we obtained all scans on a frozen human head. Conebeam CT was performed for image quality and dose comparison with multidetector row CT. Delineation of important anatomic structures and incidental pathologic conditions in the cadaver head was evaluated. One hundred kilovolts with tin prefiltration demonstrated the best compromise between dose and image quality. The most dose-effective combination for trauma imaging was Sn100 kV/250 mAs (volume CT dose index, 2.02 mGy), and for preoperative sinus surgery planning, Sn100 kV/150 mAs (volume CT dose index, 1.22 mGy). "Sn" indicates an additional prefiltration of the x-ray beam with a tin filter to constrict the energy spectrum. Exclusion of sinonasal disease was possible with even a lower dose by using Sn100 kV/25 mAs (volume CT dose index, 0.2 mGy). High image quality at very low dose levels can be achieved by using a Sn100-kV protocol with iterative reconstruction. The effective dose is comparable with that of conventional radiography, and the high image quality at even lower radiation exposure favors multidetector row CT over conebeam CT. © 2015 by American Journal of Neuroradiology.

Assessing the quality of restored images in optical long-baseline interferometry

NASA Astrophysics Data System (ADS)

Gomes, Nuno; Garcia, Paulo J. V.; Thiébaut, Éric

2017-03-01

Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics and selecting a few based on general properties. Then, a variety of image reconstruction cases are considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MIRA software, and several merit functions are put to test. It is found that convolution by an effective point spread function is required for proper image quality assessment. The effective angular resolution of the images is superior to naive expectation based on the maximum frequency sampled by the array. This is due to the prior information used in the aperture synthesis algorithm and to the nature of the objects considered. The ℓ1-norm is the most robust of all considered metrics, because being linear it is less sensitive to image smoothing by high regularization levels. For the cases considered, this metric allows the implementation of automatic quality assessment of reconstructed images, with a performance similar to human selection.

D Reconstruction of Ancient Egyptian Rock-Cut Tombs: the Case of M.I.D.A.N.05.

NASA Astrophysics Data System (ADS)

Nabil, M.; Betrò, M.; Metwally, M. N.

2013-07-01

In this paper we present an on-going work to reconstruct a 3D model of M.I.D.A.N.05., an ancient Egyptian tomb located in Luxor. The reconstruction aims at producing a high quality 3D model of the tomb to help in archaeological investigation and other scientific uses. We present details about the different stages of the used reconstruction pipeline, the results so far, and the evaluation of the results in view of the project objectives.

Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography.

PubMed

Precht, Helle; Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess

2016-12-01

Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR ( P  = 0.004). The objective measures showed significant differences between FBP and 60% ASIR ( P  < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR.

Performance of 3DOSEM and MAP algorithms for reconstructing low count SPECT acquisitions.

PubMed

Grootjans, Willem; Meeuwis, Antoi P W; Slump, Cornelis H; de Geus-Oei, Lioe-Fee; Gotthardt, Martin; Visser, Eric P

2016-12-01

Low count single photon emission computed tomography (SPECT) is becoming more important in view of whole body SPECT and reduction of radiation dose. In this study, we investigated the performance of several 3D ordered subset expectation maximization (3DOSEM) and maximum a posteriori (MAP) algorithms for reconstructing low count SPECT images. Phantom experiments were conducted using the National Electrical Manufacturers Association (NEMA) NU2 image quality (IQ) phantom. The background compartment of the phantom was filled with varying concentrations of pertechnetate and indiumchloride, simulating various clinical imaging conditions. Images were acquired using a hybrid SPECT/CT scanner and reconstructed with 3DOSEM and MAP reconstruction algorithms implemented in Siemens Syngo MI.SPECT (Flash3D) and Hermes Hybrid Recon Oncology (Hyrid Recon 3DOSEM and MAP). Image analysis was performed by calculating the contrast recovery coefficient (CRC),percentage background variability (N%), and contrast-to-noise ratio (CNR), defined as the ratio between CRC and N%. Furthermore, image distortion is characterized by calculating the aspect ratio (AR) of ellipses fitted to the hot spheres. Additionally, the performance of these algorithms to reconstruct clinical images was investigated. Images reconstructed with 3DOSEM algorithms demonstrated superior image quality in terms of contrast and resolution recovery when compared to images reconstructed with filtered-back-projection (FBP), OSEM and 2DOSEM. However, occurrence of correlated noise patterns and image distortions significantly deteriorated the quality of 3DOSEM reconstructed images. The mean AR for the 37, 28, 22, and 17mm spheres was 1.3, 1.3, 1.6, and 1.7 respectively. The mean N% increase in high and low count Flash3D and Hybrid Recon 3DOSEM from 5.9% and 4.0% to 11.1% and 9.0%, respectively. Similarly, the mean CNR decreased in high and low count Flash3D and Hybrid Recon 3DOSEM from 8.7 and 8.8 to 3.6 and 4.2, respectively. Regularization with smoothing priors could suppress these noise patterns at the cost of reduced image contrast. The mean N% was 6.4% and 6.8% for low count QSP and MRP MAP reconstructed images. Alternatively, regularization with an anatomical Bowhser prior resulted in sharp images with high contrast, limited image distortion, and low N% of 8.3% in low count images, although some image artifacts did occur. Analysis of clinical images suggested that the same effects occur in clinical imaging. Image quality of low count SPECT acquisitions reconstructed with modern 3DOSEM algorithms is deteriorated by the occurrence of correlated noise patterns and image distortions. The artifacts observed in the phantom experiments can also occur in clinical imaging. Copyright © 2015. Published by Elsevier GmbH.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

"One-Stop Shop": Free-Breathing Dynamic Contrast-Enhanced Magnetic Resonance Imaging of the Kidney Using Iterative Reconstruction and Continuous Golden-Angle Radial Sampling.

PubMed

Riffel, Philipp; Zoellner, Frank G; Budjan, Johannes; Grimm, Robert; Block, Tobias K; Schoenberg, Stefan O; Hausmann, Daniel

2016-11-01

The purpose of the present study was to evaluate a recently introduced technique for free-breathing dynamic contrast-enhanced renal magnetic resonance imaging (MRI) applying a combination of radial k-space sampling, parallel imaging, and compressed sensing. The technique allows retrospective reconstruction of 2 motion-suppressed sets of images from the same acquisition: one with lower temporal resolution but improved image quality for subjective image analysis, and one with high temporal resolution for quantitative perfusion analysis. In this study, 25 patients underwent a kidney examination, including a prototypical fat-suppressed, golden-angle radial stack-of-stars T1-weighted 3-dimensional spoiled gradient-echo examination (GRASP) performed after contrast agent administration during free breathing. Images were reconstructed at temporal resolutions of 55 spokes per frame (6.2 seconds) and 13 spokes per frame (1.5 seconds). The GRASP images were evaluated by 2 blinded radiologists. First, the reconstructions with low temporal resolution underwent subjective image analysis: the radiologists assessed the best arterial phase and the best renal phase and rated image quality score for each patient on a 5-point Likert-type scale.In addition, the diagnostic confidence was rated according to a 3-point Likert-type scale. Similarly, respiratory motion artifacts and streak artifacts were rated according to a 3-point Likert-type scale.Then, the reconstructions with high temporal resolution were analyzed with a voxel-by-voxel deconvolution approach to determine the renal plasma flow, and the results were compared with values reported in previous literature. Reader 1 and reader 2 rated the overall image quality score for the best arterial phase and the best renal phase with a median image quality score of 4 (good image quality) for both phases, respectively. A high diagnostic confidence (median score of 3) was observed. There were no respiratory motion artifacts in any of the patients. Streak artifacts were present in all of the patients, but did not compromise diagnostic image quality.The estimated renal plasma flow was slightly higher (295 ± 78 mL/100 mL per minute) than reported in previous MRI-based studies, but also closer to the physiologically expected value. Dynamic, motion-suppressed contrast-enhanced renal MRI can be performed in high diagnostic quality during free breathing using a combination of golden-angle radial sampling, parallel imaging, and compressed sensing. Both morphologic and quantitative functional information can be acquired within a single acquisition.

A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan, Hao; Folkerts, Michael; Jiang, Steve B., E-mail: xun.jia@utsouthwestern.edu, E-mail: steve.jiang@UTSouthwestern.edu

2014-07-15

Purpose: 4D cone beam CT (4D-CBCT) has been utilized in radiation therapy to provide 4D image guidance in lung and upper abdomen area. However, clinical application of 4D-CBCT is currently limited due to the long scan time and low image quality. The purpose of this paper is to develop a new 4D-CBCT reconstruction method that restores volumetric images based on the 1-min scan data acquired with a standard 3D-CBCT protocol. Methods: The model optimizes a deformation vector field that deforms a patient-specific planning CT (p-CT), so that the calculated 4D-CBCT projections match measurements. A forward-backward splitting (FBS) method is inventedmore » to solve the optimization problem. It splits the original problem into two well-studied subproblems, i.e., image reconstruction and deformable image registration. By iteratively solving the two subproblems, FBS gradually yields correct deformation information, while maintaining high image quality. The whole workflow is implemented on a graphic-processing-unit to improve efficiency. Comprehensive evaluations have been conducted on a moving phantom and three real patient cases regarding the accuracy and quality of the reconstructed images, as well as the algorithm robustness and efficiency. Results: The proposed algorithm reconstructs 4D-CBCT images from highly under-sampled projection data acquired with 1-min scans. Regarding the anatomical structure location accuracy, 0.204 mm average differences and 0.484 mm maximum difference are found for the phantom case, and the maximum differences of 0.3–0.5 mm for patients 1–3 are observed. As for the image quality, intensity errors below 5 and 20 HU compared to the planning CT are achieved for the phantom and the patient cases, respectively. Signal-noise-ratio values are improved by 12.74 and 5.12 times compared to results from FDK algorithm using the 1-min data and 4-min data, respectively. The computation time of the algorithm on a NVIDIA GTX590 card is 1–1.5 min per phase. Conclusions: High-quality 4D-CBCT imaging based on the clinically standard 1-min 3D CBCT scanning protocol is feasible via the proposed hybrid reconstruction algorithm.« less

A modified discrete algebraic reconstruction technique for multiple grey image reconstruction for limited angle range tomography.

PubMed

Liang, Zhiting; Guan, Yong; Liu, Gang; Chen, Xiangyu; Li, Fahu; Guo, Pengfei; Tian, Yangchao

2016-03-01

The `missing wedge', which is due to a restricted rotation range, is a major challenge for quantitative analysis of an object using tomography. With prior knowledge of the grey levels, the discrete algebraic reconstruction technique (DART) is able to reconstruct objects accurately with projections in a limited angle range. However, the quality of the reconstructions declines as the number of grey levels increases. In this paper, a modified DART (MDART) was proposed, in which each independent region of homogeneous material was chosen as a research object, instead of the grey values. The grey values of each discrete region were estimated according to the solution of the linear projection equations. The iterative process of boundary pixels updating and correcting the grey values of each region was executed alternately. Simulation experiments of binary phantoms as well as multiple grey phantoms show that MDART is capable of achieving high-quality reconstructions with projections in a limited angle range. The interesting advancement of MDART is that neither prior knowledge of the grey values nor the number of grey levels is necessary.

Sparse dictionary for synthetic transmit aperture medical ultrasound imaging.

PubMed

Wang, Ping; Jiang, Jin-Yang; Li, Na; Luo, Han-Wu; Li, Fang; Cui, Shi-Gang

2017-07-01

It is possible to recover a signal below the Nyquist sampling limit using a compressive sensing technique in ultrasound imaging. However, the reconstruction enabled by common sparse transform approaches does not achieve satisfactory results. Considering the ultrasound echo signal's features of attenuation, repetition, and superposition, a sparse dictionary with the emission pulse signal is proposed. Sparse coefficients in the proposed dictionary have high sparsity. Images reconstructed with this dictionary were compared with those obtained with the three other common transforms, namely, discrete Fourier transform, discrete cosine transform, and discrete wavelet transform. The performance of the proposed dictionary was analyzed via a simulation and experimental data. The mean absolute error (MAE) was used to quantify the quality of the reconstructions. Experimental results indicate that the MAE associated with the proposed dictionary was always the smallest, the reconstruction time required was the shortest, and the lateral resolution and contrast of the reconstructed images were also the closest to the original images. The proposed sparse dictionary performed better than the other three sparse transforms. With the same sampling rate, the proposed dictionary achieved excellent reconstruction quality.

Health-related quality-of-life assessment and surgical outcomes for auricular reconstruction using autologous costal cartilage.

PubMed

Soukup, Benjamin; Mashhadi, Syed A; Bulstrode, Neil W

2012-03-01

This study aims to assess the health-related quality-of-life benefit following auricular reconstruction using autologous costal cartilage in children. In addition, key aspects of the surgical reconstruction are assessed. After auricular reconstruction, patients completed two questionnaires. The first was a postinterventional health-related quality-of-life assessment tool, the Glasgow Benefit Inventory. A score of 0 signifies no change in health-related quality-of-life, +100 indicates maximal improvement, and -100 indicates maximal negative impact. The second questionnaire assessed surgical outcomes in auricular reconstruction across three areas: facial integration, aesthetic auricular units, and costal reconstruction. These were recorded on a five-point ordinal scale and are presented as mean scores of a total of 5. The mean total Glasgow Benefit Inventory score was 48.1; significant improvements were seen in all three Glasgow Benefit Inventory subscales (p < 0.0001). A mean integration score of 3.8 and a mean aesthetic auricular unit reconstruction score of 3.4 were recorded. Skin color matching (4.3) of the ear was most successfully reconstructed and auricular cartilage reconstruction scored lowest (3.5). Of the aesthetic units, the helix scored highest (3.6) and the tragus/antitragus scored lowest (3.3). Donor-site reconstruction scored 3.9. Correlation analysis revealed that higher reconstruction scores are associated with a greater health-related quality-of-life gain (r = 0.5). Ninety-six percent of patients would recommend the procedure to a friend. Auricular reconstruction with autologous cartilage results in significant improvements in health-related quality-of-life. In addition, better surgical outcomes lead to a greater improvement in health-related quality-of-life. Comparatively poorer reconstructed areas of the ear were identified so that surgical techniques may be improved. Therapeutic, IV.

Path integration guided with a quality map for shape reconstruction in the fringe reflection technique

NASA Astrophysics Data System (ADS)

Jing, Xiaoli; Cheng, Haobo; Wen, Yongfu

2018-04-01

A new local integration algorithm called quality map path integration (QMPI) is reported for shape reconstruction in the fringe reflection technique. A quality map is proposed to evaluate the quality of gradient data locally, and functions as a guideline for the integrated path. The presented method can be employed in wavefront estimation from its slopes over the general shaped surface with slope noise equivalent to that in practical measurements. Moreover, QMPI is much better at handling the slope data with local noise, which may be caused by the irregular shapes of the surface under test. The performance of QMPI is discussed by simulations and experiment. It is shown that QMPI not only improves the accuracy of local integration, but can also be easily implemented with no iteration compared to Southwell zonal reconstruction (SZR). From an engineering point-of-view, the proposed method may also provide an efficient and stable approach for different shapes with high-precise demand.

Different types of implants for reconstructive breast surgery.

PubMed

Rocco, Nicola; Rispoli, Corrado; Moja, Lorenzo; Amato, Bruno; Iannone, Loredana; Testa, Serena; Spano, Andrea; Catanuto, Giuseppe; Accurso, Antonello; Nava, Maurizio B

2016-05-16

Breast cancer is the most common cancer in women worldwide, and is a leading cause of cancer death among women. Prophylactic or curative mastectomy is often followed by breast reconstruction for which there are several surgical approaches that use breast implants with which surgeons can restore the natural feel, size and shape of the breast. To assess the effects of different types of breast implants on capsular contracture, surgical short- and long-term complications, postoperative satisfaction level and quality of life in women who have undergone reconstructive breast surgery after mastectomy. We searched the Cochrane Breast Cancer Group's Specialised Register on 20 July 2015, MEDLINE (1985 to 20 July 2015), EMBASE (1985 to 20 July 2015) and the Cochrane Central Register of Controlled Trials (CENTRAL; Issue 8, 2015). We also searched the World Health Organization's International Clinical Trials Registry Platform (WHO ICTRP) and ClinicalTrials.gov on 16 July 2015. We included randomised controlled trials (RCTs) and quasi-RCTs that compared different types of breast implants for reconstructive surgery. We considered the following types of intervention: implant envelope surfaces - texturised versus smooth; implant filler material - silicone versus saline, PVP-Hydrogel versus saline; implant shape - anatomical versus round; implant volume - variable versus fixed; brands - different implant manufacturing companies and implant generation (fifth versus previous generations). Two review authors independently assessed methodological quality and extracted data. We used standard Cochrane methodological procedures. The quality of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Five RCTs with 202 participants met the inclusion criteria. The women participants were typically in their 50s, and the majority of them (about 82%) received reconstructive surgery following breast cancer, while the others had reconstructive surgery after prophylactic mastectomy. The studies were heterogenous in terms of implant comparisons, which prevented us from pooling the data.The studies were judged as being at an unclear risk of bias for most risk of bias items owing to poor quality of reporting in the trial publications. Three of the five RCTs were judged to be at high risk of attrition bias, and one at high risk of detection bias.Textured silicone versus smooth silicone implants: textured implants were associated with worse outcomes when compared to smooth implants (capsular contracture: risk ratio (RR) 0.82, 95% CI 0.14 to 4.71; 1 study, 20 participants; very low quality evidence; reintervention: RR 0.82, 95% CI 0.14 to 4.71; 1 study, 20 participants; very low quality evidence). No results in this comparison were statistically significant.Silicone versus saline implants: saline-filled implants performed better than silicone-filled implants for some outcomes; specifically, they produced less severe capsular contracture (RR 3.25, 95% CI 1.24 to 8.51; 1 study, 60 participants; very low quality evidence) and increased patient satisfaction (RR 0.60, 95% CI 0.41 to 0.88; 1 study, 58 participants; very low quality evidence). However reintervention was significantly more frequent in the saline-filled implant group than in the silicone-filled group (OR 0.08, 95% CI 0.01 to 0.43; 1 study, 60 participants; very low quality evidence).Poly(N-vinyl-2-pyrrolidone) hydrogel-filled (PVP-hydrogel) versus saline-filled implants: PVP-hydrogel-filled implants were associated with worse outcomes when compared to saline-filled implants (capsular contracture: RR 3.50, 95% CI 0.83 to 14.83; 1 study, 40 participants; very low quality evidence; short-term complications: RR 2.10, 95% CI 0.21 to 21.39; 1 study, 41 participants; very low quality evidence).Anatomical versus round implants: anatomical implants were associated with worse outcomes than round implants (capsular contracture: RR 2.00, 95% CI 0.20 to 20.15; 1 study, 36 participants; very low quality evidence; short-term complications: RR 2.00, 95% CI 0.42 to 9.58; 1 study, 36 participants; very low quality evidence; reintervention: RR 1.50, 95% CI 0.51 to 4.43; 1 study, 36 participants; very low quality evidence). No results in this comparison were statistically significant.Variable-volume versus fixed-volume implants: data about one-stage reconstruction using variable-volume implants were compared with data about fixed-volume implants positioned during the second surgical procedure of two-stage reconstructions. Fixed-volume implant reconstructions were possibly associated with a greater number of women reporting that their reconstruction corresponded with expected results (RR 0.25, 95% CI 0.10 to 0.62; 1 study, 40 participants; very low quality evidence) and fewer reinterventions (RR 7.00, 95% CI 1.82 to 26.89; 1 study, 40 participants; very low quality evidence) when compared to variable-volume implants. A higher patient satisfaction level (rated from 1 to 6, with 1 being very bad and 6 being very good) was found with the fixed-volume implants for overall aesthetic result (mean difference (MD) -1.10, 95% CI -1.59 to -0.61; 1 study, 40 participants; very low quality evidence).There were no studies that examined the effects of recent (fifth) generation silicone implants versus previous generations or different implant manufacturing companies. Despite the central role of breast reconstruction in women with breast cancer, the best implants to use in reconstructive surgery have been studied rarely in the context of RCTs. Furthermore the quality of these studies and the overall evidence they provide is largely unsatisfactory. Some of our results can be interpreted as early evidence of potentially large differences between different surgical approaches, which should be confirmed in new high-quality RCTs that include a larger number of women. These days - even after a few million women have had breasts reconstructed - surgeons cannot inform women about the risks and complications of different implant-based breast reconstructive options on the basis of results derived from RCTs.

Probabilistic Evaluation of Three-Dimensional Reconstructions from X-Ray Images Spanning a Limited Angle

PubMed Central

Frost, Anja; Renners, Eike; Hötter, Michael; Ostermann, Jörn

2013-01-01

An important part of computed tomography is the calculation of a three-dimensional reconstruction of an object from series of X-ray images. Unfortunately, some applications do not provide sufficient X-ray images. Then, the reconstructed objects no longer truly represent the original. Inside of the volumes, the accuracy seems to vary unpredictably. In this paper, we introduce a novel method to evaluate any reconstruction, voxel by voxel. The evaluation is based on a sophisticated probabilistic handling of the measured X-rays, as well as the inclusion of a priori knowledge about the materials that the object receiving the X-ray examination consists of. For each voxel, the proposed method outputs a numerical value that represents the probability of existence of a predefined material at the position of the voxel while doing X-ray. Such a probabilistic quality measure was lacking so far. In our experiment, false reconstructed areas get detected by their low probability. In exact reconstructed areas, a high probability predominates. Receiver Operating Characteristics not only confirm the reliability of our quality measure but also demonstrate that existing methods are less suitable for evaluating a reconstruction. PMID:23344378

Quality of life of patients who undergo breast reconstruction after mastectomy: effects of personality characteristics.

PubMed

Bellino, Silvio; Fenocchio, Marina; Zizza, Monica; Rocca, Giuseppe; Bogetti, Paolo; Bogetto, Filippo

2011-01-01

Reconstruction after mastectomy has become an integral part of breast cancer treatment. The effects of psychological factors on quality of life after reconstruction have been poorly investigated. The authors examined clinical and personality characteristics related to quality of life in patients receiving reconstructive surgery. All patients received immediate reconstruction and were evaluated in the week before tissue expander implantation (T0) with a semistructured interview for demographic and clinical characteristics, the Temperament and Character Inventory, the Inventory of Interpersonal Problems, the Short Form Health Survey, the Severity Item of the Clinical Global Impression, the Hamilton Depression Rating Scale, and the Hamilton Anxiety Rating Scale. Assessment with the Short Form was repeated 3 months after expander placement (T1). Statistics were calculated with univariate regression and analysis of variance. Significant variables were included in a multiple regression analysis to identify factors related to the change T1-T0 of the mean of the Short Form-transformed scores. Results were significant when p was less than or equal to 0.05. Fifty-seven women were enrolled. Results of multiple regression analysis showed that the Temperament and Character Inventory personality dimension harm avoidance and the Inventory of Interpersonal Problems domain vindictive/self-centered were significantly and independently related to the change in Short Form mean score. Personality dimensions and patterns of interpersonal functioning produce significant effects on patients' quality of life during breast reconstruction. Patients with high harm avoidance are apprehensive and doubtful. Restoration of body image could help them to reduce social anxiety and insecurity. Vindictive/self-centered patients are resentful and aggressive. Breast reconstruction could symbolize the conclusion of a reparative process and fulfill the desire of revenge on cancer.

Design and assessment of a novel SPECT system for desktop open-gantry imaging of small animals: A simulation study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeraatkar, Navid; Farahani, Mohammad Hossein; Rahmim, Arman

Purpose: Given increasing efforts in biomedical research utilizing molecular imaging methods, development of dedicated high-performance small-animal SPECT systems has been growing rapidly in the last decade. In the present work, we propose and assess an alternative concept for SPECT imaging enabling desktop open-gantry imaging of small animals. Methods: The system, PERSPECT, consists of an imaging desk, with a set of tilted detector and pinhole collimator placed beneath it. The object to be imaged is simply placed on the desk. Monte Carlo (MC) and analytical simulations were utilized to accurately model and evaluate the proposed concept and design. Furthermore, a dedicatedmore » image reconstruction algorithm, finite-aperture-based circular projections (FABCP), was developed and validated for the system, enabling more accurate modeling of the system and higher quality reconstructed images. Image quality was quantified as a function of different tilt angles in the acquisition and number of iterations in the reconstruction algorithm. Furthermore, more complex phantoms including Derenzo, Defrise, and mouse whole body were simulated and studied. Results: The sensitivity of the PERSPECT was 207 cps/MBq. It was quantitatively demonstrated that for a tilt angle of 30°, comparable image qualities were obtained in terms of normalized squared error, contrast, uniformity, noise, and spatial resolution measurements, the latter at ∼0.6 mm. Furthermore, quantitative analyses demonstrated that 3 iterations of FABCP image reconstruction (16 subsets/iteration) led to optimally reconstructed images. Conclusions: The PERSPECT, using a novel imaging protocol, can achieve comparable image quality performance in comparison with a conventional pinhole SPECT with the same configuration. The dedicated FABCP algorithm, which was developed for reconstruction of data from the PERSPECT system, can produce high quality images for small-animal imaging via accurate modeling of the system as incorporated in the forward- and back-projection steps. Meanwhile, the developed MC model and the analytical simulator of the system can be applied for further studies on development and evaluation of the system.« less

Developing a Theoretical Framework to Illustrate Associations Among Patient Satisfaction, Body Image and Quality of Life for Women Undergoing Breast Reconstruction

PubMed Central

Fingeret, Michelle Cororve; Nipomnick, Summer; Crosby, Melissa A.; Reece, Gregory P.

2013-01-01

Within the field of breast reconstruction there is increasing focus on patient-reported outcomes related to satisfaction, body image, and quality of life. These outcomes are deemed highly relevant because the primary goal of breast reconstruction is to recreate the appearance of a breast (or breasts) that is satisfying to the patient. Prominent researchers have suggested the need to develop improved standards for outcome evaluation which can ultimately benefit patients as well as physicians. The purpose of this article is to summarize key findings in the area of patient-reported outcomes for breast reconstruction and introduce a theoretical framework for advancing research in this field. We conducted an extensive literature review of outcome studies for breast reconstruction focusing on patient-reported results. We developed a theoretical framework illustrating core patient-reported outcomes related to breast reconstruction and factors associated with these outcomes. Our theoretical model highlights domains and distinguishing features of patient satisfaction, body image, and quality of life outcomes for women undergoing breast reconstruction. This model further identifies a broad range of variables (e.g., historical/premorbid influences, disease and treatment-related factors) that have been found to influence patient-reported outcomes and need to be taken into consideration when designing future research in this area. Additional attention is given to examining the relationship between patient reported outcomes and outside evaluation of breast reconstruction. Our proposed theoretical framework suggests key opportunities to expand research in this area with the goal of optimizing body image adjustment, satisfaction, and psychosocial outcomes for the individual patient. PMID:23380309

Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Shiyu, E-mail: shiyu.xu@gmail.com; Chen, Ying, E-mail: adachen@siu.edu; Lu, Jianping

2015-09-15

Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair basedmore » prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.« less

High-speed parallel implementation of a modified PBR algorithm on DSP-based EH topology

NASA Astrophysics Data System (ADS)

Rajan, K.; Patnaik, L. M.; Ramakrishna, J.

1997-08-01

Algebraic Reconstruction Technique (ART) is an age-old method used for solving the problem of three-dimensional (3-D) reconstruction from projections in electron microscopy and radiology. In medical applications, direct 3-D reconstruction is at the forefront of investigation. The simultaneous iterative reconstruction technique (SIRT) is an ART-type algorithm with the potential of generating in a few iterations tomographic images of a quality comparable to that of convolution backprojection (CBP) methods. Pixel-based reconstruction (PBR) is similar to SIRT reconstruction, and it has been shown that PBR algorithms give better quality pictures compared to those produced by SIRT algorithms. In this work, we propose a few modifications to the PBR algorithms. The modified algorithms are shown to give better quality pictures compared to PBR algorithms. The PBR algorithm and the modified PBR algorithms are highly compute intensive, Not many attempts have been made to reconstruct objects in the true 3-D sense because of the high computational overhead. In this study, we have developed parallel two-dimensional (2-D) and 3-D reconstruction algorithms based on modified PBR. We attempt to solve the two problems encountered by the PBR and modified PBR algorithms, i.e., the long computational time and the large memory requirements, by parallelizing the algorithm on a multiprocessor system. We investigate the possible task and data partitioning schemes by exploiting the potential parallelism in the PBR algorithm subject to minimizing the memory requirement. We have implemented an extended hypercube (EH) architecture for the high-speed execution of the 3-D reconstruction algorithm using the commercially available fast floating point digital signal processor (DSP) chips as the processing elements (PEs) and dual-port random access memories (DPR) as channels between the PEs. We discuss and compare the performances of the PBR algorithm on an IBM 6000 RISC workstation, on a Silicon Graphics Indigo 2 workstation, and on an EH system. The results show that an EH(3,1) using DSP chips as PEs executes the modified PBR algorithm about 100 times faster than an LBM 6000 RISC workstation. We have executed the algorithms on a 4-node IBM SP2 parallel computer. The results show that execution time of the algorithm on an EH(3,1) is better than that of a 4-node IBM SP2 system. The speed-up of an EH(3,1) system with eight PEs and one network controller is approximately 7.85.

Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models

PubMed Central

Got, Jeanne; Cortés, María Paz; Maass, Alejandro

2018-01-01

Genome-scale metabolic models have become the tool of choice for the global analysis of microorganism metabolism, and their reconstruction has attained high standards of quality and reliability. Improvements in this area have been accompanied by the development of some major platforms and databases, and an explosion of individual bioinformatics methods. Consequently, many recent models result from “à la carte” pipelines, combining the use of platforms, individual tools and biological expertise to enhance the quality of the reconstruction. Although very useful, introducing heterogeneous tools, that hardly interact with each other, causes loss of traceability and reproducibility in the reconstruction process. This represents a real obstacle, especially when considering less studied species whose metabolic reconstruction can greatly benefit from the comparison to good quality models of related organisms. This work proposes an adaptable workspace, AuReMe, for sustainable reconstructions or improvements of genome-scale metabolic models involving personalized pipelines. At each step, relevant information related to the modifications brought to the model by a method is stored. This ensures that the process is reproducible and documented regardless of the combination of tools used. Additionally, the workspace establishes a way to browse metabolic models and their metadata through the automatic generation of ad-hoc local wikis dedicated to monitoring and facilitating the process of reconstruction. AuReMe supports exploration and semantic query based on RDF databases. We illustrate how this workspace allowed handling, in an integrated way, the metabolic reconstructions of non-model organisms such as an extremophile bacterium or eukaryote algae. Among relevant applications, the latter reconstruction led to putative evolutionary insights of a metabolic pathway. PMID:29791443

The Cost-Effectiveness of Anterior Cruciate Ligament Reconstruction in Competitive Athletes.

PubMed

Stewart, Bruce A; Momaya, Amit M; Silverstein, Marc D; Lintner, David

2017-01-01

Competitive athletes value the ability to return to competitive play after the treatment of anterior cruciate ligament (ACL) injuries. ACL reconstruction has high success rates for return to play, but some studies indicate that patients may do well with nonoperative physical therapy treatment. To evaluate the cost-effectiveness of the treatment of acute ACL tears with either initial surgical reconstruction or physical therapy in competitive athletes. Economic and decision analysis; Level of evidence, 2. The incremental cost, incremental effectiveness, and incremental cost-effectiveness ratio (ICER) of ACL reconstruction compared with physical therapy were calculated from a cost-effectiveness analysis of ACL reconstruction compared with physical therapy for the initial management of acute ACL injuries in competitive athletes. The ACL reconstruction strategy and the physical therapy strategy were represented as Markov models. Costs and quality-adjusted life-years (QALYs) were evaluated over a 6-year time horizon and were analyzed from a societal perspective. Quality of life and probabilities of clinical outcomes were obtained from the peer-reviewed literature, and costs were compiled from a large academic hospital in the United States. One-way, 2-way, and probabilistic sensitivity analyses were used to assess the effect of uncertainty in variables on the ICER of ACL reconstruction. The ICER of ACL reconstruction compared with physical therapy was $22,702 per QALY gained. The ICER was most sensitive to the quality of life of returning to play or not returning to play, costs, and duration of follow-up but relatively insensitive to the rates and costs of complications, probabilities of return to play for both operative and nonoperative treatments, and discount rate. ACL reconstruction is a cost-effective strategy for competitive athletes with an ACL injury.

Long-Term Follow-Up of Quality of Life following DIEP Flap Breast Reconstruction.

PubMed

Hunsinger, Vincent; Hivelin, Mikael; Derder, Mohamed; Klein, Delphine; Velten, Michel; Lantieri, Laurent

2016-05-01

Sequelae resulting from breast cancer negatively impact patients' quality of life. Although the deep inferior epigastric perforator (DIEP) flap has become a standard for autologous breast reconstruction, there are limited data regarding long-term quality of life. The authors studied patients' quality of life more than 5 years after DIEP flap breast reconstruction and compare it with two French reference samples. A cross-sectional study of quality of life was performed in women who underwent DIEP flap breast reconstruction between 1995 and 2007 using the Medical Outcomes Study 36-Item Health Survey (Short Form-36). The first reference sample included subjects from the French general population (n = 3308), and the second included cancer survivors who underwent mastectomy with (n = 70) or without (n = 135) breast reconstruction. One hundred eleven respondents were analyzed among 186 eligible women. The mean follow-up period after reconstruction was 8.6 years (range, 5 to 15 years). There were no statistically significant differences in the quality of life between women from 45 to 64 years old who underwent DIEP flap breast reconstruction and from the French general population. Five of the eight Short Form-36 dimensions were significantly better in the DIEP flap breast reconstruction group in the 65- to 74-year-old cohort. In addition, quality of life of our study population was significantly higher than that of women who underwent mastectomy with or without any type of breast reconstruction. These results indicate that DIEP flap breast reconstruction allows patients with breast cancer to maintain a good postoperative quality of life comparable to that of the general population. Therapeutic, III.

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.

PubMed

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC.

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method

PubMed Central

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC. PMID:28005929

Intraoperative Nerve Blocks Fail to Improve Quality of Recovery after Tissue Expander Breast Reconstruction: A Prospective, Double-Blinded, Randomized, Placebo-Controlled Clinical Trial.

PubMed

Lanier, Steven T; Lewis, Kevin C; Kendall, Mark C; Vieira, Brittany L; De Oliveira, Gildasio; Nader, Anthony; Kim, John Y S; Alghoul, Mohammed

2018-03-01

The authors' study represents the first level I evidence to assess whether intraoperative nerve blocks improve the quality of recovery from immediate tissue expander/implant breast reconstruction. A prospective, randomized, double-blinded, placebo-controlled clinical trial was conducted in which patients undergoing immediate tissue expander/implant breast reconstruction were randomized to either (1) intraoperative intercostal and pectoral nerve blocks with 0.25% bupivacaine with 1:200,000 epinephrine and 4 mg of dexamethasone or (2) sham nerve blocks with normal saline. The 40-item Quality of Recovery score, pain score, and opioid use in the postoperative period were compared statistically between groups. Power analysis ensured 80 percent power to detect a 10-point (clinically significant) difference in the 40-item Quality of Recovery score. Forty-seven patients were enrolled. Age, body mass index, laterality, mastectomy type, and lymph node dissection were similar between groups. There were no statistical differences in quality of recovery, pain burden as measured by visual analogue scale, opioid consumption, antiemetic use, or length of hospital stay between groups at 24 hours after surgery. Mean global 40-item Quality of Recovery scores were 169 (range, 155 to 182) for the treatment arm and 165 (range, 143 to 179) for the placebo arm (p = 0.36), indicating a high quality of recovery in both groups. Although intraoperative nerve blocks can be a safe adjunct to a comprehensive postsurgical recovery regimen, the authors' results indicate no effect on overall quality of recovery from tissue expander/implant breast reconstruction. Therapeutic, I.

The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique.

PubMed

Kwon, Heejin; Cho, Jinhan; Oh, Jongyeong; Kim, Dongwon; Cho, Junghyun; Kim, Sanghyun; Lee, Sangyun; Lee, Jihyun

2015-10-01

To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. 27 consecutive patients (mean body mass index: 23.55 kg m(-2) underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19-49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. This study represents the first clinical research experiment to use ASIR-V, the newest version of iterative reconstruction. Use of the ASIR-V algorithm decreased image noise and increased image quality when compared with the ASIR and FBP methods. These results suggest that high-quality low-dose CT may represent a new clinical option.

The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique

PubMed Central

Cho, Jinhan; Oh, Jongyeong; Kim, Dongwon; Cho, Junghyun; Kim, Sanghyun; Lee, Sangyun; Lee, Jihyun

2015-01-01

Objective: To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. Methods: 27 consecutive patients (mean body mass index: 23.55 kg m−2 underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. Results: At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19–49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Conclusion: Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. Advances in knowledge: This study represents the first clinical research experiment to use ASIR-V, the newest version of iterative reconstruction. Use of the ASIR-V algorithm decreased image noise and increased image quality when compared with the ASIR and FBP methods. These results suggest that high-quality low-dose CT may represent a new clinical option. PMID:26234823

Flying qualities criteria for GA single pilot IFR operations

NASA Technical Reports Server (NTRS)

Bar-Gill, A.

1982-01-01

The flying qualities criteria in general aviation (GA) to decrease accidents are discussed. The following in-flight research is discussed: (1) identification of key aerodynamic configurations; (2) implementation of an in-flight simulator; (3) mission matrix design; (4) experimental systems; (5) data reduction; (6) optimal flight path reconstruction. Some of the accomplished work is reported: an integrated flight testing and flight path reconstruction methodology was developd, high accuracy in trajectory estimation was achieved with an experimental setup, and a part of the flight test series was flown.

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.

PubMed

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.

Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

NASA Astrophysics Data System (ADS)

Dostal, P.; Krasula, L.; Klima, M.

2012-06-01

Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

Region of interest processing for iterative reconstruction in x-ray computed tomography

NASA Astrophysics Data System (ADS)

Kopp, Felix K.; Nasirudin, Radin A.; Mei, Kai; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Noël, Peter B.

2015-03-01

The recent advancements in the graphics card technology raised the performance of parallel computing and contributed to the introduction of iterative reconstruction methods for x-ray computed tomography in clinical CT scanners. Iterative maximum likelihood (ML) based reconstruction methods are known to reduce image noise and to improve the diagnostic quality of low-dose CT. However, iterative reconstruction of a region of interest (ROI), especially ML based, is challenging. But for some clinical procedures, like cardiac CT, only a ROI is needed for diagnostics. A high-resolution reconstruction of the full field of view (FOV) consumes unnecessary computation effort that results in a slower reconstruction than clinically acceptable. In this work, we present an extension and evaluation of an existing ROI processing algorithm. Especially improvements for the equalization between regions inside and outside of a ROI are proposed. The evaluation was done on data collected from a clinical CT scanner. The performance of the different algorithms is qualitatively and quantitatively assessed. Our solution to the ROI problem provides an increase in signal-to-noise ratio and leads to visually less noise in the final reconstruction. The reconstruction speed of our technique was observed to be comparable with other previous proposed techniques. The development of ROI processing algorithms in combination with iterative reconstruction will provide higher diagnostic quality in the near future.

Improvement of cardiac CT reconstruction using local motion vector fields.

PubMed

Schirra, Carsten Oliver; Bontus, Claas; van Stevendaal, Udo; Dössel, Olaf; Grass, Michael

2009-03-01

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

Influence of adaptive statistical iterative reconstruction algorithm on image quality in coronary computed tomography angiography

PubMed Central

Thygesen, Jesper; Gerke, Oke; Egstrup, Kenneth; Waaler, Dag; Lambrechtsen, Jess

2016-01-01

Background Coronary computed tomography angiography (CCTA) requires high spatial and temporal resolution, increased low contrast resolution for the assessment of coronary artery stenosis, plaque detection, and/or non-coronary pathology. Therefore, new reconstruction algorithms, particularly iterative reconstruction (IR) techniques, have been developed in an attempt to improve image quality with no cost in radiation exposure. Purpose To evaluate whether adaptive statistical iterative reconstruction (ASIR) enhances perceived image quality in CCTA compared to filtered back projection (FBP). Material and Methods Thirty patients underwent CCTA due to suspected coronary artery disease. Images were reconstructed using FBP, 30% ASIR, and 60% ASIR. Ninety image sets were evaluated by five observers using the subjective visual grading analysis (VGA) and assessed by proportional odds modeling. Objective quality assessment (contrast, noise, and the contrast-to-noise ratio [CNR]) was analyzed with linear mixed effects modeling on log-transformed data. The need for ethical approval was waived by the local ethics committee as the study only involved anonymously collected clinical data. Results VGA showed significant improvements in sharpness by comparing FBP with ASIR, resulting in odds ratios of 1.54 for 30% ASIR and 1.89 for 60% ASIR (P = 0.004). The objective measures showed significant differences between FBP and 60% ASIR (P < 0.0001) for noise, with an estimated ratio of 0.82, and for CNR, with an estimated ratio of 1.26. Conclusion ASIR improved the subjective image quality of parameter sharpness and, objectively, reduced noise and increased CNR. PMID:28405477

Poster — Thur Eve — 01: The effect of the number of projections on MTF and CNR in Compton scatter tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chighvinadze, T; Pistorius, S; CancerCare Manitoba, Winnipeg, MB

2014-08-15

Purpose: To investigate the dependence of the reconstructed image quality on the number of projections in multi-projection Compton scatter tomography (MPCST). The conventional relationship between the projection number used for reconstruction and reconstructed image quality pertained to CT does not necessarily apply to MPCST, which can produce images from a single projection if the detectors have sufficiently high energy and spatial resolution. Methods: The electron density image was obtained using filtered-backprojection of the scatter signal over circular arcs formed using Compton equation. The behavior of the reconstructed image quality as a function of the projection number was evaluated through analyticalmore » simulations and characterized by CNR and MTF. Results: The increase of the projection number improves the contrast with this dependence being a function of fluence. The number of projections required to approach the asymptotic maximum contrast decreases as the fluence increases. Increasing projection number increases the CNR but not spatial resolution. Conclusions: For MPCST using a 500eV energy resolution and a 2×2mm{sup 2} size detector, an adequate image quality can be obtained with a small number of projections provided the incident fluence is high enough. This is conceptually different from conventional CT where a minimum number of projections is required to obtain an adequate image quality. While increasing projection number, even for the lowest dose value, the CNR increases even though the number of photons per projection decreases. The spatial resolution of the image is improved by increasing the sampling within a projection rather than by increasing the number of projections.« less

A Comparison of Affect Ratings Obtained with Ecological Momentary Assessment and the Day Reconstruction Method

ERIC Educational Resources Information Center

Dockray, Samantha; Grant, Nina; Stone, Arthur A.; Kahneman, Daniel; Wardle, Jane; Steptoe, Andrew

2010-01-01

Measurement of affective states in everyday life is of fundamental importance in many types of quality of life, health, and psychological research. Ecological momentary assessment (EMA) is the recognized method of choice, but the respondent burden can be high. The day reconstruction method (DRM) was developed by Kahneman and colleagues ("Science,"…

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

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

PubMed

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 provide a more confident and accurate diagnosis for necrotizing pneumonia.

Study on the key technology of optical encryption based on compressive ghost imaging with double random-phase encoding

NASA Astrophysics Data System (ADS)

Zhang, Leihong; Pan, Zilan; Liang, Dong; Ma, Xiuhua; Zhang, Dawei

2015-12-01

An optical encryption method based on compressive ghost imaging (CGI) with double random-phase encoding (DRPE), named DRPE-CGI, is proposed. The information is first encrypted by the sender with DRPE, the DRPE-coded image is encrypted by the system of computational ghost imaging with a secret key. The key of N random-phase vectors is generated by the sender and will be shared with the receiver who is the authorized user. The receiver decrypts the DRPE-coded image with the key, with the aid of CGI and a compressive sensing technique, and then reconstructs the original information by the technique of DRPE-decoding. The experiments suggest that cryptanalysts cannot get any useful information about the original image even if they eavesdrop 60% of the key at a given time, so the security of DRPE-CGI is higher than that of the security of conventional ghost imaging. Furthermore, this method can reduce 40% of the information quantity compared with ghost imaging while the qualities of reconstructing the information are the same. It can also improve the quality of the reconstructed plaintext information compared with DRPE-GI with the same sampling times. This technique can be immediately applied to encryption and data storage with the advantages of high security, fast transmission, and high quality of reconstructed information.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Pan, X; Stayman, J

2014-06-15

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

Characterization of the reference wave in a compact digital holographic camera.

PubMed

Park, I S; Middleton, R J C; Coggrave, C R; Ruiz, P D; Coupland, J M

2018-01-01

A hologram is a recording of the interference between an unknown object wave and a coherent reference wave. Providing the object and reference waves are sufficiently separated in some region of space and the reference beam is known, a high-fidelity reconstruction of the object wave is possible. In traditional optical holography, high-quality reconstruction is achieved by careful reillumination of the holographic plate with the exact same reference wave that was used at the recording stage. To reconstruct high-quality digital holograms the exact parameters of the reference wave must be known mathematically. This paper discusses a technique that obtains the mathematical parameters that characterize a strongly divergent reference wave that originates from a fiber source in a new compact digital holographic camera. This is a lensless design that is similar in principle to a Fourier hologram, but because of the large numerical aperture, the usual paraxial approximations cannot be applied and the Fourier relationship is inexact. To characterize the reference wave, recordings of quasi-planar object waves are made at various angles of incidence using a Dammann grating. An optimization process is then used to find the reference wave that reconstructs a stigmatic image of the object wave regardless of the angle of incidence.

Fast high resolution reconstruction in multi-slice and multi-view cMRI

NASA Astrophysics Data System (ADS)

Velasco Toledo, Nelson; Romero Castro, Eduardo

2015-01-01

Cardiac magnetic resonance imaging (cMRI) is an useful tool in diagnosis, prognosis and research since it functionally tracks the heart structure. Although useful, this imaging technique is limited in spatial resolution because heart is a constant moving organ, also there are other non controled conditions such as patient movements and volumetric changes during apnea periods when data is acquired, those conditions limit the time to capture high quality information. This paper presents a very fast and simple strategy to reconstruct high resolution 3D images from a set of low resolution series of 2D images. The strategy is based on an information reallocation algorithm which uses the DICOM header to relocate voxel intensities in a regular grid. An interpolation method is applied to fill empty places with estimated data, the interpolation resamples the low resolution information to estimate the missing information. As a final step a gaussian filter that denoises the final result. A reconstructed image evaluation is performed using as a reference a super-resolution reconstructed image. The evaluation reveals that the method maintains the general heart structure with a small loss in detailed information (edge sharpening and blurring), some artifacts related with input information quality are detected. The proposed method requires low time and computational resources.

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

NASA Astrophysics Data System (ADS)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

Analysis on the Effect of Sensor Views in Image Reconstruction Produced by Optical Tomography System Using Charge-Coupled Device.

PubMed

Jamaludin, Juliza; Rahim, Ruzairi Abdul; Fazul Rahiman, Mohd Hafiz; Mohd Rohani, Jemmy

2018-04-01

Optical tomography (OPT) is a method to capture a cross-sectional image based on the data obtained by sensors, distributed around the periphery of the analyzed system. This system is based on the measurement of the final light attenuation or absorption of radiation after crossing the measured objects. The number of sensor views will affect the results of image reconstruction, where the high number of sensor views per projection will give a high image quality. This research presents an application of charge-coupled device linear sensor and laser diode in an OPT system. Experiments in detecting solid and transparent objects in crystal clear water were conducted. Two numbers of sensors views, 160 and 320 views are evaluated in this research in reconstructing the images. The image reconstruction algorithms used were filtered images of linear back projection algorithms. Analysis on comparing the simulation and experiments image results shows that, with 320 image views giving less area error than 160 views. This suggests that high image view resulted in the high resolution of image reconstruction.

Image quality of low-dose CCTA in obese patients: impact of high-definition computed tomography and adaptive statistical iterative reconstruction.

PubMed

Gebhard, Cathérine; Fuchs, Tobias A; Fiechter, Michael; Stehli, Julia; Stähli, Barbara E; Gaemperli, Oliver; Kaufmann, Philipp A

2013-10-01

The accuracy of coronary computed tomography angiography (CCTA) in obese persons is compromised by increased image noise. We investigated CCTA image quality acquired on a high-definition 64-slice CT scanner using modern adaptive statistical iterative reconstruction (ASIR). Seventy overweight and obese patients (24 males; mean age 57 years, mean body mass index 33 kg/m(2)) were studied with clinically-indicated contrast enhanced CCTA. Thirty-five patients underwent a standard definition protocol with filtered backprojection reconstruction (SD-FBP) while 35 patients matched for gender, age, body mass index and coronary artery calcifications underwent a novel high definition protocol with ASIR (HD-ASIR). Segment by segment image quality was assessed using a four-point scale (1 = excellent, 2 = good, 3 = moderate, 4 = non-diagnostic) and revealed better scores for HD-ASIR compared to SD-FBP (1.5 ± 0.43 vs. 1.8 ± 0.48; p < 0.05). The smallest detectable vessel diameter was also improved, 1.0 ± 0.5 mm for HD-ASIR as compared to 1.4 ± 0.4 mm for SD-FBP (p < 0.001). Average vessel attenuation was higher for HD-ASIR (388.3 ± 109.6 versus 350.6 ± 90.3 Hounsfield Units, HU; p < 0.05), while image noise, signal-to-noise ratio and contrast-to noise ratio did not differ significantly between reconstruction protocols (p = NS). The estimated effective radiation doses were similar, 2.3 ± 0.1 and 2.5 ± 0.1 mSv (HD-ASIR vs. SD-ASIR respectively). Compared to a standard definition backprojection protocol (SD-FBP), a newer high definition scan protocol in combination with ASIR (HD-ASIR) incrementally improved image quality and visualization of distal coronary artery segments in overweight and obese individuals, without increasing image noise and radiation dose.

K-space reconstruction with anisotropic kernel support (KARAOKE) for ultrafast partially parallel imaging.

PubMed

Miao, Jun; Wong, Wilbur C K; Narayan, Sreenath; Wilson, David L

2011-11-01

Partially parallel imaging (PPI) greatly accelerates MR imaging by using surface coil arrays and under-sampling k-space. However, the reduction factor (R) in PPI is theoretically constrained by the number of coils (N(C)). A symmetrically shaped kernel is typically used, but this often prevents even the theoretically possible R from being achieved. Here, the authors propose a kernel design method to accelerate PPI faster than R = N(C). K-space data demonstrates an anisotropic pattern that is correlated with the object itself and to the asymmetry of the coil sensitivity profile, which is caused by coil placement and B(1) inhomogeneity. From spatial analysis theory, reconstruction of such pattern is best achieved by a signal-dependent anisotropic shape kernel. As a result, the authors propose the use of asymmetric kernels to improve k-space reconstruction. The authors fit a bivariate Gaussian function to the local signal magnitude of each coil, then threshold this function to extract the kernel elements. A perceptual difference model (Case-PDM) was employed to quantitatively evaluate image quality. A MR phantom experiment showed that k-space anisotropy increased as a function of magnetic field strength. The authors tested a K-spAce Reconstruction with AnisOtropic KErnel support ("KARAOKE") algorithm with both MR phantom and in vivo data sets, and compared the reconstructions to those produced by GRAPPA, a popular PPI reconstruction method. By exploiting k-space anisotropy, KARAOKE was able to better preserve edges, which is particularly useful for cardiac imaging and motion correction, while GRAPPA failed at a high R near or exceeding N(C). KARAOKE performed comparably to GRAPPA at low Rs. As a rule of thumb, KARAOKE reconstruction should always be used for higher quality k-space reconstruction, particularly when PPI data is acquired at high Rs and/or high field strength.

K-space reconstruction with anisotropic kernel support (KARAOKE) for ultrafast partially parallel imaging

PubMed Central

Miao, Jun; Wong, Wilbur C. K.; Narayan, Sreenath; Wilson, David L.

2011-01-01

Purpose: Partially parallel imaging (PPI) greatly accelerates MR imaging by using surface coil arrays and under-sampling k-space. However, the reduction factor (R) in PPI is theoretically constrained by the number of coils (NC). A symmetrically shaped kernel is typically used, but this often prevents even the theoretically possible R from being achieved. Here, the authors propose a kernel design method to accelerate PPI faster than R = NC. Methods: K-space data demonstrates an anisotropic pattern that is correlated with the object itself and to the asymmetry of the coil sensitivity profile, which is caused by coil placement and B1 inhomogeneity. From spatial analysis theory, reconstruction of such pattern is best achieved by a signal-dependent anisotropic shape kernel. As a result, the authors propose the use of asymmetric kernels to improve k-space reconstruction. The authors fit a bivariate Gaussian function to the local signal magnitude of each coil, then threshold this function to extract the kernel elements. A perceptual difference model (Case-PDM) was employed to quantitatively evaluate image quality. Results: A MR phantom experiment showed that k-space anisotropy increased as a function of magnetic field strength. The authors tested a K-spAce Reconstruction with AnisOtropic KErnel support (“KARAOKE”) algorithm with both MR phantom and in vivo data sets, and compared the reconstructions to those produced by GRAPPA, a popular PPI reconstruction method. By exploiting k-space anisotropy, KARAOKE was able to better preserve edges, which is particularly useful for cardiac imaging and motion correction, while GRAPPA failed at a high R near or exceeding NC. KARAOKE performed comparably to GRAPPA at low Rs. Conclusions: As a rule of thumb, KARAOKE reconstruction should always be used for higher quality k-space reconstruction, particularly when PPI data is acquired at high Rs and∕or high field strength. PMID:22047378

Breast reconstruction post mastectomy- Let's Google it. Accessibility, readability and quality of online information.

PubMed

Lynch, Noel P; Lang, Bronagh; Angelov, Sophia; McGarrigle, Sarah A; Boyle, Terence J; Al-Azawi, Dhafir; Connolly, Elizabeth M

2017-04-01

This study evaluated the readability, accessibility and quality of information pertaining to breast reconstruction post mastectomy on the Internet in the English language. Using the Google © search engine the keywords "Breast reconstruction post mastectomy" were searched for. We analyzed the top 75 sites. The Flesch Reading Ease Score and Gunning Fog Index were calculated to assess readability. Web site quality was assessed objectively using the University of Michigan Consumer Health Web site Evaluation Checklist. Accessibility was determined using an automated accessibility tool. In addition, the country of origin, type of organisation producing the site and presence of Health on the Net (HoN) Certification status was recorded. The Web sites were difficult to read and comprehend. The mean Flesch Reading Ease scores were 55.5. The mean Gunning Fog Index scores was 8.6. The mean Michigan score was 34.8 indicating weak quality of websites. Websites with HoN certification ranked higher in the search results (p = 0.007). Website quality was influenced by organisation type (p < 0.0001) with academic/healthcare, not for profit and government sites having higher Michigan scores. 20% of sites met the minimum accessibility criteria. Internet information on breast reconstruction post mastectomy and procedures is poorly written and we suggest that Webpages providing information must be made more readable and accessible. We suggest that health professionals should recommend Web sites that are easy to read and contain high-quality surgical information. Medical information on the Internet should be readable, accessible, reliable and of a consistent quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

3D Reconstruction of human bones based on dictionary learning.

PubMed

Zhang, Binkai; Wang, Xiang; Liang, Xiao; Zheng, Jinjin

2017-11-01

An effective method for reconstructing a 3D model of human bones from computed tomography (CT) image data based on dictionary learning is proposed. In this study, the dictionary comprises the vertices of triangular meshes, and the sparse coefficient matrix indicates the connectivity information. For better reconstruction performance, we proposed a balance coefficient between the approximation and regularisation terms and a method for optimisation. Moreover, we applied a local updating strategy and a mesh-optimisation method to update the dictionary and the sparse matrix, respectively. The two updating steps are iterated alternately until the objective function converges. Thus, a reconstructed mesh could be obtained with high accuracy and regularisation. The experimental results show that the proposed method has the potential to obtain high precision and high-quality triangular meshes for rapid prototyping, medical diagnosis, and tissue engineering. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Developing a theoretical framework to illustrate associations among patient satisfaction, body image and quality of life for women undergoing breast reconstruction.

PubMed

Fingeret, Michelle Cororve; Nipomnick, Summer W; Crosby, Melissa A; Reece, Gregory P

2013-10-01

Within the field of breast reconstruction there is increasing focus on patient-reported outcomes related to satisfaction, body image, and quality of life. These outcomes are deemed highly relevant because the primary goal of breast reconstruction is to recreate the appearance of a breast (or breasts) that is satisfying to the patient. Prominent researchers have suggested the need to develop improved standards for outcome evaluation which can ultimately benefit patients as well as physicians. The purpose of this article is to summarize key findings in the area of patient-reported outcomes for breast reconstruction and introduce a theoretical framework for advancing research in this field. We conducted an extensive literature review of outcome studies for breast reconstruction focusing on patient-reported results. We developed a theoretical framework illustrating core patient-reported outcomes related to breast reconstruction and factors associated with these outcomes. Our theoretical model highlights domains and distinguishing features of patient satisfaction, body image, and quality of life outcomes for women undergoing breast reconstruction. This model further identifies a broad range of variables (e.g., historical/premorbid influences, disease and treatment-related factors) that have been found to influence patient-reported outcomes and need to be taken into consideration when designing future research in this area. Additional attention is given to examining the relationship between patient reported outcomes and outside evaluation of breast reconstruction. Our proposed theoretical framework suggests key opportunities to expand research in this area with the goal of optimizing body image adjustment, satisfaction, and psychosocial outcomes for the individual patient. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Two-Stage Framework for 3D Face Reconstruction from RGBD Images.

PubMed

Wang, Kangkan; Wang, Xianwang; Pan, Zhigeng; Liu, Kai

2014-08-01

This paper proposes a new approach for 3D face reconstruction with RGBD images from an inexpensive commodity sensor. The challenges we face are: 1) substantial random noise and corruption are present in low-resolution depth maps; and 2) there is high degree of variability in pose and face expression. We develop a novel two-stage algorithm that effectively maps low-quality depth maps to realistic face models. Each stage is targeted toward a certain type of noise. The first stage extracts sparse errors from depth patches through the data-driven local sparse coding, while the second stage smooths noise on the boundaries between patches and reconstructs the global shape by combining local shapes using our template-based surface refinement. Our approach does not require any markers or user interaction. We perform quantitative and qualitative evaluations on both synthetic and real test sets. Experimental results show that the proposed approach is able to produce high-resolution 3D face models with high accuracy, even if inputs are of low quality, and have large variations in viewpoint and face expression.

Forward and backward tone mapping of high dynamic range images based on subband architecture

NASA Astrophysics Data System (ADS)

Bouzidi, Ines; Ouled Zaid, Azza

2015-01-01

This paper presents a novel High Dynamic Range (HDR) tone mapping (TM) system based on sub-band architecture. Standard wavelet filters of Daubechies, Symlets, Coiflets and Biorthogonal were used to estimate the proposed system performance in terms of Low Dynamic Range (LDR) image quality and reconstructed HDR image fidelity. During TM stage, the HDR image is firstly decomposed in sub-bands using symmetrical analysis-synthesis filter bank. The transform coefficients are then rescaled using a predefined gain map. The inverse Tone Mapping (iTM) stage is straightforward. Indeed, the LDR image passes through the same sub-band architecture. But, instead of reducing the dynamic range, the LDR content is boosted to an HDR representation. Moreover, in our TM sheme, we included an optimization module to select the gain map components that minimize the reconstruction error, and consequently resulting in high fidelity HDR content. Comparisons with recent state-of-the-art methods have shown that our method provides better results in terms of visual quality and HDR reconstruction fidelity using objective and subjective evaluations.

Contrast adaptive total p-norm variation minimization approach to CT reconstruction for artifact reduction in reduced-view brain perfusion CT

NASA Astrophysics Data System (ADS)

Kim, Chang-Won; Kim, Jong-Hyo

2011-03-01

Perfusion CT (PCT) examinations are getting more frequently used for diagnosis of acute brain diseases such as hemorrhage and infarction, because the functional map images it produces such as regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), and mean transit time (MTT) may provide critical information in the emergency work-up of patient care. However, a typical PCT scans the same slices several tens of times after injection of contrast agent, which leads to much increased radiation dose and is inevitability of growing concern for radiation-induced cancer risk. Reducing the number of views in projection in combination of TV minimization reconstruction technique is being regarded as an option for radiation reduction. However, reconstruction artifacts due to insufficient number of X-ray projections become problematic especially when high contrast enhancement signals are present or patient's motion occurred. In this study, we present a novel reconstruction technique using contrast-adaptive TpV minimization that can reduce reconstruction artifacts effectively by using different p-norms in high contrast and low contrast objects. In the proposed method, high contrast components are first reconstructed using thresholded projection data and low p-norm total variation to reflect sparseness in both projection and reconstruction spaces. Next, projection data are modified to contain only low contrast objects by creating projection data of reconstructed high contrast components and subtracting them from original projection data. Then, the low contrast projection data are reconstructed by using relatively high p-norm TV minimization technique, and are combined with the reconstructed high contrast component images to produce final reconstructed images. The proposed algorithm was applied to numerical phantom and a clinical data set of brain PCT exam, and the resultant images were compared with those using filtered back projection (FBP) and conventional TV reconstruction algorithm. Our results show the potential of the proposed algorithm for image quality improvement, which in turn may lead to dose reduction.

Evidence-Based Performance Measures: Quality Metrics for the Care of Patients Undergoing Breast Reconstruction.

PubMed

Manahan, Michele A; Wooden, William A; Becker, Stephen M; Cacioppo, Jason R; Edge, Stephen B; Grandinetti, Amanda C; Gray, Diedra D; Holley, Susan O; Karp, Nolan S; Kocak, Ergun; Rao, Roshni; Rosson, Gedge D; Schwartz, Jaime S; Sitzman, Thomas J; Soltanian, Hooman T; TerKonda, Sarvam P; Wallace, Anne M

2017-12-01

The American Society of Plastic Surgeons commissioned the Breast Reconstruction Performance Measure Development Work Group to identify and draft quality measures for the care of patients undergoing breast reconstruction surgery. Two outcome measures were identified. The first desired outcome was to reduce the number of returns to the operating room following reconstruction within 60 days of the initial reconstructive procedure. The second desired outcome was to reduce flap loss within 30 days of the initial reconstructive procedure. All measures in this report were approved by the American Society of Plastic Surgeons Breast Reconstruction Performance Measures Work Group and the American Society of Plastic Surgeons Executive Committee. The Work Group recommends the use of these measures for quality initiatives, Continuing Medical Education, Maintenance of Certification, American Society of Plastic Surgeons' Qualified Clinical Data Registry reporting, and national quality reporting programs.

Adaptive 3D Face Reconstruction from Unconstrained Photo Collections.

PubMed

Roth, Joseph; Tong, Yiying; Liu, Xiaoming

2016-12-07

Given a photo collection of "unconstrained" face images of one individual captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of the individual along with albedo information. Unlike prior work on face reconstruction that requires large photo collections, we formulate an approach to adapt to photo collections with a high diversity in both the number of images and the image quality. To achieve this, we incorporate prior knowledge about face shape by fitting a 3D morphable model to form a personalized template, following by using a novel photometric stereo formulation to complete the fine details, under a coarse-to-fine scheme. Our scheme incorporates a structural similarity-based local selection step to help identify a common expression for reconstruction while discarding occluded portions of faces. The evaluation of reconstruction performance is through a novel quality measure, in the absence of ground truth 3D scans. Superior large-scale experimental results are reported on synthetic, Internet, and personal photo collections.

High-contrast multilayer imaging of biological organisms through dark-field digital refocusing.

PubMed

Faridian, Ahmad; Pedrini, Giancarlo; Osten, Wolfgang

2013-08-01

We have developed an imaging system to extract high contrast images from different layers of biological organisms. Utilizing a digital holographic approach, the system works without scanning through layers of the specimen. In dark-field illumination, scattered light has the main contribution in image formation, but in the case of coherent illumination, this creates a strong speckle noise that reduces the image quality. To remove this restriction, the specimen has been illuminated with various speckle-fields and a hologram has been recorded for each speckle-field. Each hologram has been analyzed separately and the corresponding intensity image has been reconstructed. The final image has been derived by averaging over the reconstructed images. A correlation approach has been utilized to determine the number of speckle-fields required to achieve a desired contrast and image quality. The reconstructed intensity images in different object layers are shown for different sea urchin larvae. Two multimedia files are attached to illustrate the process of digital focusing.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levin, Barnaby D. A.; Padgett, Elliot; Chen, Chien-Chun

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co 2 P nanocrystal, platinum nanoparticles on a carbonmore » nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.« less

Joint synthetic aperture radar plus ground moving target indicator from single-channel radar using compressive sensing

DOEpatents

Thompson, Douglas; Hallquist, Aaron; Anderson, Hyrum

2017-10-17

The various embodiments presented herein relate to utilizing an operational single-channel radar to collect and process synthetic aperture radar (SAR) and ground moving target indicator (GMTI) imagery from a same set of radar returns. In an embodiment, data is collected by randomly staggering a slow-time pulse repetition interval (PRI) over a SAR aperture such that a number of transmitted pulses in the SAR aperture is preserved with respect to standard SAR, but many of the pulses are spaced very closely enabling movers (e.g., targets) to be resolved, wherein a relative velocity of the movers places them outside of the SAR ground patch. The various embodiments of image reconstruction can be based on compressed sensing inversion from undersampled data, which can be solved efficiently using such techniques as Bregman iteration. The various embodiments enable high-quality SAR reconstruction, and high-quality GMTI reconstruction from the same set of radar returns.

Highly accelerated cardiac cine parallel MRI using low-rank matrix completion and partial separability model

NASA Astrophysics Data System (ADS)

Lyu, Jingyuan; Nakarmi, Ukash; Zhang, Chaoyi; Ying, Leslie

2016-05-01

This paper presents a new approach to highly accelerated dynamic parallel MRI using low rank matrix completion, partial separability (PS) model. In data acquisition, k-space data is moderately randomly undersampled at the center kspace navigator locations, but highly undersampled at the outer k-space for each temporal frame. In reconstruction, the navigator data is reconstructed from undersampled data using structured low-rank matrix completion. After all the unacquired navigator data is estimated, the partial separable model is used to obtain partial k-t data. Then the parallel imaging method is used to acquire the entire dynamic image series from highly undersampled data. The proposed method has shown to achieve high quality reconstructions with reduction factors up to 31, and temporal resolution of 29ms, when the conventional PS method fails.

Iterative reconstruction methods in atmospheric tomography: FEWHA, Kaczmarz and Gradient-based algorithm

NASA Astrophysics Data System (ADS)

Ramlau, R.; Saxenhuber, D.; Yudytskiy, M.

2014-07-01

The problem of atmospheric tomography arises in ground-based telescope imaging with adaptive optics (AO), where one aims to compensate in real-time for the rapidly changing optical distortions in the atmosphere. Many of these systems depend on a sufficient reconstruction of the turbulence profiles in order to obtain a good correction. Due to steadily growing telescope sizes, there is a strong increase in the computational load for atmospheric reconstruction with current methods, first and foremost the MVM. In this paper we present and compare three novel iterative reconstruction methods. The first iterative approach is the Finite Element- Wavelet Hybrid Algorithm (FEWHA), which combines wavelet-based techniques and conjugate gradient schemes to efficiently and accurately tackle the problem of atmospheric reconstruction. The method is extremely fast, highly flexible and yields superior quality. Another novel iterative reconstruction algorithm is the three step approach which decouples the problem in the reconstruction of the incoming wavefronts, the reconstruction of the turbulent layers (atmospheric tomography) and the computation of the best mirror correction (fitting step). For the atmospheric tomography problem within the three step approach, the Kaczmarz algorithm and the Gradient-based method have been developed. We present a detailed comparison of our reconstructors both in terms of quality and speed performance in the context of a Multi-Object Adaptive Optics (MOAO) system for the E-ELT setting on OCTOPUS, the ESO end-to-end simulation tool.

COMPARISON OF ADAPTIVE STATISTICAL ITERATIVE RECONSTRUCTION (ASIR™) AND MODEL-BASED ITERATIVE RECONSTRUCTION (VEO™) FOR PAEDIATRIC ABDOMINAL CT EXAMINATIONS: AN OBSERVER PERFORMANCE STUDY OF DIAGNOSTIC IMAGE QUALITY.

PubMed

Hultenmo, Maria; Caisander, Håkan; Mack, Karsten; Thilander-Klang, Anne

2016-06-01

The diagnostic image quality of 75 paediatric abdominal computed tomography (CT) examinations reconstructed with two different iterative reconstruction (IR) algorithms-adaptive statistical IR (ASiR™) and model-based IR (Veo™)-was compared. Axial and coronal images were reconstructed with 70 % ASiR with the Soft™ convolution kernel and with the Veo algorithm. The thickness of the reconstructed images was 2.5 or 5 mm depending on the scanning protocol used. Four radiologists graded the delineation of six abdominal structures and the diagnostic usefulness of the image quality. The Veo reconstruction significantly improved the visibility of most of the structures compared with ASiR in all subgroups of images. For coronal images, the Veo reconstruction resulted in significantly improved ratings of the diagnostic use of the image quality compared with the ASiR reconstruction. This was not seen for the axial images. The greatest improvement using Veo reconstruction was observed for the 2.5 mm coronal slices. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Comparison of Ultrasound Tomography Methods in Circular Geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leach, R R; Azevedo, S G; Berryman, J G

2002-01-24

Extremely high quality data was acquired using an experimental ultrasound scanner developed at Lawrence Livermore National Laboratory using a 2D ring geometry with up to 720 transmitter/receiver transducer positions. This unique geometry allows reflection and transmission modes and transmission imaging and quantification of a 3D volume using 2D slice data. Standard image reconstruction methods were applied to the data including straight-ray filtered back projection, reflection tomography, and diffraction tomography. Newer approaches were also tested such as full wave, full wave adjoint method, bent-ray filtered back projection, and full-aperture tomography. A variety of data sets were collected including a formalin-fixed humanmore » breast tissue sample, a commercial ultrasound complex breast phantom, and cylindrical objects with and without inclusions. The resulting reconstruction quality of the images ranges from poor to excellent. The method and results of this study are described including like-data reconstructions produced by different algorithms with side-by-side image comparisons. Comparisons to medical B-scan and x-ray CT scan images are also shown. Reconstruction methods with respect to image quality using resolution, noise, and quantitative accuracy, and computational efficiency metrics will also be discussed.« less

Multi-frame super-resolution with quality self-assessment for retinal fundus videos.

PubMed

Köhler, Thomas; Brost, Alexander; Mogalle, Katja; Zhang, Qianyi; Köhler, Christiane; Michelson, Georg; Hornegger, Joachim; Tornow, Ralf P

2014-01-01

This paper proposes a novel super-resolution framework to reconstruct high-resolution fundus images from multiple low-resolution video frames in retinal fundus imaging. Natural eye movements during an examination are used as a cue for super-resolution in a robust maximum a-posteriori scheme. In order to compensate heterogeneous illumination on the fundus, we integrate retrospective illumination correction for photometric registration to the underlying imaging model. Our method utilizes quality self-assessment to provide objective quality scores for reconstructed images as well as to select regularization parameters automatically. In our evaluation on real data acquired from six human subjects with a low-cost video camera, the proposed method achieved considerable enhancements of low-resolution frames and improved noise and sharpness characteristics by 74%. In terms of image analysis, we demonstrate the importance of our method for the improvement of automatic blood vessel segmentation as an example application, where the sensitivity was increased by 13% using super-resolution reconstruction.

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms.

PubMed

Tang, Jie; Nett, Brian E; Chen, Guang-Hong

2009-10-07

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

Feasibility Study of Using Gemstone Spectral Imaging (GSI) and Adaptive Statistical Iterative Reconstruction (ASIR) for Reducing Radiation and Iodine Contrast Dose in Abdominal CT Patients with High BMI Values.

PubMed

Zhu, Zheng; Zhao, Xin-ming; Zhao, Yan-feng; Wang, Xiao-yi; Zhou, Chun-wu

2015-01-01

To prospectively investigate the effect of using Gemstone Spectral Imaging (GSI) and adaptive statistical iterative reconstruction (ASIR) for reducing radiation and iodine contrast dose in abdominal CT patients with high BMI values. 26 patients (weight > 65kg and BMI ≥ 22) underwent abdominal CT using GSI mode with 300mgI/kg contrast material as study group (group A). Another 21 patients (weight ≤ 65kg and BMI ≥ 22) were scanned with a conventional 120 kVp tube voltage for noise index (NI) of 11 with 450mgI/kg contrast material as control group (group B). GSI images were reconstructed at 60keV with 50%ASIR and the conventional 120kVp images were reconstructed with FBP reconstruction. The CT values, standard deviation (SD), signal-noise-ratio (SNR), contrast-noise-ratio (CNR) of 26 landmarks were quantitatively measured and image quality qualitatively assessed using statistical analysis. As for the quantitative analysis, the difference of CNR between groups A and B was all significant except for the mesenteric vein. The SNR in group A was higher than B except the mesenteric artery and splenic artery. As for the qualitative analysis, all images had diagnostic quality and the agreement for image quality assessment between the reviewers was substantial (kappa = 0.684). CT dose index (CTDI) values for non-enhanced, arterial phase and portal phase in group A were decreased by 49.04%, 40.51% and 40.54% compared with group B (P = 0.000), respectively. The total dose and the injection rate for the contrast material were reduced by 14.40% and 14.95% in A compared with B. The use of GSI and ASIR provides similar enhancement in vessels and image quality with reduced radiation dose and contrast dose, compared with the use of conventional scan protocol.

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization.

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.

A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning.

PubMed

Zhang, Cheng; Zhang, Tao; Zheng, Jian; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

2015-01-01

In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time.

Feasibility study of low-dose intra-operative cone-beam CT for image-guided surgery

NASA Astrophysics Data System (ADS)

Han, Xiao; Shi, Shuanghe; Bian, Junguo; Helm, Patrick; Sidky, Emil Y.; Pan, Xiaochuan

2011-03-01

Cone-beam computed tomography (CBCT) has been increasingly used during surgical procedures for providing accurate three-dimensional anatomical information for intra-operative navigation and verification. High-quality CBCT images are in general obtained through reconstruction from projection data acquired at hundreds of view angles, which is associated with a non-negligible amount of radiation exposure to the patient. In this work, we have applied a novel image-reconstruction algorithm, the adaptive-steepest-descent-POCS (ASD-POCS) algorithm, to reconstruct CBCT images from projection data at a significantly reduced number of view angles. Preliminary results from experimental studies involving both simulated data and real data show that images of comparable quality to those presently available in clinical image-guidance systems can be obtained by use of the ASD-POCS algorithm from a fraction of the projection data that are currently used. The result implies potential value of the proposed reconstruction technique for low-dose intra-operative CBCT imaging applications.

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization

PubMed Central

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2016-01-01

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate. PMID:27073853

[Research advances in dendrochronology].

PubMed

Fang, Ke-Yan; Chen, Qiu-Yan; Liu, Chang-Zhi; Cao, Chun-Fu; Chen, Ya-Jun; Zhou, Fei-Fei

2014-07-01

Tree-ring studies in China have achieved great advances since the 1990s, particularly for the dendroclimatological studies which have made some influence around the world. However, because of the uneven development, limited attention has been currently paid on the other branches of dendrochronology. We herein briefly compared the advances of dendrochronology in China and of the world and presented suggestions on future dendrochronological studies. Large-scale tree-ring based climate reconstructions in China are highly needed by employing mathematical methods and a high quality tree-ring network of the ring-width, density, stable isotope and wood anatomy. Tree-ring based field climate reconstructions provide potentials on explorations of climate forcings during the reconstructed periods via climate diagnosis and process simulation.

Simultaneous phylogeny reconstruction and multiple sequence alignment

PubMed Central

Yue, Feng; Shi, Jian; Tang, Jijun

2009-01-01

Background A phylogeny is the evolutionary history of a group of organisms. To date, sequence data is still the most used data type for phylogenetic reconstruction. Before any sequences can be used for phylogeny reconstruction, they must be aligned, and the quality of the multiple sequence alignment has been shown to affect the quality of the inferred phylogeny. At the same time, all the current multiple sequence alignment programs use a guide tree to produce the alignment and experiments showed that good guide trees can significantly improve the multiple alignment quality. Results We devise a new algorithm to simultaneously align multiple sequences and search for the phylogenetic tree that leads to the best alignment. We also implemented the algorithm as a C program package, which can handle both DNA and protein data and can take simple cost model as well as complex substitution matrices, such as PAM250 or BLOSUM62. The performance of the new method are compared with those from other popular multiple sequence alignment tools, including the widely used programs such as ClustalW and T-Coffee. Experimental results suggest that this method has good performance in terms of both phylogeny accuracy and alignment quality. Conclusion We present an algorithm to align multiple sequences and reconstruct the phylogenies that minimize the alignment score, which is based on an efficient algorithm to solve the median problems for three sequences. Our extensive experiments suggest that this method is very promising and can produce high quality phylogenies and alignments. PMID:19208110

Do psychosocial interventions improve rehabilitation outcomes after anterior cruciate ligament reconstruction? A systematic review.

PubMed

Coronado, Rogelio A; Bird, Mackenzie L; Van Hoy, Erin E; Huston, Laura J; Spindler, Kurt P; Archer, Kristin R

2018-03-01

To examine the role of psychosocial interventions in improving patient-reported clinical outcomes, including return to sport/activity, and intermediary psychosocial factors after anterior cruciate ligament reconstruction. MEDLINE/PubMed, CINAHL, PsycINFO, and Web of Science were searched from each database's inception to March 2017 for published studies in patients after anterior cruciate ligament reconstruction. Studies were included if they reported on the effects of a postoperative psychosocial intervention on a patient-reported clinical measure of disability, function, pain, quality of life, return to sport/activity, or intermediary psychosocial factor. Data were extracted using a standardized form and summary effects from each article were compiled. The methodological quality of randomized trials was assessed using the Physiotherapy Evidence Database Scale and scores greater than 5/10 were considered high quality. A total of 893 articles were identified from the literature search. Of these, four randomized trials ( N = 210) met inclusion criteria. The four articles examined guided imagery and relaxation, coping modeling, and visual imagery as postoperative psychosocial interventions. Methodological quality scores of the studies ranged from 5 to 9. There were inconsistent findings for the additive benefit of psychosocial interventions for improving postoperative function, pain, or self-efficacy and limited evidence for improving postoperative quality of life, anxiety, or fear of reinjury. No study examined the effects of psychosocial interventions on return to sport/activity. Overall, there is limited evidence on the efficacy of postoperative psychosocial interventions for improving functional recovery after anterior cruciate ligament reconstruction.

Comparison of SeaWinds Backscatter Imaging Algorithms

PubMed Central

Long, David G.

2017-01-01

This paper compares the performance and tradeoffs of various backscatter imaging algorithms for the SeaWinds scatterometer when multiple passes over a target are available. Reconstruction methods are compared with conventional gridding algorithms. In particular, the performance and tradeoffs in conventional ‘drop in the bucket’ (DIB) gridding at the intrinsic sensor resolution are compared to high-spatial-resolution imaging algorithms such as fine-resolution DIB and the scatterometer image reconstruction (SIR) that generate enhanced-resolution backscatter images. Various options for each algorithm are explored, including considering both linear and dB computation. The effects of sampling density and reconstruction quality versus time are explored. Both simulated and actual data results are considered. The results demonstrate the effectiveness of high-resolution reconstruction using SIR as well as its limitations and the limitations of DIB and fDIB. PMID:28828143

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

NASA Astrophysics Data System (ADS)

Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong

2016-03-01

In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.

LORAKS Makes Better SENSE: Phase-Constrained Partial Fourier SENSE Reconstruction without Phase Calibration

PubMed Central

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P.

2016-01-01

Purpose Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. Theory and Methods The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly-accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely-used calibrationless uniformly-undersampled trajectories. Results Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. Conclusion The SENSE-LORAKS framework provides promising new opportunities for highly-accelerated MRI. PMID:27037836

Anisotropic modeling and joint-MAP stitching for improved ultrasound model-based iterative reconstruction of large and thick specimens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almansouri, Hani; Venkatakrishnan, Singanallur V.; Clayton, Dwight A.

One-sided non-destructive evaluation (NDE) is widely used to inspect materials, such as concrete structures in nuclear power plants (NPP). A widely used method for one-sided NDE is the synthetic aperture focusing technique (SAFT). The SAFT algorithm produces reasonable results when inspecting simple structures. However, for complex structures, such as heavily reinforced thick concrete structures, SAFT results in artifacts and hence there is a need for a more sophisticated inversion technique. Model-based iterative reconstruction (MBIR) algorithms, which are typically equivalent to regularized inversion techniques, offer a powerful framework to incorporate complex models for the physics, detector miscalibrations and the materials beingmore » imaged to obtain high quality reconstructions. Previously, we have proposed an ultrasonic MBIR method that signifcantly improves reconstruction quality compared to SAFT. However, the method made some simplifying assumptions on the propagation model and did not disucss ways to handle data that is obtained by raster scanning a system over a surface to inspect large regions. In this paper, we propose a novel MBIR algorithm that incorporates an anisotropic forward model and allows for the joint processing of data obtained from a system that raster scans a large surface. We demonstrate that the new MBIR method can produce dramatic improvements in reconstruction quality compared to SAFT and suppresses articfacts compared to the perviously presented MBIR approach.« less

Anisotropic modeling and joint-MAP stitching for improved ultrasound model-based iterative reconstruction of large and thick specimens

NASA Astrophysics Data System (ADS)

Almansouri, Hani; Venkatakrishnan, Singanallur; Clayton, Dwight; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

2018-04-01

One-sided non-destructive evaluation (NDE) is widely used to inspect materials, such as concrete structures in nuclear power plants (NPP). A widely used method for one-sided NDE is the synthetic aperture focusing technique (SAFT). The SAFT algorithm produces reasonable results when inspecting simple structures. However, for complex structures, such as heavily reinforced thick concrete structures, SAFT results in artifacts and hence there is a need for a more sophisticated inversion technique. Model-based iterative reconstruction (MBIR) algorithms, which are typically equivalent to regularized inversion techniques, offer a powerful framework to incorporate complex models for the physics, detector miscalibrations and the materials being imaged to obtain high quality reconstructions. Previously, we have proposed an ultrasonic MBIR method that signifcantly improves reconstruction quality compared to SAFT. However, the method made some simplifying assumptions on the propagation model and did not disucss ways to handle data that is obtained by raster scanning a system over a surface to inspect large regions. In this paper, we propose a novel MBIR algorithm that incorporates an anisotropic forward model and allows for the joint processing of data obtained from a system that raster scans a large surface. We demonstrate that the new MBIR method can produce dramatic improvements in reconstruction quality compared to SAFT and suppresses articfacts compared to the perviously presented MBIR approach.

Visually lossless compression of digital hologram sequences

NASA Astrophysics Data System (ADS)

Darakis, Emmanouil; Kowiel, Marcin; Näsänen, Risto; Naughton, Thomas J.

2010-01-01

Digital hologram sequences have great potential for the recording of 3D scenes of moving macroscopic objects as their numerical reconstruction can yield a range of perspective views of the scene. Digital holograms inherently have large information content and lossless coding of holographic data is rather inefficient due to the speckled nature of the interference fringes they contain. Lossy coding of still holograms and hologram sequences has shown promising results. By definition, lossy compression introduces errors in the reconstruction. In all of the previous studies, numerical metrics were used to measure the compression error and through it, the coding quality. Digital hologram reconstructions are highly speckled and the speckle pattern is very sensitive to data changes. Hence, numerical quality metrics can be misleading. For example, for low compression ratios, a numerically significant coding error can have visually negligible effects. Yet, in several cases, it is of high interest to know how much lossy compression can be achieved, while maintaining the reconstruction quality at visually lossless levels. Using an experimental threshold estimation method, the staircase algorithm, we determined the highest compression ratio that was not perceptible to human observers for objects compressed with Dirac and MPEG-4 compression methods. This level of compression can be regarded as the point below which compression is perceptually lossless although physically the compression is lossy. It was found that up to 4 to 7.5 fold compression can be obtained with the above methods without any perceptible change in the appearance of video sequences.

Spectral reconstruction of dental X-ray tubes using laplace inverse transform of the attenuation curve

NASA Astrophysics Data System (ADS)

Malezan, A.; Tomal, A.; Antoniassi, M.; Watanabe, P. C. A.; Albino, L. D.; Poletti, M. E.

2015-11-01

In this work, a spectral reconstruction methodology for diagnostic X-ray, using Laplace inverse transform of the attenuation, was successfully applied to dental X-ray equipments. The attenuation curves of 8 commercially available dental X-ray equipment, from 3 different manufactures (Siemens, Gnatus and Dabi Atlante), were obtained by using an ionization chamber and high purity aluminium filters, while the kVp was obtained with a specific meter. A computational routine was implemented in order to adjust a model function, whose inverse Laplace transform is analytically known, to the attenuation curve. This methodology was validated by comparing the reconstructed and the measured (using semiconductor detector of cadmium telluride) spectra of a given dental X-ray unit. The spectral reconstruction showed the Dabi Atlante equipments generating similar shape spectra. This is a desirable feature from clinic standpoint because it produces similar levels of image quality and dose. We observed that equipments from Siemens and Gnatus generate significantly different spectra, suggesting that, for a given operating protocol, these units will present different levels of image quality and dose. This fact claims for the necessity of individualized operating protocols that maximize image quality and dose. The proposed methodology is suitable to perform a spectral reconstruction of dental X-ray equipments from the simple measurements of attenuation curve and kVp. The simplified experimental apparatus and the low level of technical difficulty make this methodology accessible to a broad range of users. The knowledge of the spectral distribution can help in the development of operating protocols that maximize image quality and dose.

An Efficient Framework for Compressed Sensing Reconstruction of Highly Accelerated Dynamic Cardiac MRI

NASA Astrophysics Data System (ADS)

Ting, Samuel T.

The research presented in this work seeks to develop, validate, and deploy practical techniques for improving diagnosis of cardiovascular disease. In the philosophy of biomedical engineering, we seek to identify an existing medical problem having significant societal and economic effects and address this problem using engineering approaches. Cardiovascular disease is the leading cause of mortality in the United States, accounting for more deaths than any other major cause of death in every year since 1900 with the exception of the year 1918. Cardiovascular disease is estimated to account for almost one-third of all deaths in the United States, with more than 2150 deaths each day, or roughly 1 death every 40 seconds. In the past several decades, a growing array of imaging modalities have proven useful in aiding the diagnosis and evaluation of cardiovascular disease, including computed tomography, single photon emission computed tomography, and echocardiography. In particular, cardiac magnetic resonance imaging is an excellent diagnostic tool that can provide within a single exam a high quality evaluation of cardiac function, blood flow, perfusion, viability, and edema without the use of ionizing radiation. The scope of this work focuses on the application of engineering techniques for improving imaging using cardiac magnetic resonance with the goal of improving the utility of this powerful imaging modality. Dynamic cine imaging, or the capturing of movies of a single slice or volume within the heart or great vessel region, is used in nearly every cardiac magnetic resonance imaging exam, and adequate evaluation of cardiac function and morphology for diagnosis and evaluation of cardiovascular disease depends heavily on both the spatial and temporal resolution as well as the image quality of the reconstruction cine images. This work focuses primarily on image reconstruction techniques utilized in cine imaging; however, the techniques discussed are also relevant to other dynamic and static imaging techniques based on cardiac magnetic resonance. Conventional segmented techniques for cardiac cine imaging require breath-holding as well as regular cardiac rhythm, and can be time-consuming to acquire. Inadequate breath-holding or irregular cardiac rhythm can result in completely non-diagnostic images, limiting the utility of these techniques in a significant patient population. Real-time single-shot cardiac cine imaging enables free-breathing acquisition with significantly shortened imaging time and promises to significantly improve the utility of cine imaging for diagnosis and evaluation of cardiovascular disease. However, utility of real-time cine images depends heavily on the successful reconstruction of final cine images from undersampled data. Successful reconstruction of images from more highly undersampled data results directly in images exhibiting finer spatial and temporal resolution provided that image quality is sufficient. This work focuses primarily on the development, validation, and deployment of practical techniques for enabling the reconstruction of real-time cardiac cine images at the spatial and temporal resolutions and image quality needed for diagnostic utility. Particular emphasis is placed on the development of reconstruction approaches resulting in with short computation times that can be used in the clinical environment. Specifically, the use of compressed sensing signal recovery techniques is considered; such techniques show great promise in allowing successful reconstruction of highly undersampled data. The scope of this work concerns two primary topics related to signal recovery using compressed sensing: (1) long reconstruction times of these techniques, and (2) improved sparsity models for signal recovery from more highly undersampled data. Both of these aspects are relevant to the practical application of compressed sensing techniques in the context of improving image reconstruction of real-time cardiac cine images. First, algorithmic and implementational approaches are proposed for reducing the computational time for a compressed sensing reconstruction framework. Specific optimization algorithms based on the fast iterative/shrinkage algorithm (FISTA) are applied in the context of real-time cine image reconstruction to achieve efficient per-iteration computation time. Implementation within a code framework utilizing commercially available graphics processing units (GPUs) allows for practical and efficient implementation directly within the clinical environment. Second, patch-based sparsity models are proposed to enable compressed sensing signal recovery from highly undersampled data. Numerical studies demonstrate that this approach can help improve image quality at higher undersampling ratios, enabling real-time cine imaging at higher acceleration rates. In this work, it is shown that these techniques yield a holistic framework for achieving efficient reconstruction of real-time cine images with spatial and temporal resolution sufficient for use in the clinical environment. A thorough description of these techniques from both a theoretical and practical view is provided - both of which may be of interest to the reader in terms of future work.

Clinical evaluation of new automatic coronary-specific best cardiac phase selection algorithm for single-beat coronary CT angiography.

PubMed

Wang, Hui; Xu, Lei; Fan, Zhanming; Liang, Junfu; Yan, Zixu; Sun, Zhonghua

2017-01-01

The aim of this study was to evaluate the workflow efficiency of a new automatic coronary-specific reconstruction technique (Smart Phase, GE Healthcare-SP) for selection of the best cardiac phase with least coronary motion when compared with expert manual selection (MS) of best phase in patients with high heart rate. A total of 46 patients with heart rates above 75 bpm who underwent single beat coronary computed tomography angiography (CCTA) were enrolled in this study. CCTA of all subjects were performed on a 256-detector row CT scanner (Revolution CT, GE Healthcare, Waukesha, Wisconsin, US). With the SP technique, the acquired phase range was automatically searched in 2% phase intervals during the reconstruction process to determine the optimal phase for coronary assessment, while for routine expert MS, reconstructions were performed at 5% intervals and a best phase was manually determined. The reconstruction and review times were recorded to measure the workflow efficiency for each method. Two reviewers subjectively assessed image quality for each coronary artery in the MS and SP reconstruction volumes using a 4-point grading scale. The average HR of the enrolled patients was 91.1±19.0bpm. A total of 204 vessels were assessed. The subjective image quality using SP was comparable to that of the MS, 1.45±0.85 vs 1.43±0.81 respectively (p = 0.88). The average time was 246 seconds for the manual best phase selection, and 98 seconds for the SP selection, resulting in average time saving of 148 seconds (60%) with use of the SP algorithm. The coronary specific automatic cardiac best phase selection technique (Smart Phase) improves clinical workflow in high heart rate patients and provides image quality comparable with manual cardiac best phase selection. Reconstruction of single-beat CCTA exams with SP can benefit the users with less experienced in CCTA image interpretation.

TU-AB-207A-03: Image Quality, Dose, and Clinical Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, F.

Practicing medical physicists are often time charged with the tasks of evaluating and troubleshooting complex image quality issues related to CT scanners. This course will equip them with a solid and practical understanding of common CT imaging chain and its major components with emphasis on acquisition physics and hardware, reconstruction, artifacts, image quality, dose, and advanced clinical applications. The core objective is to explain the effects of these major system components on the image quality. This course will not focus on the rapid-changing advanced technologies given the two-hour time limit, but the fundamental principles discussed in this course may facilitatemore » better understanding of those more complicated technologies. The course will begin with an overview of CT acquisition physics and geometry. X-ray tube and CT detector are important acquisition hardware critical to the overall image quality. Each of these two subsystems consists of several major components. An in-depth description of the function and failure modes of these components will be provided. Examples of artifacts related to these failure modes will be presented: off-focal radiation, tube arcing, heel effect, oil bubble, offset drift effect, cross-talk effect, and bad pixels. The fundamentals of CT image reconstruction will first be discussed on an intuitive level. Approaches that do not require rigorous derivation of mathematical formulations will be presented. This is followed by a detailed derivation of the Fourier slice theorem: the foundation of the FBP algorithm. FBP for parallel-beam, fan-beam, and cone-beam geometries will be discussed. To address the issue of radiation dose related to x-ray CT, recent advances in iterative reconstruction, their advantages, and clinical applications will also be described. Because of the nature of fundamental physics and mathematics, limitations in data acquisition, and non-ideal conditions of major system components, image artifact often arise in the reconstructed images. Because of the limited scope of this course, only major imaging artifacts, their appearance, and possible mitigation and corrections will be discussed. Assessment of the performance of a CT scanner is a complicated subject. Procedures to measure common image quality metrics such as high contrast spatial resolution, low contrast detectability, and slice profile will be described. The reason why these metrics used for FBP may not be sufficient for statistical iterative reconstruction will be explained. Optimizing radiation dose requires comprehension of CT dose metrics. This course will briefly describe various dose metrics, and interaction with acquisition parameters and patient habitus. CT is among the most frequently used imaging tools due to its superior image quality, easy to operate, and a broad range of applications. This course will present several interesting CT applications such as a mobile CT unit on an ambulance for stroke patients, low dose lung cancer screening, and single heartbeat cardiac CT. Learning Objectives: Understand the function and impact of major components of X-ray tube on the image quality. Understand the function and impact of major components of CT detector on the image quality. Be familiar with the basic procedure of CT image reconstruction. Understand the effect of image reconstruction on CT image quality and artifacts. Understand the root causes of common CT image artifacts. Be familiar with image quality metrics especially high and low contrast resolution, noise power spectrum, slice sensitivity profile, etc. Understand why basic image quality metrics used for FBP may not be sufficient to characterize the performance of advanced iterative reconstruction. Be familiar with various CT dose metrics and their interaction with acquisition parameters. New development in advanced CT clinical applications. JH: Employee of GE Healthcare. FD: No disclosure.; J. Hsieh, Jiang Hsieh is an employee of GE Healthcare.« less

Virtual Reconstruction of Lost Architectures: from the Tls Survey to AR Visualization

NASA Astrophysics Data System (ADS)

Quattrini, R.; Pierdicca, R.; Frontoni, E.; Barcaglioni, R.

2016-06-01

The exploitation of high quality 3D models for dissemination of archaeological heritage is currently an investigated topic, although Mobile Augmented Reality platforms for historical architecture are not available, allowing to develop low-cost pipelines for effective contents. The paper presents a virtual anastylosis, starting from historical sources and from 3D model based on TLS survey. Several efforts and outputs in augmented or immersive environments, exploiting this reconstruction, are discussed. The work demonstrates the feasibility of a 3D reconstruction approach for complex architectural shapes starting from point clouds and its AR/VR exploitation, allowing the superimposition with archaeological evidences. Major contributions consist in the presentation and the discussion of a pipeline starting from the virtual model, to its simplification showing several outcomes, comparing also the supported data qualities and advantages/disadvantages due to MAR and VR limitations.

Large Scale Textured Mesh Reconstruction from Mobile Mapping Images and LIDAR Scans

NASA Astrophysics Data System (ADS)

Boussaha, M.; Vallet, B.; Rives, P.

2018-05-01

The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS). First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points) and photometry (images). Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014) is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17 km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.

Effects of pure and hybrid iterative reconstruction algorithms on high-resolution computed tomography in the evaluation of interstitial lung disease.

PubMed

Katsura, Masaki; Sato, Jiro; Akahane, Masaaki; Mise, Yoko; Sumida, Kaoru; Abe, Osamu

2017-08-01

To compare image quality characteristics of high-resolution computed tomography (HRCT) in the evaluation of interstitial lung disease using three different reconstruction methods: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Eighty-nine consecutive patients with interstitial lung disease underwent standard-of-care chest CT with 64-row multi-detector CT. HRCT images were reconstructed in 0.625-mm contiguous axial slices using FBP, ASIR, and MBIR. Two radiologists independently assessed the images in a blinded manner for subjective image noise, streak artifacts, and visualization of normal and pathologic structures. Objective image noise was measured in the lung parenchyma. Spatial resolution was assessed by measuring the modulation transfer function (MTF). MBIR offered significantly lower objective image noise (22.24±4.53, P<0.01 among all pairs, Student's t-test) compared with ASIR (39.76±7.41) and FBP (51.91±9.71). MTF (spatial resolution) was increased using MBIR compared with ASIR and FBP. MBIR showed improvements in visualization of normal and pathologic structures over ASIR and FBP, while ASIR was rated quite similarly to FBP. MBIR significantly improved subjective image noise (P<0.01 among all pairs, the sign test), and streak artifacts (P<0.01 each for MBIR vs. the other 2 image data sets). MBIR provides high-quality HRCT images for interstitial lung disease by reducing image noise and streak artifacts and improving spatial resolution compared with ASIR and FBP. Copyright © 2017 Elsevier B.V. All rights reserved.

LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

NASA Astrophysics Data System (ADS)

Li, Yusheng; Matej, Samuel; Karp, Joel S.; Metzler, Scott D.

2015-01-01

Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which can have significant implications in preclinical and clinical ROI imaging applications.

Coastal barrier stratigraphy for Holocene high-resolution sea-level reconstruction

PubMed Central

Costas, Susana; Ferreira, Óscar; Plomaritis, Theocharis A.; Leorri, Eduardo

2016-01-01

The uncertainties surrounding present and future sea-level rise have revived the debate around sea-level changes through the deglaciation and mid- to late Holocene, from which arises a need for high-quality reconstructions of regional sea level. Here, we explore the stratigraphy of a sandy barrier to identify the best sea-level indicators and provide a new sea-level reconstruction for the central Portuguese coast over the past 6.5 ka. The selected indicators represent morphological features extracted from coastal barrier stratigraphy, beach berm and dune-beach contact. These features were mapped from high-resolution ground penetrating radar images of the subsurface and transformed into sea-level indicators through comparison with modern analogs and a chronology based on optically stimulated luminescence ages. Our reconstructions document a continuous but slow sea-level rise after 6.5 ka with an accumulated change in elevation of about 2 m. In the context of SW Europe, our results show good agreement with previous studies, including the Tagus isostatic model, with minor discrepancies that demand further improvement of regional models. This work reinforces the potential of barrier indicators to accurately reconstruct high-resolution mid- to late Holocene sea-level changes through simple approaches. PMID:27929122

Coastal barrier stratigraphy for Holocene high-resolution sea-level reconstruction.

PubMed

Costas, Susana; Ferreira, Óscar; Plomaritis, Theocharis A; Leorri, Eduardo

2016-12-08

The uncertainties surrounding present and future sea-level rise have revived the debate around sea-level changes through the deglaciation and mid- to late Holocene, from which arises a need for high-quality reconstructions of regional sea level. Here, we explore the stratigraphy of a sandy barrier to identify the best sea-level indicators and provide a new sea-level reconstruction for the central Portuguese coast over the past 6.5 ka. The selected indicators represent morphological features extracted from coastal barrier stratigraphy, beach berm and dune-beach contact. These features were mapped from high-resolution ground penetrating radar images of the subsurface and transformed into sea-level indicators through comparison with modern analogs and a chronology based on optically stimulated luminescence ages. Our reconstructions document a continuous but slow sea-level rise after 6.5 ka with an accumulated change in elevation of about 2 m. In the context of SW Europe, our results show good agreement with previous studies, including the Tagus isostatic model, with minor discrepancies that demand further improvement of regional models. This work reinforces the potential of barrier indicators to accurately reconstruct high-resolution mid- to late Holocene sea-level changes through simple approaches.

An extended algebraic reconstruction technique (E-ART) for dual spectral CT.

PubMed

Zhao, Yunsong; Zhao, Xing; Zhang, Peng

2015-03-01

Compared with standard computed tomography (CT), dual spectral CT (DSCT) has many advantages for object separation, contrast enhancement, artifact reduction, and material composition assessment. But it is generally difficult to reconstruct images from polychromatic projections acquired by DSCT, because of the nonlinear relation between the polychromatic projections and the images to be reconstructed. This paper first models the DSCT reconstruction problem as a nonlinear system problem; and then extend the classic ART method to solve the nonlinear system. One feature of the proposed method is its flexibility. It fits for any scanning configurations commonly used and does not require consistent rays for different X-ray spectra. Another feature of the proposed method is its high degree of parallelism, which means that the method is suitable for acceleration on GPUs (graphic processing units) or other parallel systems. The method is validated with numerical experiments from simulated noise free and noisy data. High quality images are reconstructed with the proposed method from the polychromatic projections of DSCT. The reconstructed images are still satisfactory even if there are certain errors in the estimated X-ray spectra.

A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data.

PubMed

Luo, Jianhua; Mou, Zhiying; Qin, Binjie; Li, Wanqing; Ogunbona, Philip; Robini, Marc C; Zhu, Yuemin

2018-07-01

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.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Compressed/reconstructed test images for CRAF/Cassini

NASA Technical Reports Server (NTRS)

Dolinar, S.; Cheung, K.-M.; Onyszchuk, I.; Pollara, F.; Arnold, S.

1991-01-01

A set of compressed, then reconstructed, test images submitted to the Comet Rendezvous Asteroid Flyby (CRAF)/Cassini project is presented as part of its evaluation of near lossless high compression algorithms for representing image data. A total of seven test image files were provided by the project. The seven test images were compressed, then reconstructed with high quality (root mean square error of approximately one or two gray levels on an 8 bit gray scale), using discrete cosine transforms or Hadamard transforms and efficient entropy coders. The resulting compression ratios varied from about 2:1 to about 10:1, depending on the activity or randomness in the source image. This was accomplished without any special effort to optimize the quantizer or to introduce special postprocessing to filter the reconstruction errors. A more complete set of measurements, showing the relative performance of the compression algorithms over a wide range of compression ratios and reconstruction errors, shows that additional compression is possible at a small sacrifice in fidelity.

Long-term outcomes of urinary tract reconstruction in patients with neurogenic urinary tract dysfunction

PubMed Central

Johnson, E. U.; Singh, Gurpreet

2013-01-01

The advent of specialized spinal units and better understanding of the pathophysiology of neurogenic urinary tract dysfunction has made long-term survival of these patients a reality. This has, in turn, led to an increase in quality and choice of management modalities offered to these patients including complex anatomic urinary tract reconstructive procedures tailored to the unique needs of each individual with variable outcomes. We performed a literature review evaluating the long-term outcomes of these reconstructive procedures. To achieve this, we conducted a world-wide electronic literature search of long-term outcomes published in English. As the premise of this review is long-term outcomes, we have focused on pathologies where evidence of long-term outcome is available such as patients with spinal injuries and spina bifida. Therapeutic success following urinary tract reconstruction is usually measured by preservation of renal function, improvement in quality-of-life, the satisfactory achievement of agreed outcomes and the prevention of serious complications. Prognostic factors include neuropathic detrusor overactivity; sphincter dyssynergia; bladder over distension; high pressure storage and high leak point pressures; vesicoureteric reflex, stone formation and urinary tract infections. Although, the past decade has witnessed a reduction in the total number of bladder reconstructive surgeries in the UK, these procedures are essentially safe and effective; but require long-term clinical and functional follow-up/monitoring. Until tissue engineering and gene therapy becomes more mainstream, we feel there is still a place for urinary tract reconstruction in patients with neurogenic lower urinary tract dysfunction. PMID:24235796

Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

PubMed

Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

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 < 0.0001) for the ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P < 0.0001) for ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective 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%.

The Wide-Field Imaging Interferometry Testbed: Enabling Techniques for High Angular Resolution Astronomy

NASA Technical Reports Server (NTRS)

Rinehart, S. A.; Armstrong, T.; Frey, Bradley J.; Jung, J.; Kirk, J.; Leisawitz, David T.; Leviton, Douglas B.; Lyon, R.; Maher, Stephen; Martino, Anthony J.;

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca; Després, Philippe, E-mail: philippe.despres@phy.ulaval.ca

2015-04-15

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

A novel high-frequency encoding algorithm for image compression

NASA Astrophysics Data System (ADS)

Siddeq, Mohammed M.; Rodrigues, Marcos A.

2017-12-01

In this paper, a new method for image compression is proposed whose quality is demonstrated through accurate 3D reconstruction from 2D images. The method is based on the discrete cosine transform (DCT) together with a high-frequency minimization encoding algorithm at compression stage and a new concurrent binary search algorithm at decompression stage. The proposed compression method consists of five main steps: (1) divide the image into blocks and apply DCT to each block; (2) apply a high-frequency minimization method to the AC-coefficients reducing each block by 2/3 resulting in a minimized array; (3) build a look up table of probability data to enable the recovery of the original high frequencies at decompression stage; (4) apply a delta or differential operator to the list of DC-components; and (5) apply arithmetic encoding to the outputs of steps (2) and (4). At decompression stage, the look up table and the concurrent binary search algorithm are used to reconstruct all high-frequency AC-coefficients while the DC-components are decoded by reversing the arithmetic coding. Finally, the inverse DCT recovers the original image. We tested the technique by compressing and decompressing 2D images including images with structured light patterns for 3D reconstruction. The technique is compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results demonstrate that the proposed compression method is perceptually superior to JPEG with equivalent quality to JPEG2000. Concerning 3D surface reconstruction from images, it is demonstrated that the proposed method is superior to both JPEG and JPEG2000.

High Spatiotemporal Resolution Dynamic Contrast-Enhanced MR Enterography in Crohn Disease Terminal Ileitis Using Continuous Golden-Angle Radial Sampling, Compressed Sensing, and Parallel Imaging.

PubMed

Ream, Justin M; Doshi, Ankur; Lala, Shailee V; Kim, Sooah; Rusinek, Henry; Chandarana, Hersh

2015-06-01

The purpose of this article was to assess the feasibility of golden-angle radial acquisition with compress sensing reconstruction (Golden-angle RAdial Sparse Parallel [GRASP]) for acquiring high temporal resolution data for pharmacokinetic modeling while maintaining high image quality in patients with Crohn disease terminal ileitis. Fourteen patients with biopsy-proven Crohn terminal ileitis were scanned using both contrast-enhanced GRASP and Cartesian breath-hold (volume-interpolated breath-hold examination [VIBE]) acquisitions. GRASP data were reconstructed with 2.4-second temporal resolution and fitted to the generalized kinetic model using an individualized arterial input function to derive the volume transfer coefficient (K(trans)) and interstitial volume (v(e)). Reconstructions, including data from the entire GRASP acquisition and Cartesian VIBE acquisitions, were rated for image quality, artifact, and detection of typical Crohn ileitis features. Inflamed loops of ileum had significantly higher K(trans) (3.36 ± 2.49 vs 0.86 ± 0.49 min(-1), p < 0.005) and v(e) (0.53 ± 0.15 vs 0.20 ± 0.11, p < 0.005) compared with normal bowel loops. There were no significant differences between GRASP and Cartesian VIBE for overall image quality (p = 0.180) or detection of Crohn ileitis features, although streak artifact was worse with the GRASP acquisition (p = 0.001). High temporal resolution data for pharmacokinetic modeling and high spatial resolution data for morphologic image analysis can be achieved in the same acquisition using GRASP.

[Criteria of life quality after reconstructive breast cancer surgery].

PubMed

Strittmatter, H J; Neises, M; Blecken, S R

2006-08-01

The aim of this study was to evaluate the quality of life of women after a breast cancer surgery. The question was if women which had reconstructive breast cancer surgery experience a higher quality of life than women who, for various distinct reasons, had not undergone reconstruction. The participants of this study were women who had either received a mastectomy or those who at the same time underwent a breast reconstruction using implants during the time period from 1/1/2000 until 31/10/2003 at the University Hospital for Women of Heidelberg and Mannheim. With the help of three standardised questionnaires, the women could describe their post-surgical physical and psychological condition as well as the perceived quality of life. The study included 33 patients who had received breast implants and 31 patients without reconstruction. Women who had breast cancer surgery with reconstruction through implants had less problems and restrictions concerning their physical condition as well as their functional status. Moreover, compared to those participants with no reconstruction, their cognitive and emotional burdens were not as pronounced and they also they were able to better cope with the disease. Thus, their overall quality of life was superior than that of the other women. Breast reconstruction after primary and secondary mastectomy is an important contribution in order to improve the self-esteem and quality of a patient's life. Furthermore, it plays an essential role in coping with the psychological effects of breast cancer.

Challenges in Flying Quadrotor Unmanned Aerial Vehicle for 3d Indoor Reconstruction

NASA Astrophysics Data System (ADS)

Yan, J.; Grasso, N.; Zlatanova, S.; Braggaar, R. C.; Marx, D. B.

2017-09-01

Three-dimensional modelling plays a vital role in indoor 3D tracking, navigation, guidance and emergency evacuation. Reconstruction of indoor 3D models is still problematic, in part, because indoor spaces provide challenges less-documented than their outdoor counterparts. Challenges include obstacles curtailing image and point cloud capture, restricted accessibility and a wide array of indoor objects, each with unique semantics. Reconstruction of indoor environments can be achieved through a photogrammetric approach, e.g. by using image frames, aligned using recurring corresponding image points (CIP) to build coloured point clouds. Our experiments were conducted by flying a QUAV in three indoor environments and later reconstructing 3D models which were analysed under different conditions. Point clouds and meshes were created using Agisoft PhotoScan Professional. We concentrated on flight paths from two vantage points: 1) safety and security while flying indoors and 2) data collection needed for reconstruction of 3D models. We surmised that the main challenges in providing safe flight paths are related to the physical configuration of indoor environments, privacy issues, the presence of people and light conditions. We observed that the quality of recorded video used for 3D reconstruction has a high dependency on surface materials, wall textures and object types being reconstructed. Our results show that 3D indoor reconstruction predicated on video capture using a QUAV is indeed feasible, but close attention should be paid to flight paths and conditions ultimately influencing the quality of 3D models. Moreover, it should be decided in advance which objects need to be reconstructed, e.g. bare rooms or detailed furniture.

Implementation of compressive sensing for preclinical cine-MRI

NASA Astrophysics Data System (ADS)

Tan, Elliot; Yang, Ming; Ma, Lixin; Zheng, Yahong Rosa

2014-03-01

This paper presents a practical implementation of Compressive Sensing (CS) for a preclinical MRI machine to acquire randomly undersampled k-space data in cardiac function imaging applications. First, random undersampling masks were generated based on Gaussian, Cauchy, wrapped Cauchy and von Mises probability distribution functions by the inverse transform method. The best masks for undersampling ratios of 0.3, 0.4 and 0.5 were chosen for animal experimentation, and were programmed into a Bruker Avance III BioSpec 7.0T MRI system through method programming in ParaVision. Three undersampled mouse heart datasets were obtained using a fast low angle shot (FLASH) sequence, along with a control undersampled phantom dataset. ECG and respiratory gating was used to obtain high quality images. After CS reconstructions were applied to all acquired data, resulting images were quantitatively analyzed using the performance metrics of reconstruction error and Structural Similarity Index (SSIM). The comparative analysis indicated that CS reconstructed images from MRI machine undersampled data were indeed comparable to CS reconstructed images from retrospective undersampled data, and that CS techniques are practical in a preclinical setting. The implementation achieved 2 to 4 times acceleration for image acquisition and satisfactory quality of image reconstruction.

3D reconstruction from multi-view VHR-satellite images in MicMac

NASA Astrophysics Data System (ADS)

Rupnik, Ewelina; Pierrot-Deseilligny, Marc; Delorme, Arthur

2018-05-01

This work addresses the generation of high quality digital surface models by fusing multiple depths maps calculated with the dense image matching method. The algorithm is adapted to very high resolution multi-view satellite images, and the main contributions of this work are in the multi-view fusion. The algorithm is insensitive to outliers, takes into account the matching quality indicators, handles non-correlated zones (e.g. occlusions), and is solved with a multi-directional dynamic programming approach. No geometric constraints (e.g. surface planarity) or auxiliary data in form of ground control points are required for its operation. Prior to the fusion procedures, the RPC geolocation parameters of all images are improved in a bundle block adjustment routine. The performance of the algorithm is evaluated on two VHR (Very High Resolution)-satellite image datasets (Pléiades, WorldView-3) revealing its good performance in reconstructing non-textured areas, repetitive patterns, and surface discontinuities.

Context dependent anti-aliasing image reconstruction

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

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

PubMed

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

2014-12-01

To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality. © RSNA, 2014.

Multistatic Array Sampling Scheme for Fast Near-Field Image Reconstruction

DTIC Science & Technology

2016-01-01

1 Multistatic Array Sampling Scheme for Fast Near-Field Image Reconstruction William F. Moulder, James D. Krieger, Denise T. Maurais-Galejs, Huy...described and validated experimentally with the formation of high quality microwave images. It is further shown that the scheme is more than two orders of... scheme (wherein transmitters and receivers are co-located) which require NTNR transmit-receive elements to achieve the same sampling. The second

Cone beam computed tomography in veterinary dentistry.

PubMed

Van Thielen, Bert; Siguenza, Francis; Hassan, Bassam

2012-01-01

The purpose of this study was to assess the feasibility of cone beam computed tomography (CBCT) in imaging dogs and cats for diagnostic dental veterinary applications. CBCT scans of heads of six dogs and two cats were made. Dental panoramic and multi-planar reformatted (MPR) para-sagittal reconstructions were created using specialized software. Image quality and visibility of anatomical landmarks were subjectively assessed by two observers. Good image quality was obtained for the MPR para-sagittal reconstructions through multiple teeth. The image quality of the panoramic reconstructions of dogs was moderate while the panoramic reconstructions of cats were poor since the images were associated with an increased noise level. Segmental panoramic reconstructions of the mouth seem to be useful for studying the dental anatomy especially in dogs. The results of this study using human dental CBCT technology demonstrate the potential of this scanning technology in veterinary medicine. Unfortunately, the moderate image quality obtained with the CBCT technique reported here seems to be inferior to the diagnostic image quality obtained from 2-dimensional dental radiographs. Further research is required to optimize scanning and reconstruction protocols for veterinary applications.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

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

NASA Astrophysics Data System (ADS)

Huang, Xiaokun; Zhang, You; Wang, Jing

2018-02-01

Reconstructing four-dimensional cone-beam computed tomography (4D-CBCT) images directly from respiratory phase-sorted traditional 3D-CBCT projections can capture target motion trajectory, reduce motion artifacts, and reduce imaging dose and time. However, the limited numbers of projections in each phase after phase-sorting decreases CBCT image quality under traditional reconstruction techniques. To address this problem, we developed a simultaneous motion estimation and image reconstruction (SMEIR) algorithm, an iterative method that can reconstruct higher quality 4D-CBCT images from limited projections using an inter-phase intensity-driven motion model. However, the accuracy of the intensity-driven motion model is limited in regions with fine details whose quality is degraded due to insufficient projection number, which consequently degrades the reconstructed image quality in corresponding regions. In this study, we developed a new 4D-CBCT reconstruction algorithm by introducing biomechanical modeling into SMEIR (SMEIR-Bio) to boost the accuracy of the motion model in regions with small fine structures. The biomechanical modeling uses tetrahedral meshes to model organs of interest and solves internal organ motion using tissue elasticity parameters and mesh boundary conditions. This physics-driven approach enhances the accuracy of solved motion in the organ’s fine structures regions. This study used 11 lung patient cases to evaluate the performance of SMEIR-Bio, making both qualitative and quantitative comparisons between SMEIR-Bio, SMEIR, and the algebraic reconstruction technique with total variation regularization (ART-TV). The reconstruction results suggest that SMEIR-Bio improves the motion model’s accuracy in regions containing small fine details, which consequently enhances the accuracy and quality of the reconstructed 4D-CBCT images.

ADART: an adaptive algebraic reconstruction algorithm for discrete tomography.

PubMed

Maestre-Deusto, F Javier; Scavello, Giovanni; Pizarro, Joaquín; Galindo, Pedro L

2011-08-01

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.

Hyperspectral image reconstruction for x-ray fluorescence tomography

DOE PAGES

Gürsoy, Doǧa; Biçer, Tekin; Lanzirotti, Antonio; ...

2015-01-01

A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses a penalty term that has the effect of encouraging local continuity of model parameter estimates in both spatial and spectral dimensions simultaneously. The performance of the reconstruction method is demonstrated with experimental data acquired from a seed of arabidopsis thaliana collected at the 13-ID-E microprobe beamline at the Advanced Photon Source. The resulting element distribution estimates with the proposed approach show significantly better reconstruction quality than the conventional analytical inversionmore » approaches, and allows for a high data compression factor which can reduce data acquisition times remarkably. In particular, this technique provides the capability to tomographically reconstruct full energy dispersive spectra without compromising reconstruction artifacts that impact the interpretation of results.« less

The spontaneous return of sensibility in breasts reconstructed with autologous tissues.

PubMed

Shaw, W W; Orringer, J S; Ko, C Y; Ratto, L L; Mersmann, C A

1997-02-01

Some spontaneous return of sensibility following autologous tissue breast reconstruction is often suspected but not well documented. In the present study, objective touch-pressure, pain, temperature, and vibratory sensibilities were recorded in 33 autologous breast reconstructions at an average of 25.2 months postoperatively. Correlation of the sensory return with patients' satisfaction toward reconstruction was done by a detailed questionnaire. All except one patient regained a variety of sensibilities touch pressure in 97 percent of patients (averaging 81.05 gm/mm2 versus control of 7.98 gm/mm2), pain in 88 percent of patients, heat in 64 percent of patients (45 percent of quadrants), cold in 82 percent of patients (67 percent of quadrants), and high- and low-frequency vibration in 100 percent of patients (high in 90 percent of quadrants, low in 96 percent). Subjectively, 94 percent considered their chest comfortable to touch following reconstruction compared with 34 percent following mastectomy. On a scale from 1 to 10, patients rated their reconstructions an average of 9.3. Our findings confirm the spontaneous return of sensibility following a variety of autologous tissue breast reconstructions. The value of the sensory return is suggested by the high degree of satisfaction in nearly all patients. Further attempts to correlate the degree of sensory return with the degree of satisfaction were inconclusive because of the uniformly high satisfaction reported by the patients. The mechanism of reinnervation appears to come both from the skin margins and from the deep surface of the flap. Future developments in breast reconstruction should take into consideration the eventual quality of sensory return.

Nanomaterial datasets to advance tomography in scanning transmission electron microscopy

DOE PAGES

Levin, Barnaby D. A.; Padgett, Elliot; Chen, Chien-Chun; ...

2016-06-07

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co 2 P nanocrystal, platinum nanoparticles on a carbonmore » nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.« less

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT

PubMed Central

Wang, Ying Yi; Wang, Kai; Xu, Zuo Yu; Song, Yan; Wang, Chu Nan; Zhang, Chong Qing; Sun, Xi Lin; Shen, Bao Zhong

2017-01-01

Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification. PMID:28881772

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT.

PubMed

Wang, Ying Yi; Wang, Kai; Xu, Zuo Yu; Song, Yan; Wang, Chu Nan; Zhang, Chong Qing; Sun, Xi Lin; Shen, Bao Zhong

2017-08-08

Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification.

Nanomaterial datasets to advance tomography in scanning transmission electron microscopy.

PubMed

Levin, Barnaby D A; Padgett, Elliot; Chen, Chien-Chun; Scott, M C; Xu, Rui; Theis, Wolfgang; Jiang, Yi; Yang, Yongsoo; Ophus, Colin; Zhang, Haitao; Ha, Don-Hyung; Wang, Deli; Yu, Yingchao; Abruña, Hector D; Robinson, Richard D; Ercius, Peter; Kourkoutis, Lena F; Miao, Jianwei; Muller, David A; Hovden, Robert

2016-06-07

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co2P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data.

Nanomaterial datasets to advance tomography in scanning transmission electron microscopy

PubMed Central

Levin, Barnaby D.A.; Padgett, Elliot; Chen, Chien-Chun; Scott, M.C.; Xu, Rui; Theis, Wolfgang; Jiang, Yi; Yang, Yongsoo; Ophus, Colin; Zhang, Haitao; Ha, Don-Hyung; Wang, Deli; Yu, Yingchao; Abruña, Hector D.; Robinson, Richard D.; Ercius, Peter; Kourkoutis, Lena F.; Miao, Jianwei; Muller, David A.; Hovden, Robert

2016-01-01

Electron tomography in materials science has flourished with the demand to characterize nanoscale materials in three dimensions (3D). Access to experimental data is vital for developing and validating reconstruction methods that improve resolution and reduce radiation dose requirements. This work presents five high-quality scanning transmission electron microscope (STEM) tomography datasets in order to address the critical need for open access data in this field. The datasets represent the current limits of experimental technique, are of high quality, and contain materials with structural complexity. Included are tomographic series of a hyperbranched Co2P nanocrystal, platinum nanoparticles on a carbon nanofibre imaged over the complete 180° tilt range, a platinum nanoparticle and a tungsten needle both imaged at atomic resolution by equal slope tomography, and a through-focal tilt series of PtCu nanoparticles. A volumetric reconstruction from every dataset is provided for comparison and development of post-processing and visualization techniques. Researchers interested in creating novel data processing and reconstruction algorithms will now have access to state of the art experimental test data. PMID:27272459

Deep learning massively accelerates super-resolution localization microscopy.

PubMed

Ouyang, Wei; Aristov, Andrey; Lelek, Mickaël; Hao, Xian; Zimmer, Christophe

2018-06-01

The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PALM, a computational strategy that uses artificial neural networks to reconstruct super-resolution views from sparse, rapidly acquired localization images and/or widefield images. Simulations and experimental imaging of microtubules, nuclear pores, and mitochondria show that high-quality, super-resolution images can be reconstructed from up to two orders of magnitude fewer frames than usually needed, without compromising spatial resolution. Super-resolution reconstructions are even possible from widefield images alone, though adding localization data improves image quality. We demonstrate super-resolution imaging of >1,000 fields of view containing >1,000 cells in ∼3 h, yielding an image spanning spatial scales from ∼20 nm to ∼2 mm. The drastic reduction in acquisition time and sample irradiation afforded by ANNA-PALM enables faster and gentler high-throughput and live-cell super-resolution imaging.

Generation of complementary sampled phase-only holograms.

PubMed

Tsang, P W M; Chow, Y T; Poon, T-C

2016-10-03

If an image is uniformly down-sampled into a sparse form and converted into a hologram, the phase component alone will be adequate to reconstruct the image. However, the appearance of the reconstructed image is degraded with numerous empty holes. In this paper, we present a low complexity and non-iterative solution to this problem. Briefly, two phase-only holograms are generated for an image, each based on a different down-sampling lattice. Subsequently, the holograms are displayed alternately at high frame rate. The reconstructed images of the 2 holograms will appear to be a single, densely sampled image with enhance visual quality.

Convolutional Sparse Coding for RGB+NIR Imaging.

PubMed

Hu, Xuemei; Heide, Felix; Dai, Qionghai; Wetzstein, Gordon

2018-04-01

Emerging sensor designs increasingly rely on novel color filter arrays (CFAs) to sample the incident spectrum in unconventional ways. In particular, capturing a near-infrared (NIR) channel along with conventional RGB color is an exciting new imaging modality. RGB+NIR sensing has broad applications in computational photography, such as low-light denoising, it has applications in computer vision, such as facial recognition and tracking, and it paves the way toward low-cost single-sensor RGB and depth imaging using structured illumination. However, cost-effective commercial CFAs suffer from severe spectral cross talk. This cross talk represents a major challenge in high-quality RGB+NIR imaging, rendering existing spatially multiplexed sensor designs impractical. In this work, we introduce a new approach to RGB+NIR image reconstruction using learned convolutional sparse priors. We demonstrate high-quality color and NIR imaging for challenging scenes, even including high-frequency structured NIR illumination. The effectiveness of the proposed method is validated on a large data set of experimental captures, and simulated benchmark results which demonstrate that this work achieves unprecedented reconstruction quality.

Ultra-broadband ptychography with self-consistent coherence estimation from a high harmonic source

NASA Astrophysics Data System (ADS)

Odstrčil, M.; Baksh, P.; Kim, H.; Boden, S. A.; Brocklesby, W. S.; Frey, J. G.

2015-09-01

With the aim of improving imaging using table-top extreme ultraviolet sources, we demonstrate coherent diffraction imaging (CDI) with relative bandwidth of 20%. The coherence properties of the illumination probe are identified using the same imaging setup. The presented methods allows for the use of fewer monochromating optics, obtaining higher flux at the sample and thus reach higher resolution or shorter exposure time. This is important in the case of ptychography when a large number of diffraction patterns need to be collected. Our microscopy setup was tested on a reconstruction of an extended sample to show the quality of the reconstruction. We show that high harmonic generation based EUV tabletop microscope can provide reconstruction of samples with a large field of view and high resolution without additional prior knowledge about the sample or illumination.

Mesh quality oriented 3D geometric vascular modeling based on parallel transport frame.

PubMed

Guo, Jixiang; Li, Shun; Chui, Yim Pan; Qin, Jing; Heng, Pheng Ann

2013-08-01

While a number of methods have been proposed to reconstruct geometrically and topologically accurate 3D vascular models from medical images, little attention has been paid to constantly maintain high mesh quality of these models during the reconstruction procedure, which is essential for many subsequent applications such as simulation-based surgical training and planning. We propose a set of methods to bridge this gap based on parallel transport frame. An improved bifurcation modeling method and two novel trifurcation modeling methods are developed based on 3D Bézier curve segments in order to ensure the continuous surface transition at furcations. In addition, a frame blending scheme is implemented to solve the twisting problem caused by frame mismatch of two successive furcations. A curvature based adaptive sampling scheme combined with a mesh quality guided frame tilting algorithm is developed to construct an evenly distributed, non-concave and self-intersection free surface mesh for vessels with distinct radius and high curvature. Extensive experiments demonstrate that our methodology can generate vascular models with better mesh quality than previous methods in terms of surface mesh quality criteria. Copyright © 2013 Elsevier Ltd. All rights reserved.

Influence of reconstruction algorithms on image quality in SPECT myocardial perfusion imaging.

PubMed

Davidsson, Anette; Olsson, Eva; Engvall, Jan; Gustafsson, Agnetha

2017-11-01

We investigated if image- and diagnostic quality in SPECT MPI could be maintained despite a reduced acquisition time adding Depth Dependent Resolution Recovery (DDRR) for image reconstruction. Images were compared with filtered back projection (FBP) and iterative reconstruction using Ordered Subsets Expectation Maximization with (IRAC) and without (IRNC) attenuation correction (AC). Stress- and rest imaging for 15 min was performed on 21 subjects with a dual head gamma camera (Infinia Hawkeye; GE Healthcare), ECG-gating with 8 frames/cardiac cycle and a low-dose CT-scan. A 9 min acquisition was generated using five instead of eight gated frames and was reconstructed with DDRR, with (IRACRR) and without AC (IRNCRR) as well as with FBP. Three experienced nuclear medicine specialists visually assessed anonymized images according to eight criteria on a four point scale, three related to image quality and five to diagnostic confidence. Statistical analysis was performed using Visual Grading Regression (VGR). Observer confidence in statements on image quality was highest for the images that were reconstructed using DDRR (P<0·01 compared to FBP). Iterative reconstruction without DDRR was not superior to FBP. Interobserver variability was significant for statements on image quality (P<0·05) but lower in the diagnostic statements on ischemia and scar. The confidence in assessing ischemia and scar was not different between the reconstruction techniques (P = n.s.). SPECT MPI collected in 9 min, reconstructed with DDRR and AC, produced better image quality than the standard procedure. The observers expressed the highest diagnostic confidence in the DDRR reconstruction. © 2016 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

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

PubMed

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

2018-06-01

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.

An application framework of three-dimensional reconstruction and measurement for endodontic research.

PubMed

Gao, Yuan; Peters, Ove A; Wu, Hongkun; Zhou, Xuedong

2009-02-01

The purpose of this study was to customize an application framework by using the MeVisLab image processing and visualization platform for three-dimensional reconstruction and assessment of tooth and root canal morphology. One maxillary first molar was scanned before and after preparation with ProTaper by using micro-computed tomography. With a customized application framework based on MeVisLab, internal and external anatomy was reconstructed. Furthermore, the dimensions of root canal and radicular dentin were quantified, and effects of canal preparation were assessed. Finally, a virtual preparation with risk analysis was performed to simulate the removal of a broken instrument. This application framework provided an economical platform and met current requirements of endodontic research. The broad-based use of high-quality free software and the resulting exchange of experience might help to improve the quality of endodontic research with micro-computed tomography.

LORAKS makes better SENSE: Phase-constrained partial fourier SENSE reconstruction without phase calibration.

PubMed

Kim, Tae Hyung; Setsompop, Kawin; Haldar, Justin P

2017-03-01

Parallel imaging and partial Fourier acquisition are two classical approaches for accelerated MRI. Methods that combine these approaches often rely on prior knowledge of the image phase, but the need to obtain this prior information can place practical restrictions on the data acquisition strategy. In this work, we propose and evaluate SENSE-LORAKS, which enables combined parallel imaging and partial Fourier reconstruction without requiring prior phase information. The proposed formulation is based on combining the classical SENSE model for parallel imaging data with the more recent LORAKS framework for MR image reconstruction using low-rank matrix modeling. Previous LORAKS-based methods have successfully enabled calibrationless partial Fourier parallel MRI reconstruction, but have been most successful with nonuniform sampling strategies that may be hard to implement for certain applications. By combining LORAKS with SENSE, we enable highly accelerated partial Fourier MRI reconstruction for a broader range of sampling trajectories, including widely used calibrationless uniformly undersampled trajectories. Our empirical results with retrospectively undersampled datasets indicate that when SENSE-LORAKS reconstruction is combined with an appropriate k-space sampling trajectory, it can provide substantially better image quality at high-acceleration rates relative to existing state-of-the-art reconstruction approaches. The SENSE-LORAKS framework provides promising new opportunities for highly accelerated MRI. Magn Reson Med 77:1021-1035, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study.

PubMed

Aurumskjöld, Marie-Louise; Ydström, Kristina; Tingberg, Anders; Söderberg, Marcus

2017-01-01

The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose. To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction. An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose 4 ) and model-based (IMR) iterative reconstruction methods. iDose 4 decreased the noise by 15-45% compared with FBP depending on the level of iDose 4 . The IMR reduced the noise even further, by 60-75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose 4 , and the improvement was even greater with IMR. There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality. © The Foundation Acta Radiologica 2016.

Increasing reconstruction quality of diffractive optical elements displayed with LC SLM

NASA Astrophysics Data System (ADS)

Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Sergey N.

2015-03-01

Phase liquid crystal (LC) spatial light modulators (SLM) are actively used in various applications. However, majority of scientific applications require stable phase modulation which might be hard to achieve with commercially available SLM due to its consumer origin. The use of digital voltage addressing scheme leads to phase temporal fluctuations, which results in lower diffraction efficiency and reconstruction quality of displayed diffractive optical elements (DOE). Due to high periodicity of fluctuations it should be possible to use knowledge of these fluctuations during DOE synthesis to minimize negative effect. We synthesized DOE using accurately measured phase fluctuations of phase LC SLM "HoloEye PLUTO VIS" to minimize its negative impact on displayed DOE reconstruction. Synthesis was conducted with versatile direct search with random trajectory (DSRT) method in the following way. Before DOE synthesis begun, two-dimensional dependency of SLM phase shift on addressed signal level and time from frame start was obtained. Then synthesis begins. First, initial phase distribution is created. Second, random trajectory of consecutive processing of all DOE elements is generated. Then iterative process begins. Each DOE element sequentially has its value changed to one that provides better value of objective criterion, e.g. lower deviation of reconstructed image from original one. If current element value provides best objective criterion value then it left unchanged. After all elements are processed, iteration repeats until stagnation is reached. It is demonstrated that application of SLM phase fluctuations knowledge in DOE synthesis with DSRT method leads to noticeable increase of DOE reconstruction quality.

Socioeconomic Factors Associated with Post-Mastectomy Immediate Reconstruction in a Contemporary Cohort of Breast Cancer Survivors.

PubMed

Schumacher, Jessica R; Taylor, Lauren J; Tucholka, Jennifer L; Poore, Samuel; Eggen, Amanda; Steiman, Jennifer; Wilke, Lee G; Greenberg, Caprice C; Neuman, Heather B

2017-10-01

Post-mastectomy reconstruction is a critical component of high-quality breast cancer care. Prior studies demonstrate socioeconomic disparity in receipt of reconstruction. Our objective was to evaluate trends in receipt of immediate reconstruction and examine socioeconomic factors associated with reconstruction in a contemporary cohort. Using the National Cancer Database, we identified women <75 years of age with stage 0-1 breast cancer treated with mastectomy (n = 297,121). Trends in immediate reconstruction rates (2004-2013) for the overall cohort and stratified by socioeconomic factors were examined using Join-point regression analysis, and annual percentage change (APC) was calculated. We then restricted our sample to a contemporary cohort (2010-2013, n = 145,577). Multivariable logistic regression identified socioeconomic factors associated with immediate reconstruction. Average adjusted predicted probabilities of receiving reconstruction were calculated. Immediate reconstruction rates increased from 27 to 48%. Although absolute rates of reconstruction for each stratification group increased, similar APCs across strata led to persistent gaps in receipt of reconstruction. On multivariable logistic regression using our contemporary cohort, race, income, education, and insurance type were all strongly associated with immediate reconstruction. Patients with the lowest predicted probability of receiving reconstruction were patients with Medicaid who lived in areas with the lowest rates of high-school graduation (Black 42.4% [95% CI 40.5-44.3], White 45.7% [95% CI 43.9-47.4]). Although reconstruction rates have increased dramatically over the past decade, lower rates persist for disadvantaged patients. Understanding how socioeconomic factors influence receipt of reconstruction, and identifying modifiable factors, are critical next steps towards identifying interventions to reduce disparities in breast cancer surgical care.

Reconstructions of Columbia River streamflow from tree-ring chronologies in the Pacific Northwest, USA

USGS Publications Warehouse

Littell, Jeremy; Pederson, Gregory T.; Gray, Stephen T.; Tjoelker, Michael; Hamlet, Alan F.; Woodhouse, Connie A.

2016-01-01

We developed Columbia River streamflow reconstructions using a network of existing, new, and updated tree-ring records sensitive to the main climatic factors governing discharge. Reconstruction quality is enhanced by incorporating tree-ring chronologies where high snowpack limits growth, which better represent the contribution of cool-season precipitation to flow than chronologies from trees positively sensitive to hydroclimate alone. The best performing reconstruction (back to 1609 CE) explains 59% of the historical variability and the longest reconstruction (back to 1502 CE) explains 52% of the variability. Droughts similar to the high-intensity, long-duration low flows observed during the 1920s and 1940s are rare, but occurred in the early 1500s and 1630s-1640s. The lowest Columbia flow events appear to be reflected in chronologies both positively and negatively related to streamflow, implying low snowpack and possibly low warm-season precipitation. High flows of magnitudes observed in the instrumental record appear to have been relatively common, and high flows from the 1680s to 1740s exceeded the magnitude and duration of observed wet periods in the late-19th and 20th Century. Comparisons between the Columbia River reconstructions and future projections of streamflow derived from global climate and hydrologic models show the potential for increased hydrologic variability, which could present challenges for managing water in the face of competing demands

A neural network technique for remeshing of bone microstructure.

PubMed

Fischer, Anath; Holdstein, Yaron

2012-01-01

Today, there is major interest within the biomedical community in developing accurate noninvasive means for the evaluation of bone microstructure and bone quality. Recent improvements in 3D imaging technology, among them development of micro-CT and micro-MRI scanners, allow in-vivo 3D high-resolution scanning and reconstruction of large specimens or even whole bone models. Thus, the tendency today is to evaluate bone features using 3D assessment techniques rather than traditional 2D methods. For this purpose, high-quality meshing methods are required. However, the 3D meshes produced from current commercial systems usually are of low quality with respect to analysis and rapid prototyping. 3D model reconstruction of bone is difficult due to the complexity of bone microstructure. The small bone features lead to a great deal of neighborhood ambiguity near each vertex. The relatively new neural network method for mesh reconstruction has the potential to create or remesh 3D models accurately and quickly. A neural network (NN), which resembles an artificial intelligence (AI) algorithm, is a set of interconnected neurons, where each neuron is capable of making an autonomous arithmetic calculation. Moreover, each neuron is affected by its surrounding neurons through the structure of the network. This paper proposes an extension of the growing neural gas (GNN) neural network technique for remeshing a triangular manifold mesh that represents bone microstructure. This method has the advantage of reconstructing the surface of a genus-n freeform object without a priori knowledge regarding the original object, its topology, or its shape.

High Spatial and Temporal Resolution Dynamic Contrast-Enhanced Magnetic Resonance Angiography (CE-MRA) using Compressed Sensing with Magnitude Image Subtraction

PubMed Central

Rapacchi, Stanislas; Han, Fei; Natsuaki, Yutaka; Kroeker, Randall; Plotnik, Adam; Lehman, Evan; Sayre, James; Laub, Gerhard; Finn, J Paul; Hu, Peng

2014-01-01

Purpose We propose a compressed-sensing (CS) technique based on magnitude image subtraction for high spatial and temporal resolution dynamic contrast-enhanced MR angiography (CE-MRA). Methods Our technique integrates the magnitude difference image into the CS reconstruction to promote subtraction sparsity. Fully sampled Cartesian 3D CE-MRA datasets from 6 volunteers were retrospectively under-sampled and three reconstruction strategies were evaluated: k-space subtraction CS, independent CS, and magnitude subtraction CS. The techniques were compared in image quality (vessel delineation, image artifacts, and noise) and image reconstruction error. Our CS technique was further tested on 7 volunteers using a prospectively under-sampled CE-MRA sequence. Results Compared with k-space subtraction and independent CS, our magnitude subtraction CS provides significantly better vessel delineation and less noise at 4X acceleration, and significantly less reconstruction error at 4X and 8X (p<0.05 for all). On a 1–4 point image quality scale in vessel delineation, our technique scored 3.8±0.4 at 4X, 2.8±0.4 at 8X and 2.3±0.6 at 12X acceleration. Using our CS sequence at 12X acceleration, we were able to acquire dynamic CE-MRA with higher spatial and temporal resolution than current clinical TWIST protocol while maintaining comparable image quality (2.8±0.5 vs. 3.0±0.4, p=NS). Conclusion Our technique is promising for dynamic CE-MRA. PMID:23801456

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

NASA Astrophysics Data System (ADS)

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.

A Model of Regularization Parameter Determination in Low-Dose X-Ray CT Reconstruction Based on Dictionary Learning

PubMed Central

Zhang, Cheng; Zhang, Tao; Li, Ming; Lu, Yanfei; You, Jiali; Guan, Yihui

2015-01-01

In recent years, X-ray computed tomography (CT) is becoming widely used to reveal patient's anatomical information. However, the side effect of radiation, relating to genetic or cancerous diseases, has caused great public concern. The problem is how to minimize radiation dose significantly while maintaining image quality. As a practical application of compressed sensing theory, one category of methods takes total variation (TV) minimization as the sparse constraint, which makes it possible and effective to get a reconstruction image of high quality in the undersampling situation. On the other hand, a preliminary attempt of low-dose CT reconstruction based on dictionary learning seems to be another effective choice. But some critical parameters, such as the regularization parameter, cannot be determined by detecting datasets. In this paper, we propose a reweighted objective function that contributes to a numerical calculation model of the regularization parameter. A number of experiments demonstrate that this strategy performs well with better reconstruction images and saving of a large amount of time. PMID:26550024

Singular value decomposition metrics show limitations of detector design in diffuse fluorescence tomography

PubMed Central

Leblond, Frederic; Tichauer, Kenneth M.; Pogue, Brian W.

2010-01-01

The spatial resolution and recovered contrast of images reconstructed from diffuse fluorescence tomography data are limited by the high scattering properties of light propagation in biological tissue. As a result, the image reconstruction process can be exceedingly vulnerable to inaccurate prior knowledge of tissue optical properties and stochastic noise. In light of these limitations, the optimal source-detector geometry for a fluorescence tomography system is non-trivial, requiring analytical methods to guide design. Analysis of the singular value decomposition of the matrix to be inverted for image reconstruction is one potential approach, providing key quantitative metrics, such as singular image mode spatial resolution and singular data mode frequency as a function of singular mode. In the present study, these metrics are used to analyze the effects of different sources of noise and model errors as related to image quality in the form of spatial resolution and contrast recovery. The image quality is demonstrated to be inherently noise-limited even when detection geometries were increased in complexity to allow maximal tissue sampling, suggesting that detection noise characteristics outweigh detection geometry for achieving optimal reconstructions. PMID:21258566

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

PubMed

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. 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 into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

Resolving the Complexity of Human Skin Metagenomes Using Single-Molecule Sequencing

PubMed Central

Tsai, Yu-Chih; Deming, Clayton; Segre, Julia A.; Kong, Heidi H.; Korlach, Jonas

2016-01-01

ABSTRACT Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communities. However, the resultant “genomes” are typically fragmented and incomplete due to the limited ability of short-read sequence data to assemble complex or low-coverage regions. Here, we use single-molecule, real-time (SMRT) sequencing to reconstruct a high-quality, closed genome of a previously uncharacterized Corynebacterium simulans and its companion bacteriophage from a skin metagenomic sample. Considerable improvement in assembly quality occurs in hybrid approaches incorporating short-read data, with even relatively small amounts of long-read data being sufficient to improve metagenome reconstruction. Using short-read data to evaluate strain variation of this C. simulans in its skin community at single-nucleotide resolution, we observed a dominant C. simulans strain with moderate allelic heterozygosity throughout the population. We demonstrate the utility of SMRT sequencing and hybrid approaches in metagenome quantitation, reconstruction, and annotation. PMID:26861018

The effect of exit beam phase aberrations on parallel beam coherent x-ray reconstructions

NASA Astrophysics Data System (ADS)

Hruszkewycz, S. O.; Harder, R.; Xiao, X.; Fuoss, P. H.

2010-12-01

Diffraction artifacts from imperfect x-ray windows near the sample are an important consideration in the design of coherent x-ray diffraction measurements. In this study, we used simulated and experimental diffraction patterns in two and three dimensions to explore the effect of phase imperfections in a beryllium window (such as a void or inclusion) on the convergence behavior of phasing algorithms and on the ultimate reconstruction. A predictive relationship between beam wavelength, sample size, and window position was derived to explain the dependence of reconstruction quality on beryllium defect size. Defects corresponding to this prediction cause the most damage to the sample exit wave and induce signature error oscillations during phasing that can be used as a fingerprint of experimental x-ray window artifacts. The relationship between x-ray window imperfection size and coherent x-ray diffractive imaging reconstruction quality explored in this work can play an important role in designing high-resolution in situ coherent imaging instrumentation and will help interpret the phasing behavior of coherent diffraction measured in these in situ environments.

The effect of exit beam phase aberrations on parallel beam coherent x-ray reconstructions.

PubMed

Hruszkewycz, S O; Harder, R; Xiao, X; Fuoss, P H

2010-12-01

Diffraction artifacts from imperfect x-ray windows near the sample are an important consideration in the design of coherent x-ray diffraction measurements. In this study, we used simulated and experimental diffraction patterns in two and three dimensions to explore the effect of phase imperfections in a beryllium window (such as a void or inclusion) on the convergence behavior of phasing algorithms and on the ultimate reconstruction. A predictive relationship between beam wavelength, sample size, and window position was derived to explain the dependence of reconstruction quality on beryllium defect size. Defects corresponding to this prediction cause the most damage to the sample exit wave and induce signature error oscillations during phasing that can be used as a fingerprint of experimental x-ray window artifacts. The relationship between x-ray window imperfection size and coherent x-ray diffractive imaging reconstruction quality explored in this work can play an important role in designing high-resolution in situ coherent imaging instrumentation and will help interpret the phasing behavior of coherent diffraction measured in these in situ environments.

Monochromatic-beam-based dynamic X-ray microtomography based on OSEM-TV algorithm.

PubMed

Xu, Liang; Chen, Rongchang; Yang, Yiming; Deng, Biao; Du, Guohao; Xie, Honglan; Xiao, Tiqiao

2017-01-01

Monochromatic-beam-based dynamic X-ray computed microtomography (CT) was developed to observe evolution of microstructure inside samples. However, the low flux density results in low efficiency in data collection. To increase efficiency, reducing the number of projections should be a practical solution. However, it has disadvantages of low image reconstruction quality using the traditional filtered back projection (FBP) algorithm. In this study, an iterative reconstruction method using an ordered subset expectation maximization-total variation (OSEM-TV) algorithm was employed to address and solve this problem. The simulated results demonstrated that normalized mean square error of the image slices reconstructed by the OSEM-TV algorithm was about 1/4 of that by FBP. Experimental results also demonstrated that the density resolution of OSEM-TV was high enough to resolve different materials with the number of projections less than 100. As a result, with the introduction of OSEM-TV, the monochromatic-beam-based dynamic X-ray microtomography is potentially practicable for the quantitative and non-destructive analysis to the evolution of microstructure with acceptable efficiency in data collection and reconstructed image quality.

Improving transcriptome construction in non-model organisms: integrating manual and automated gene definition in Emiliania huxleyi.

PubMed

Feldmesser, Ester; Rosenwasser, Shilo; Vardi, Assaf; Ben-Dor, Shifra

2014-02-22

The advent of Next Generation Sequencing technologies and corresponding bioinformatics tools allows the definition of transcriptomes in non-model organisms. Non-model organisms are of great ecological and biotechnological significance, and consequently the understanding of their unique metabolic pathways is essential. Several methods that integrate de novo assembly with genome-based assembly have been proposed. Yet, there are many open challenges in defining genes, particularly where genomes are not available or incomplete. Despite the large numbers of transcriptome assemblies that have been performed, quality control of the transcript building process, particularly on the protein level, is rarely performed if ever. To test and improve the quality of the automated transcriptome reconstruction, we used manually defined and curated genes, several of them experimentally validated. Several approaches to transcript construction were utilized, based on the available data: a draft genome, high quality RNAseq reads, and ESTs. In order to maximize the contribution of the various data, we integrated methods including de novo and genome based assembly, as well as EST clustering. After each step a set of manually curated genes was used for quality assessment of the transcripts. The interplay between the automated pipeline and the quality control indicated which additional processes were required to improve the transcriptome reconstruction. We discovered that E. huxleyi has a very high percentage of non-canonical splice junctions, and relatively high rates of intron retention, which caused unique issues with the currently available tools. While individual tools missed genes and artificially joined overlapping transcripts, combining the results of several tools improved the completeness and quality considerably. The final collection, created from the integration of several quality control and improvement rounds, was compared to the manually defined set both on the DNA and protein levels, and resulted in an improvement of 20% versus any of the read-based approaches alone. To the best of our knowledge, this is the first time that an automated transcript definition is subjected to quality control using manually defined and curated genes and thereafter the process is improved. We recommend using a set of manually curated genes to troubleshoot transcriptome reconstruction.

SubspaceEM: A Fast Maximum-a-posteriori Algorithm for Cryo-EM Single Particle Reconstruction

PubMed Central

Dvornek, Nicha C.; Sigworth, Fred J.; Tagare, Hemant D.

2015-01-01

Single particle reconstruction methods based on the maximum-likelihood principle and the expectation-maximization (E–M) algorithm are popular because of their ability to produce high resolution structures. However, these algorithms are computationally very expensive, requiring a network of computational servers. To overcome this computational bottleneck, we propose a new mathematical framework for accelerating maximum-likelihood reconstructions. The speedup is by orders of magnitude and the proposed algorithm produces similar quality reconstructions compared to the standard maximum-likelihood formulation. Our approach uses subspace approximations of the cryo-electron microscopy (cryo-EM) data and projection images, greatly reducing the number of image transformations and comparisons that are computed. Experiments using simulated and actual cryo-EM data show that speedup in overall execution time compared to traditional maximum-likelihood reconstruction reaches factors of over 300. PMID:25839831

Structured light optical microscopy for three-dimensional reconstruction of technical surfaces

NASA Astrophysics Data System (ADS)

Kettel, Johannes; Reinecke, Holger; Müller, Claas

2016-04-01

In microsystems technology quality control of micro structured surfaces with different surface properties is playing an ever more important role. The process of quality control incorporates three-dimensional (3D) reconstruction of specularand diffusive reflecting technical surfaces. Due to the demand on high measurement accuracy and data acquisition rates, structured light optical microscopy has become a valuable solution to solve this problem providing high vertical and lateral resolution. However, 3D reconstruction of specular reflecting technical surfaces still remains a challenge to optical measurement principles. In this paper we present a measurement principle based on structured light optical microscopy which enables 3D reconstruction of specular- and diffusive reflecting technical surfaces. It is realized using two light paths of a stereo microscope equipped with different magnification levels. The right optical path of the stereo microscope is used to project structured light onto the object surface. The left optical path is used to capture the structured illuminated object surface with a camera. Structured light patterns are generated by a Digital Light Processing (DLP) device in combination with a high power Light Emitting Diode (LED). Structured light patterns are realized as a matrix of discrete light spots to illuminate defined areas on the object surface. The introduced measurement principle is based on multiple and parallel processed point measurements. Analysis of the measured Point Spread Function (PSF) by pattern recognition and model fitting algorithms enables the precise calculation of 3D coordinates. Using exemplary technical surfaces we demonstrate the successful application of our measurement principle.

Compressed sensing for energy-efficient wireless telemonitoring of noninvasive fetal ECG via block sparse Bayesian learning.

PubMed

Zhang, Zhilin; Jung, Tzyy-Ping; Makeig, Scott; Rao, Bhaskar D

2013-02-01

Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a telemonitoring system via a wireless body area network with low energy consumption for ambulatory use is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in compressing/reconstructing data with low energy consumption. However, due to some specific characteristics of raw FECG recordings such as nonsparsity and strong noise contamination, current CS algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not destroy the interdependence relation among the multichannel recordings. This ensures that the independent component analysis decomposition of the reconstructed recordings has high fidelity. Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero entries. This shows that the framework, compared to other algorithms such as current CS algorithms and wavelet algorithms, can greatly reduce code execution in CPU in the data compression stage.

X-ray computed tomography using curvelet sparse regularization.

PubMed

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Cost-effectiveness analysis of implants versus autologous perforator flaps using the BREAST-Q.

PubMed

Matros, Evan; Albornoz, Claudia R; Razdan, Shantanu N; Mehrara, Babak J; Macadam, Sheina A; Ro, Teresa; McCarthy, Colleen M; Disa, Joseph J; Cordeiro, Peter G; Pusic, Andrea L

2015-04-01

Reimbursement has been recognized as a physician barrier to autologous reconstruction. Autologous reconstructions are more expensive than prosthetic reconstructions, but provide greater health-related quality of life. The authors' hypothesis is that autologous tissue reconstructions are cost-effective compared with prosthetic techniques when considering health-related quality of life and patient satisfaction. A cost-effectiveness analysis from the payer perspective, including patient input, was performed for unilateral and bilateral reconstructions with deep inferior epigastric perforator (DIEP) flaps and implants. The effectiveness measure was derived using the BREAST-Q and interpreted as the cost for obtaining 1 year of perfect breast health-related quality-adjusted life-year. Costs were obtained from the 2010 Nationwide Inpatient Sample. The incremental cost-effectiveness ratio was generated. A sensitivity analysis for age and stage at diagnosis was performed. BREAST-Q scores from 309 patients with implants and 217 DIEP flap reconstructions were included. The additional cost for obtaining 1 year of perfect breast-related health for a unilateral DIEP flap compared with implant reconstruction was $11,941. For bilateral DIEP flaps compared with implant reconstructions, the cost for an additional breast health-related quality-adjusted life-year was $28,017. The sensitivity analysis demonstrated that the cost for an additional breast health-related quality-adjusted life-year for DIEP flaps compared with implants was less for younger patients and earlier stage breast cancer. DIEP flaps are cost-effective compared with implants, especially for unilateral reconstructions. Cost-effectiveness of autologous techniques is maximized in women with longer life expectancy. Patient-reported outcomes findings can be incorporated into cost-effectiveness analyses to demonstrate the relative value of reconstructive procedures.

Terahertz imaging with compressed sensing and phase retrieval.

PubMed

Chan, Wai Lam; Moravec, Matthew L; Baraniuk, Richard G; Mittleman, Daniel M

2008-05-01

We describe a novel, high-speed pulsed terahertz (THz) Fourier imaging system based on compressed sensing (CS), a new signal processing theory, which allows image reconstruction with fewer samples than traditionally required. Using CS, we successfully reconstruct a 64 x 64 image of an object with pixel size 1.4 mm using a randomly chosen subset of the 4096 pixels, which defines the image in the Fourier plane, and observe improved reconstruction quality when we apply phase correction. For our chosen image, only about 12% of the pixels are required for reassembling the image. In combination with phase retrieval, our system has the capability to reconstruct images with only a small subset of Fourier amplitude measurements and thus has potential application in THz imaging with cw sources.

Nonlinear PET parametric image reconstruction with MRI information using kernel method

NASA Astrophysics Data System (ADS)

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.

Reconstructing color images of astronomical objects using black and white spectroscopic emulsions

NASA Technical Reports Server (NTRS)

Dufour, R. I.; Martins, D. H.

1976-01-01

A color photograph of the peculiar elliptical galaxy NGC 5128 (Centaurus A) has been reconstructed from three Kodak 103a emulsion type photographs by projecting positives of the three B&W plates through appropriate filters onto a conventional color film. The resulting photograph shows color balance and latitude characteristics superior to color photographs of similar astronomical objects made with commercially available conventional color film. Similar results have been obtained for color reconstructed photographs of the Large and Small Magellanic Clouds. These and other results suggest that these projection-reconstruction techniques can be used to obtain high-quality color photographs of astronomical objects which overcome many of the problems associated with the use of conventional color film for the long exposures required in astronomy.

AFFINE-CORRECTED PARADISE: FREE-BREATHING PATIENT-ADAPTIVE CARDIAC MRI WITH SENSITIVITY ENCODING

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

We propose a real-time cardiac imaging method with parallel MRI that allows for free breathing during imaging and does not require cardiac or respiratory gating. The method is based on the recently proposed PARADISE (Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding) scheme. The new acquisition method adapts the PARADISE k-t space sampling pattern according to an affine model of the respiratory motion. The reconstruction scheme involves multi-channel time-sequential imaging with time-varying channels. All model parameters are adapted to the imaged patient as part of the experiment and drive both data acquisition and cine reconstruction. Simulated cardiac MRI experiments using the realistic NCAT phantom show high quality cine reconstructions and robustness to modeling inaccuracies. PMID:24390159

Analysis of algebraic reconstruction technique for accurate imaging of gas temperature and concentration based on tunable diode laser absorption spectroscopy

NASA Astrophysics Data System (ADS)

Hui-Hui, Xia; Rui-Feng, Kan; Jian-Guo, Liu; Zhen-Yu, Xu; Ya-Bai, He

2016-06-01

An improved algebraic reconstruction technique (ART) combined with tunable diode laser absorption spectroscopy(TDLAS) is presented in this paper for determining two-dimensional (2D) distribution of H2O concentration and temperature in a simulated combustion flame. This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy. It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid, and after that point, the number of projection rays has little influence on reconstruction accuracy. It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method. In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed, and the capability of this new method is evaluated by using appropriate assessment parameters. By using this new approach, not only the concentration reconstruction accuracy is greatly improved, but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation. Finally, a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method. Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles. This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices. Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61205151), the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2014YQ060537), and the National Basic Research Program, China (Grant No. 2013CB632803).

Technical Note: FreeCT_wFBP: A robust, efficient, open-source implementation of weighted filtered backprojection for helical, fan-beam CT.

PubMed

Hoffman, John; Young, Stefano; Noo, Frédéric; McNitt-Gray, Michael

2016-03-01

With growing interest in quantitative imaging, radiomics, and CAD using CT imaging, the need to explore the impacts of acquisition and reconstruction parameters has grown. This usually requires extensive access to the scanner on which the data were acquired and its workflow is not designed for large-scale reconstruction projects. Therefore, the authors have developed a freely available, open-source software package implementing a common reconstruction method, weighted filtered backprojection (wFBP), for helical fan-beam CT applications. FreeCT_wFBP is a low-dependency, GPU-based reconstruction program utilizing c for the host code and Nvidia CUDA C for GPU code. The software is capable of reconstructing helical scans acquired with arbitrary pitch-values, and sampling techniques such as flying focal spots and a quarter-detector offset. In this work, the software has been described and evaluated for reconstruction speed, image quality, and accuracy. Speed was evaluated based on acquisitions of the ACR CT accreditation phantom under four different flying focal spot configurations. Image quality was assessed using the same phantom by evaluating CT number accuracy, uniformity, and contrast to noise ratio (CNR). Finally, reconstructed mass-attenuation coefficient accuracy was evaluated using a simulated scan of a FORBILD thorax phantom and comparing reconstructed values to the known phantom values. The average reconstruction time evaluated under all flying focal spot configurations was found to be 17.4 ± 1.0 s for a 512 row × 512 column × 32 slice volume. Reconstructions of the ACR phantom were found to meet all CT Accreditation Program criteria including CT number, CNR, and uniformity tests. Finally, reconstructed mass-attenuation coefficient values of water within the FORBILD thorax phantom agreed with original phantom values to within 0.0001 mm(2)/g (0.01%). FreeCT_wFBP is a fast, highly configurable reconstruction package for third-generation CT available under the GNU GPL. It shows good performance with both clinical and simulated data.

A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

NASA Astrophysics Data System (ADS)

Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

2018-01-01

Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

A Novel Image Compression Algorithm for High Resolution 3D Reconstruction

NASA Astrophysics Data System (ADS)

Siddeq, M. M.; Rodrigues, M. A.

2014-06-01

This research presents a novel algorithm to compress high-resolution images for accurate structured light 3D reconstruction. Structured light images contain a pattern of light and shadows projected on the surface of the object, which are captured by the sensor at very high resolutions. Our algorithm is concerned with compressing such images to a high degree with minimum loss without adversely affecting 3D reconstruction. The Compression Algorithm starts with a single level discrete wavelet transform (DWT) for decomposing an image into four sub-bands. The sub-band LL is transformed by DCT yielding a DC-matrix and an AC-matrix. The Minimize-Matrix-Size Algorithm is used to compress the AC-matrix while a DWT is applied again to the DC-matrix resulting in LL2, HL2, LH2 and HH2 sub-bands. The LL2 sub-band is transformed by DCT, while the Minimize-Matrix-Size Algorithm is applied to the other sub-bands. The proposed algorithm has been tested with images of different sizes within a 3D reconstruction scenario. The algorithm is demonstrated to be more effective than JPEG2000 and JPEG concerning higher compression rates with equivalent perceived quality and the ability to more accurately reconstruct the 3D models.

SU-F-J-74: High Z Geometric Integrity and Beam Hardening Artifact Assessment Using a Retrospective Metal Artifact Reduction (MAR) Reconstruction Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woods, K; DiCostanzo, D; Gupta, N

Purpose: To test the efficacy of a retrospective metal artifact reduction (MAR) reconstruction algorithm for a commercial computed tomography (CT) scanner for radiation therapy purposes. Methods: High Z geometric integrity and artifact reduction analysis was performed with three phantoms using General Electric’s (GE) Discovery CT. The three phantoms included: a Computerized Imaging Reference Systems (CIRS) electron density phantom (Model 062) with a 6.5 mm diameter titanium rod insert, a custom spine phantom using Synthes Spine hardware submerged in water, and a dental phantom with various high Z fillings submerged in water. Each phantom was reconstructed using MAR and compared againstmore » the original scan. Furthermore, each scenario was tested using standard and extended Hounsfield Unit (HU) ranges. High Z geometric integrity was performed using the CIRS phantom, while the artifact reduction was performed using all three phantoms. Results: Geometric integrity of the 6.5 mm diameter rod was slightly overestimated for non-MAR scans for both standard and extended HU. With MAR reconstruction, the rod was underestimated for both standard and extended HU. For artifact reduction, the mean and standard deviation was compared in a volume of interest (VOI) in the surrounding material (water and water equivalent material, ∼0HU). Overall, the mean value of the VOI was closer to 0 HU for the MAR reconstruction compared to the non-MAR scan for most phantoms. Additionally, the standard deviations for all phantoms were greatly reduced using MAR reconstruction. Conclusion: GE’s MAR reconstruction algorithm improves image quality with the presence of high Z material with minimal degradation of its geometric integrity. High Z delineation can be carried out with proper contouring techniques. The effects of beam hardening artifacts are greatly reduced with MAR reconstruction. Tissue corrections due to these artifacts can be eliminated for simple high Z geometries and greatly reduced for more complex geometries.« less

Intraoperative imaging for patient safety and QA: detection of intracranial hemorrhage using C-arm cone-beam CT

NASA Astrophysics Data System (ADS)

Schafer, Sebastian; Wang, Adam; Otake, Yoshito; Stayman, J. W.; Zbijewski, Wojciech; Kleinszig, Gerhard; Xia, Xuewei; Gallia, Gary L.; Siewerdsen, Jeffrey H.

2013-03-01

Intraoperative imaging could improve patient safety and quality assurance (QA) via the detection of subtle complications that might otherwise only be found hours after surgery. Such capability could therefore reduce morbidity and the need for additional intervention. Among the severe adverse events that could be more quickly detected by high-quality intraoperative imaging is acute intracranial hemorrhage (ICH), conventionally assessed using post-operative CT. A mobile C-arm capable of high-quality cone-beam CT (CBCT) in combination with advanced image reconstruction techniques is reported as a means of detecting ICH in the operating room. The system employs an isocentric C-arm with a flat-panel detector in dual gain mode, correction of x-ray scatter and beam-hardening, and a penalized likelihood (PL) iterative reconstruction method. Performance in ICH detection was investigated using a quantitative phantom focusing on (non-contrast-enhanced) blood-brain contrast, an anthropomorphic head phantom, and a porcine model with injection of fresh blood bolus. The visibility of ICH was characterized in terms of contrast-to-noise ratio (CNR) and qualitative evaluation of images by a neurosurgeon. Across a range of size and contrast of the ICH as well as radiation dose from the CBCT scan, the CNR was found to increase from ~2.2-3.7 for conventional filtered backprojection (FBP) to ~3.9-5.4 for PL at equivalent spatial resolution. The porcine model demonstrated superior ICH detectability for PL. The results support the role of high-quality mobile C-arm CBCT employing advanced reconstruction algorithms for detecting subtle complications in the operating room at lower radiation dose and lower cost than intraoperative CT scanners and/or fixedroom C-arms. Such capability could present a potentially valuable aid to patient safety and QA.

WE-EF-207-09: Single-Scan Dual-Energy CT Using Primary Modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrongolo, M; Zhu, L

Purpose: Compared with conventional CT, dual energy CT (DECT) provides better material differentiation but requires projection data with two different effective x-ray spectra. Current DECT scanners use either a two-scan setting or costly imaging components, which are not feasible or available on open-gantry cone-beam CT systems. We propose a hardware-based method which utilizes primary modulation to enable single-scan DECT on a conventional CT scanner. The CT imaging geometry of primary modulation is identical to that used in our previous method for scatter removal, making it possible for future combination with effective scatter correction on the same CT scanner. Methods: Wemore » insert an attenuation sheet with a spatially-varying pattern - primary modulator-between the x-ray source and the imaged object. During the CT scan, the modulator selectively hardens the x-ray beam at specific detector locations. Thus, the proposed method simultaneously acquires high and low energy data. High and low energy CT images are then reconstructed from projections with missing data via an iterative CT reconstruction algorithm with gradient weighting. Proof-of-concept studies are performed using a copper modulator on a cone-beam CT system. Results: Our preliminary results on the Catphan(c) 600 phantom indicate that the proposed method for single-scan DECT is able to successfully generate high-quality high and low energy CT images and distinguish different materials through basis material decomposition. By applying correction algorithms and using all of the acquired projection data, we can reconstruct a single CT image of comparable image quality to conventional CT images, i.e., without primary modulation. Conclusion: This work shows great promise in using a primary modulator to perform high-quality single-scan DECT imaging. Future studies will test method performance on anthropomorphic phantoms and perform quantitative analyses on image qualities and DECT decomposition accuracy. We will use simulations to optimize the modulator material and geometry parameters.« less

System Matrix Analysis for Computed Tomography Imaging

PubMed Central

Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo

2015-01-01

In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482

Dense Matching Comparison Between Census and a Convolutional Neural Network Algorithm for Plant Reconstruction

NASA Astrophysics Data System (ADS)

Xia, Y.; Tian, J.; d'Angelo, P.; Reinartz, P.

2018-05-01

3D reconstruction of plants is hard to implement, as the complex leaf distribution highly increases the difficulty level in dense matching. Semi-Global Matching has been successfully applied to recover the depth information of a scene, but may perform variably when different matching cost algorithms are used. In this paper two matching cost computation algorithms, Census transform and an algorithm using a convolutional neural network, are tested for plant reconstruction based on Semi-Global Matching. High resolution close-range photogrammetric images from a handheld camera are used for the experiment. The disparity maps generated based on the two selected matching cost methods are comparable with acceptable quality, which shows the good performance of Census and the potential of neural networks to improve the dense matching.

Respiratory Motion-Resolved Compressed Sensing Reconstruction of Free-Breathing Radial Acquisition for Dynamic Liver MRI

PubMed Central

Chandarana, Hersh; Feng, Li; Ream, Justin; Wang, Annie; Babb, James S; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo

2015-01-01

Purpose Demonstrate feasibility of free-breathing radial acquisition with respiratory motion-resolved compressed sensing (CS) reconstruction (XD-GRASP) for multiphase dynamic Gd-EOB-DTPA enhanced liver imaging, and compare image quality to CS reconstruction with respiratory motion-averaging (GRASP) and prior conventional breath-held Cartesian-sampled datasets (BH-VIBE) in same patients. Subjects and Methods In this HIPAA-compliant prospective study, 16 subjects underwent free-breathing continuous radial acquisition during Gd-EOB-DTPA injection, and had prior BH-VIBE exam available. Acquired data were reconstructed using motion-averaging GRASP approach, in which consecutive 84-spokes were grouped in each contrast-enhanced phase for a temporal resolution of ~14 seconds. Additionally, respiratory motion-resolved reconstruction was performed from the same k-space data, by sorting each contrast-enhanced phase into multiple respiratory motion states using compressed sensing algorithm named XD-GRASP, which exploits sparsity along both the contrast-enhancement and respiratory-state dimensions. Contrast-enhanced dynamic multi-phase XD-GRASP, GRASP, and BH-VIBE images were anonymized, pooled together in a random order and presented to two board-certified radiologists for independent evaluation of image quality, with higher score indicating more optimal exam. Results XD-GRASP reconstructions had significantly (all p<0.05) higher overall image quality scores compared to GRASP for early arterial (Reader 1: 4.3 ± 0.6 vs. 3.31 ± 0.6 ; Reader 2: 3.81 ± 0.8 vs. 3.38 ± 0.9) and late arterial (Reader 1: 4.5 ± 0.6 vs. 3.63 ± 0.6; Reader 2: 3.56 ± 0.5 vs. 2.88 ± 0.7) phases of enhancement for both readers. XD-GRASP also had higher overall image quality score in portal venous phase which was significant for Reader 1 (4.44 ± 0.5 vs. 3.75 ± 0.8; p=0.002). In addition, XD-GRASP had higher overall image quality score compared to BH-VIBE for early (Reader 1: 4.3±0.6 vs. 3.88±0.6; Reader 2: 3.81±0.8 vs. 3.50±1.0) and late (Reader 1: 4.5±0.6 vs. 3.44±0.6; Reader 2: 3.56±0.5 vs. 2.94±0.9) arterial phases. Conclusion Free-breathing motion-resolved XD-GRASP reconstructions provide diagnostic high-quality multiphase images in patients undergoing Gd-EOB-DTPA-enhanced liver exam. PMID:26146869

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

PubMed

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 that the reconstructions from super-sampled data sets using a fine system matrix yield improved image quality compared to the reconstructions using a coarse system matrix. Super-sampling reconstructions with different count levels showed that the more spatial-resolution improvement can be obtained with higher count at a larger iteration number. The authors developed a super-sampling reconstruction framework that can reconstruct super-resolution images using the super-sampling data sets simultaneously with known acquisition motion. The super-sampling PET acquisition using the proposed algorithms provides an effective and economic way to improve image quality for PET imaging, which has an important implication in preclinical and clinical region-of-interest PET imaging applications.

Development of acoustic model-based iterative reconstruction technique for thick-concrete imaging

NASA Astrophysics Data System (ADS)

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

The CMS muon system: status and upgrades for LHC Run-2 and performance of muon reconstruction with 13 TeV data

NASA Astrophysics Data System (ADS)

Battilana, C.

2017-01-01

The CMS muon system has played a key role for many physics results obtained from the LHC Run-1 and Run-2 data. During the Long Shutdown (2013-2014), as well as during the last year-end technical stop (2015-2016), significant consolidation and upgrades have been carried out on the muon detectors and on the L1 muon trigger. The algorithms for muon reconstruction and identification have also been improved for both the High-Level Trigger and the offline reconstruction. Results of the performance of muon detectors, reconstruction and trigger, obtained using data collected at 13 TeV centre-of-mass energy during the 2015 and 2016 LHC runs, will be presented. Comparison of simulation with experimental data will also be discussed where relevant. The system's state of the art performance will be shown, and the improvements foreseen to achieve excellent overall quality of muon reconstruction in CMS, in the conditions expected during the high-luminosity phase of Run-2, will be described.

Can sinogram-affirmed iterative (SAFIRE) reconstruction improve imaging quality on low-dose lung CT screening compared with traditional filtered back projection (FBP) reconstruction?

PubMed

Yang, Wen Jie; Yan, Fu Hua; Liu, Bo; Pang, Li Fang; Hou, Liang; Zhang, Huan; Pan, Zi Lai; Chen, Ke Min

2013-01-01

To evaluate the performance of sinogram-affirmed iterative (SAFIRE) reconstruction on image quality of low-dose lung computed tomographic (CT) screening compared with filtered back projection (FBP). Three hundred four patients for annual low-dose lung CT screening were examined by a dual-source CT system at 120 kilovolt (peak) with reference tube current of 40 mA·s. Six image serials were reconstructed, including one data set of FBP and 5 data sets of SAFIRE with different reconstruction strengths from 1 to 5. Image noise was recorded; and subjective scores of image noise, images artifacts, and the overall image quality were also assessed by 2 radiologists. The mean ± SD weight for all patients was 66.3 ± 12.8 kg, and the body mass index was 23.4 ± 3.2. The mean ± SD dose-length product was 95.2 ± 30.6 mGy cm, and the mean ± SD effective dose was 1.6 ± 0.5 mSv. The observation agreements for image noise grade, artifact grade, and the overall image quality were 0.785, 0.595 and 0.512, respectively. Among the overall 6 data sets, both the measured mean objective image noise and the subjective image noise of FBP was the highest, and the image noise decreased with the increasing of SAFIRE reconstruction strength. The data sets of S3 obtained the best image quality scores. Sinogram-affirmed iterative reconstruction can significantly improve image quality of low-dose lung CT screening compared with FBP, and SAFIRE with reconstruction strength 3 was a pertinent choice for low-dose lung CT.

High-resolution multiproxy climate reconstruction for southern South America since 1000 AD: LOTRED-SA, a new IGBP-PAGES initiative

NASA Astrophysics Data System (ADS)

Kiefer, T.

2006-12-01

Regional high-resolution multi-proxy climate reconstructions and associated uncertainties for the last ca. 1000 years is a priority area of future research within the Past Global Changes project of the International Geosphere Biosphere Programme (IGBP-PAGES). Considerable progress has been made in the reconstruction techniques, in the handling of a wide range of high- and low-frequency proxy data, and in the quantity and quality of proxy data sets available at continental and northern hemispheric or global scale. Regional reconstructions are particularly important since regional climate change and extremes exhibit much larger amplitudes than hemispherical and global reconstructions. LOTRED-SA (Long-Term climate REconstruction and Dynamics of southern South America is a new collaborative long-term initiative under the umbrella of PAGES and will involve many research groups from different countries. The initiative seeks (i) to collate the large number of disperse already existing and new paleoclimate data sets (documentary data, early instrumental data, data from tree rings, glaciers and ice cores, high resolution marine and lake sediments, pollen data of peat cores etc.) for the last ca. 1000 years available for South America, and (ii) to use the Mann et al. (1998, Nature), Luterbacher et al. (2004, Science) and Moberg et al. (2005, Nature) methodologies to work towards a regional reconstruction at different temporal and spatial resolution with associated uncertainties for southern South America. This contribution reports on the state-of-the-art and the scientific highlights of the first LOTRED-SA science conference (October 2006 in Mendoza, Argentina).

Comparison Study of Regularizations in Spectral Computed Tomography Reconstruction

NASA Astrophysics Data System (ADS)

Salehjahromi, Morteza; Zhang, Yanbo; Yu, Hengyong

2018-12-01

The energy-resolving photon-counting detectors in spectral computed tomography (CT) can acquire projections of an object in different energy channels. In other words, they are able to reliably distinguish the received photon energies. These detectors lead to the emerging spectral CT, which is also called multi-energy CT, energy-selective CT, color CT, etc. Spectral CT can provide additional information in comparison with the conventional CT in which energy integrating detectors are used to acquire polychromatic projections of an object being investigated. The measurements obtained by X-ray CT detectors are noisy in reality, especially in spectral CT where the photon number is low in each energy channel. Therefore, some regularization should be applied to obtain a better image quality for this ill-posed problem in spectral CT image reconstruction. Quadratic-based regularizations are not often satisfactory as they blur the edges in the reconstructed images. As a result, different edge-preserving regularization methods have been adopted for reconstructing high quality images in the last decade. In this work, we numerically evaluate the performance of different regularizers in spectral CT, including total variation, non-local means and anisotropic diffusion. The goal is to provide some practical guidance to accurately reconstruct the attenuation distribution in each energy channel of the spectral CT data.

Pediatric chest HRCT using the iDose4 Hybrid Iterative Reconstruction Algorithm: Which iDose level to choose?

NASA Astrophysics Data System (ADS)

Smarda, M.; Alexopoulou, E.; Mazioti, A.; Kordolaimi, S.; Ploussi, A.; Priftis, K.; Efstathopoulos, E.

2015-09-01

Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions.

Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Photoacoustic image reconstruction via deep learning

NASA Astrophysics Data System (ADS)

Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes

2018-02-01

Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.

An iterative reconstruction method for high-pitch helical luggage CT

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

[Correction of light refraction and reflection in medical transmission optical tomography].

PubMed

Tereshchenko, S A; Potapov, D A

2002-01-01

The effects of light refraction and reflection on the quality of image reconstruction in medical transmission optical tomography of high-scattering media are considered. It has been first noted that light refraction not only distorts the geometric scheme of measurements, but may lead to the appearance of object areas that cannot be scanned. Some ways of decreasing the effect of refraction on the reconstruction of spatial distribution of the extinction coefficient are stated.

Reconstruction design before tumour resection: A new concept of through-and-through cheek defect reconstruction.

PubMed

Gong, Zhao-Jian; Ren, Zhen-Hu; Wang, Kai; Tan, Hong-Yu; Zhang, Sheng; Wu, Han-Jiang

2017-11-01

To explore a new method of reconstruction of through-and-through cheek defects and to evaluate this method's efficacy and patient prognosis. This retrospective study included 70 patients who underwent reconstruction of through-and-through cheek defects. The surgical approach, design of facial skin incisions, selection and design of flaps, postoperative quality of life and prognosis of patients were recorded and reported. Postoperative quality of life gradually increased over time, and the mean scores of University of Washington Quality of Life (UW-QOL) Questionnaire was more than 80 at 1-year postoperatively. The appearance, oral competence, chewing, swallowing, speech and other oral functions were well recovered in about 90% of patients at 1-year postoperatively. This new idea of reconstruction before tumour resection, brings the effect of plastic and reconstructive surgery to a new height. Copyright © 2017. Published by Elsevier Ltd.

Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting.

PubMed

Cao, Xiaozhi; Liao, Congyu; Wang, Zhixing; Chen, Ying; Ye, Huihui; He, Hongjian; Zhong, Jianhui

2017-10-01

To develop a method for accelerated and robust MR fingerprinting (MRF) with improved image reconstruction and parameter matching processes. A sliding-window (SW) strategy was applied to MRF, in which signal and dictionary matching was conducted between fingerprints consisting of mixed-contrast image series reconstructed from consecutive data frames segmented by a sliding window, and a precalculated mixed-contrast dictionary. The effectiveness and performance of this new method, dubbed SW-MRF, was evaluated in both phantom and in vivo. Error quantifications were conducted on results obtained with various settings of SW reconstruction parameters. Compared with the original MRF strategy, the results of both phantom and in vivo experiments demonstrate that the proposed SW-MRF strategy either provided similar accuracy with reduced acquisition time, or improved accuracy with equal acquisition time. Parametric maps of T 1 , T 2 , and proton density of comparable quality could be achieved with a two-fold or more reduction in acquisition time. The effect of sliding-window width on dictionary sensitivity was also estimated. The novel SW-MRF recovers high quality image frames from highly undersampled MRF data, which enables more robust dictionary matching with reduced numbers of data frames. This time efficiency may facilitate MRF applications in time-critical clinical settings. Magn Reson Med 78:1579-1588, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE)

PubMed Central

Sharif, Behzad; Derbyshire, J. Andrew; Faranesh, Anthony Z.; Bresler, Yoram

2010-01-01

MR imaging of the human heart without explicit cardiac synchronization promises to extend the applicability of cardiac MR to a larger patient population and potentially expand its diagnostic capabilities. However, conventional non-gated imaging techniques typically suffer from low image quality or inadequate spatio-temporal resolution and fidelity. Patient-Adaptive Reconstruction and Acquisition in Dynamic Imaging with Sensitivity Encoding (PARADISE) is a highly-accelerated non-gated dynamic imaging method that enables artifact-free imaging with high spatio-temporal resolutions by utilizing novel computational techniques to optimize the imaging process. In addition to using parallel imaging, the method gains acceleration from a physiologically-driven spatio-temporal support model; hence, it is doubly accelerated. The support model is patient-adaptive, i.e., its geometry depends on dynamics of the imaged slice, e.g., subject’s heart-rate and heart location within the slice. The proposed method is also doubly adaptive as it adapts both the acquisition and reconstruction schemes. Based on the theory of time-sequential sampling, the proposed framework explicitly accounts for speed limitations of gradient encoding and provides performance guarantees on achievable image quality. The presented in-vivo results demonstrate the effectiveness and feasibility of the PARADISE method for high resolution non-gated cardiac MRI during a short breath-hold. PMID:20665794

3D single point imaging with compressed sensing provides high temporal resolution R 2* mapping for in vivo preclinical applications.

PubMed

Rioux, James A; Beyea, Steven D; Bowen, Chris V

2017-02-01

Purely phase-encoded techniques such as single point imaging (SPI) are generally unsuitable for in vivo imaging due to lengthy acquisition times. Reconstruction of highly undersampled data using compressed sensing allows SPI data to be quickly obtained from animal models, enabling applications in preclinical cellular and molecular imaging. TurboSPI is a multi-echo single point technique that acquires hundreds of images with microsecond spacing, enabling high temporal resolution relaxometry of large-R 2 * systems such as iron-loaded cells. TurboSPI acquisitions can be pseudo-randomly undersampled in all three dimensions to increase artifact incoherence, and can provide prior information to improve reconstruction. We evaluated the performance of CS-TurboSPI in phantoms, a rat ex vivo, and a mouse in vivo. An algorithm for iterative reconstruction of TurboSPI relaxometry time courses does not affect image quality or R 2 * mapping in vitro at acceleration factors up to 10. Imaging ex vivo is possible at similar acceleration factors, and in vivo imaging is demonstrated at an acceleration factor of 8, such that acquisition time is under 1 h. Accelerated TurboSPI enables preclinical R 2 * mapping without loss of data quality, and may show increased specificity to iron oxide compared to other sequences.

Comparison of Knowledge-based Iterative Model Reconstruction and Hybrid Reconstruction Techniques for Liver CT Evaluation of Hypervascular Hepatocellular Carcinoma.

PubMed

Park, Hyun Jeong; Lee, Jeong Min; Park, Sung Bin; Lee, Jong Beum; Jeong, Yoong Ki; Yoon, Jeong Hee

The purpose of this work was to evaluate the image quality, lesion conspicuity, and dose reduction provided by knowledge-based iterative model reconstruction (IMR) in computed tomography (CT) of the liver compared with hybrid iterative reconstruction (IR) and filtered back projection (FBP) in patients with hepatocellular carcinoma (HCC). Fifty-six patients with 61 HCCs who underwent multiphasic reduced-dose CT (RDCT; n = 33) or standard-dose CT (SDCT; n = 28) were retrospectively evaluated. Reconstructed images with FBP, hybrid IR (iDose), IMR were evaluated for image quality using CT attenuation and image noise. Objective and subjective image quality of RDCT and SDCT sets were independently assessed by 2 observers in a blinded manner. Image quality and lesion conspicuity were better with IMR for both RDCT and SDCT than either FBP or IR (P < 0.001). Contrast-to-noise ratio of HCCs in IMR-RDCT was significantly higher on delayed phase (DP) (P < 0.001), and comparable on arterial phase, than with IR-SDCT (P = 0.501). Iterative model reconstruction RDCT was significantly superior to FBP-SDCT (P < 0.001). Compared with IR-SDCT, IMR-RDCT was comparable in image sharpness and tumor conspicuity on arterial phase, and superior in image quality, noise, and lesion conspicuity on DP. With the use of IMR, a 27% reduction of effective dose was achieved with RDCT (12.7 ± 0.6 mSv) compared with SDCT (17.4 ± 1.1 mSv) without loss of image quality (P < 0.001). Iterative model reconstruction provides better image quality and tumor conspicuity than FBP and IR with considerable noise reduction. In addition, more than comparable results were achieved with IMR-RDCT to IR-SDCT for the evaluation of HCCs.

Low-dose 4D cardiac imaging in small animals using dual source micro-CT

NASA Astrophysics Data System (ADS)

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

2018-01-01

Micro-CT is widely used in preclinical studies, generating substantial interest in extending its capabilities in functional imaging applications such as blood perfusion and cardiac function. However, imaging cardiac structure and function in mice is challenging due to their small size and rapid heart rate. To overcome these challenges, we propose and compare improvements on two strategies for cardiac gating in dual-source, preclinical micro-CT: fast prospective gating (PG) and uncorrelated retrospective gating (RG). These sampling strategies combined with a sophisticated iterative image reconstruction algorithm provide faster acquisitions and high image quality in low-dose 4D (i.e. 3D  +  Time) cardiac micro-CT. Fast PG is performed under continuous subject rotation which results in interleaved projection angles between cardiac phases. Thus, fast PG provides a well-sampled temporal average image for use as a prior in iterative reconstruction. Uncorrelated RG incorporates random delays during sampling to prevent correlations between heart rate and sampling rate. We have performed both simulations and animal studies to validate these new sampling protocols. Sampling times for 1000 projections using fast PG and RG were 2 and 3 min, respectively, and the total dose was 170 mGy each. Reconstructions were performed using a 4D iterative reconstruction technique based on the split Bregman method. To examine undersampling robustness, subsets of 500 and 250 projections were also used for reconstruction. Both sampling strategies in conjunction with our iterative reconstruction method are capable of resolving cardiac phases and provide high image quality. In general, for equal numbers of projections, fast PG shows fewer errors than RG and is more robust to undersampling. Our results indicate that only 1000-projection based reconstruction with fast PG satisfies a 5% error criterion in left ventricular volume estimation. These methods promise low-dose imaging with a wide range of preclinical applications in cardiac imaging.

Evaluating the effect of a third-party implementation of resolution recovery on the quality of SPECT bone scan imaging using visual grading regression.

PubMed

Hay, Peter D; Smith, Julie; O'Connor, Richard A

2016-02-01

The aim of this study was to evaluate the benefits to SPECT bone scan image quality when applying resolution recovery (RR) during image reconstruction using software provided by a third-party supplier. Bone SPECT data from 90 clinical studies were reconstructed retrospectively using software supplied independent of the gamma camera manufacturer. The current clinical datasets contain 120×10 s projections and are reconstructed using an iterative method with a Butterworth postfilter. Five further reconstructions were created with the following characteristics: 10 s projections with a Butterworth postfilter (to assess intraobserver variation); 10 s projections with a Gaussian postfilter with and without RR; and 5 s projections with a Gaussian postfilter with and without RR. Two expert observers were asked to rate image quality on a five-point scale relative to our current clinical reconstruction. Datasets were anonymized and presented in random order. The benefits of RR on image scores were evaluated using ordinal logistic regression (visual grading regression). The application of RR during reconstruction increased the probability of both observers of scoring image quality as better than the current clinical reconstruction even where the dataset contained half the normal counts. Type of reconstruction and observer were both statistically significant variables in the ordinal logistic regression model. Visual grading regression was found to be a useful method for validating the local introduction of technological developments in nuclear medicine imaging. RR, as implemented by the independent software supplier, improved bone SPECT image quality when applied during image reconstruction. In the majority of clinical cases, acquisition times for bone SPECT intended for the purposes of localization can safely be halved (from 10 s projections to 5 s) when RR is applied.

SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noid, G; Tai, A; Li, X

2015-06-15

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition ASmore » Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.« less

Dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modelling language (VRML).

PubMed

Yu, Zheng-yang; Zheng, Shu-sen; Chen, Lei-ting; He, Xiao-qian; Wang, Jian-jun

2005-07-01

This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic concision, the VRML browser can offer better windows for man-computer interaction in real-time environment than ever before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and have a promising prospect in the fields of medical imaging.

Dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modelling language (VRML)*

PubMed Central

Yu, Zheng-yang; Zheng, Shu-sen; Chen, Lei-ting; He, Xiao-qian; Wang, Jian-jun

2005-01-01

This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic concision, the VRML browser can offer better windows for man-computer interaction in real-time environment than ever before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and have a promising prospect in the fields of medical imaging. PMID:15973760

Reconstruction and visualization of carbohydrate, N-glycosylation pathways in Pichia pastoris CBS7435 using computational and system biology approaches.

PubMed

Srivastava, Akriti; Somvanshi, Pallavi; Mishra, Bhartendu Nath

2013-06-01

Pichia pastoris is an efficient expression system for production of recombinant proteins. To understand its physiology for building novel applications it is important to understand and reconstruct its metabolic network. The metabolic reconstruction approach connects genotype with phenotype. Here, we have attempted to reconstruct carbohydrate metabolism pathways responsible for high biomass density and N-glycosylation pathways involved in the post translational modification of proteins of P. pastoris CBS7435. Both these metabolic pathways play a crucial role in heterologous protein production. We report novel, missing and unannotated enzymes involved in the target metabolic pathways. A strong possibility of cellulose and xylose metabolic processes in P. pastoris CBS7435 suggests its use in the area of biofuels. The reconstructed metabolic networks can be used for increased yields and improved product quality, for designing appropriate growth medium, for production of recombinant therapeutics and for making biofuels.

Technical Note: FreeCT_ICD: An Open Source Implementation of a Model-Based Iterative Reconstruction Method using Coordinate Descent Optimization for CT Imaging Investigations.

PubMed

Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael

2018-06-01

To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

An iterative reduced field-of-view reconstruction for periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI.

PubMed

Lin, Jyh-Miin; Patterson, Andrew J; Chang, Hing-Chiu; Gillard, Jonathan H; Graves, Martin J

2015-10-01

To propose a new reduced field-of-view (rFOV) strategy for iterative reconstructions in a clinical environment. Iterative reconstructions can incorporate regularization terms to improve the image quality of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) MRI. However, the large amount of calculations required for full FOV iterative reconstructions has posed a huge computational challenge for clinical usage. By subdividing the entire problem into smaller rFOVs, the iterative reconstruction can be accelerated on a desktop with a single graphic processing unit (GPU). This rFOV strategy divides the iterative reconstruction into blocks, based on the block-diagonal dominant structure. A near real-time reconstruction system was developed for the clinical MR unit, and parallel computing was implemented using the object-oriented model. In addition, the Toeplitz method was implemented on the GPU to reduce the time required for full interpolation. Using the data acquired from the PROPELLER MRI, the reconstructed images were then saved in the digital imaging and communications in medicine format. The proposed rFOV reconstruction reduced the gridding time by 97%, as the total iteration time was 3 s even with multiple processes running. A phantom study showed that the structure similarity index for rFOV reconstruction was statistically superior to conventional density compensation (p < 0.001). In vivo study validated the increased signal-to-noise ratio, which is over four times higher than with density compensation. Image sharpness index was improved using the regularized reconstruction implemented. The rFOV strategy permits near real-time iterative reconstruction to improve the image quality of PROPELLER images. Substantial improvements in image quality metrics were validated in the experiments. The concept of rFOV reconstruction may potentially be applied to other kinds of iterative reconstructions for shortened reconstruction duration.

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

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.

Reconstruction of perfect ZnO nanowires facets with high optical quality

NASA Astrophysics Data System (ADS)

Zehani, E.; Hassani, S.; Lusson, A.; Vigneron, J.; Etcheberry, A.; Galtier, P.; Sallet, V.

2017-07-01

ZnO nanowires were grown on sapphire substrates using metalorganic chemical vapor deposition. The samples were subsequently annealed under zinc pressure in a vacuum-sealed ampoule, at temperature ranging from 500 to 800 °C. The originality and the main motivation to provide a zinc-rich atmosphere were to prevent the out-diffusion of zinc from the nanowires. In doing so, the perfect structural properties and the morphology of the nanowires are kept. Interestingly, photoluminescence experiments performed on nanowires annealed in a narrow window of temperature [580-620 °C] show a spectacular improvement of the optical quality, as transitions commonly observable in high quality bulk samples are found. In addition, the intensity of the so-called "surface excitons" (SX) is strongly decreased. To accurately investigate the chemical modifications of the surface, XPS experiments were carried out and show that zinc hydroxide species and/or Zn(OH)2 sublayer were partially removed from the surface. These results suggest that the annealing process in zinc vapor helps to properly reconstruct the surface of ZnO nanowires, and improves the optical quality of their core. Such a thermal treatment at moderate temperature should be beneficial to nanodevices involving surface reaction, e.g. gas sensors.

Bayesian image reconstruction for improving detection performance of muon tomography.

PubMed

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

2009-05-01

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

Physics of cardiac imaging with multiple-row detector CT.

PubMed

Mahesh, Mahadevappa; Cody, Dianna D

2007-01-01

Cardiac imaging with multiple-row detector computed tomography (CT) has become possible due to rapid advances in CT technologies. Images with high temporal and spatial resolution can be obtained with multiple-row detector CT scanners; however, the radiation dose associated with cardiac imaging is high. Understanding the physics of cardiac imaging with multiple-row detector CT scanners allows optimization of cardiac CT protocols in terms of image quality and radiation dose. Knowledge of the trade-offs between various scan parameters that affect image quality--such as temporal resolution, spatial resolution, and pitch--is the key to optimized cardiac CT protocols, which can minimize the radiation risks associated with these studies. Factors affecting temporal resolution include gantry rotation time, acquisition mode, and reconstruction method; factors affecting spatial resolution include detector size and reconstruction interval. Cardiac CT has the potential to become a reliable tool for noninvasive diagnosis and prevention of cardiac and coronary artery disease. (c) RSNA, 2007.

Spectral CT Reconstruction with Image Sparsity and Spectral Mean

PubMed Central

Zhang, Yi; Xi, Yan; Yang, Qingsong; Cong, Wenxiang; Zhou, Jiliu

2017-01-01

Photon-counting detectors can acquire x-ray intensity data in different energy bins. The signal to noise ratio of resultant raw data in each energy bin is generally low due to the narrow bin width and quantum noise. To address this problem, here we propose an image reconstruction approach for spectral CT to simultaneously reconstructs x-ray attenuation coefficients in all the energy bins. Because the measured spectral data are highly correlated among the x-ray energy bins, the intra-image sparsity and inter-image similarity are important prior acknowledge for image reconstruction. Inspired by this observation, the total variation (TV) and spectral mean (SM) measures are combined to improve the quality of reconstructed images. For this purpose, a linear mapping function is used to minimalize image differences between energy bins. The split Bregman technique is applied to perform image reconstruction. Our numerical and experimental results show that the proposed algorithms outperform competing iterative algorithms in this context. PMID:29034267

The Impact of Facial Aesthetic and Reconstructive Surgeries on Patients' Quality of Life.

PubMed

Yıldız, Tülin; Selimen, Deniz

2015-12-01

The aim of the present prospective and descriptive study was to assess the impact of facial aesthetic and reconstructive surgeries on quality of life. Ninety-one patients, of whom 43 had aesthetic surgery and 48 had reconstructive surgery, were analysed. The data were collected using the patient information form, body cathexis scale, and short form (SF)-36 quality of life scale. There were significant differences between before and after the surgery in both groups in terms of body cathexis scale and quality of life (p < 0.05 for both). It was observed that problems regarding the body image perception were encountered more, and the quality of life was poorer in both aesthetic and reconstructive surgery patients before the surgery. However, the problems were decreased, and the quality of life was enhanced after the surgery. Among the parameters of SF-36 quality of life scale, particularly the mean scores of social functioning, physical role functioning, emotional role functioning, mental health, and vitality/fatigue were found low before the surgery, whereas the mean scores were significantly improved after the surgery. The results revealed that facial aesthetic and reconstructive surgical interventions favourably affected the body image perception and self-esteem and that positive reflections in emotional, social, and mental aspects were effective in enhancing self-confidence and quality of life of the individual.

Evaluation of Aesthetic and Quality-of-Life Results after Immediate Breast Reconstruction with Definitive Form-Stable Anatomical Implants.

PubMed

Kuroda, Flavia; Urban, Cicero; Zucca-Matthes, Gustavo; de Oliveira, Vilmar Marques; Arana, Gabriel Hubner; Iera, Marco; Rietjens, Mario; Santos, Gabriela; Spagnol, Caroline; de Lima, Rubens Silveira

2016-02-01

Although there are many reports on different techniques in breast reconstruction, there are few data regarding immediate breast reconstruction with definitive form-stable anatomical implants in terms of aesthetics and quality-of-life outcomes. Ninety-four patients underwent mastectomy with immediate breast reconstruction using anatomical implants and contralateral symmetrization. Aesthetic results were evaluated by three different methods: the patient's self-report, the assessment of four independent specialists (two breast surgeons and two plastic surgeons from different institutions), and the BCCT.core software. Quality of life was evaluated by means of the BREAST-Q instrument. Average age ± SD was 52.1 ± 11.6 years. Most of patients had medium size breasts and T1 tumors. Patients had evaluated their aesthetic results better than did software and specialists. There was no significant difference in the comparison between software and specialist's evaluation. Multifactorial analysis showed that age older than 70 years and radiotherapy were significant risk factors for poor aesthetic outcomes after immediate breast reconstruction with implants. Considering quality of life, most of the patients were satisfied with their outcome and psychosocial and sexual well-being. Immediate breast reconstruction with implants and contralateral symmetrization had a positive impact on the quality of life and showed satisfactory outcomes when evaluated by subjective and objective methods.

Residual Highway Convolutional Neural Networks for in-loop Filtering in HEVC.

PubMed

Zhang, Yongbing; Shen, Tao; Ji, Xiangyang; Zhang, Yun; Xiong, Ruiqin; Dai, Qionghai

2018-08-01

High efficiency video coding (HEVC) standard achieves half bit-rate reduction while keeping the same quality compared with AVC. However, it still cannot satisfy the demand of higher quality in real applications, especially at low bit rates. To further improve the quality of reconstructed frame while reducing the bitrates, a residual highway convolutional neural network (RHCNN) is proposed in this paper for in-loop filtering in HEVC. The RHCNN is composed of several residual highway units and convolutional layers. In the highway units, there are some paths that could allow unimpeded information across several layers. Moreover, there also exists one identity skip connection (shortcut) from the beginning to the end, which is followed by one small convolutional layer. Without conflicting with deblocking filter (DF) and sample adaptive offset (SAO) filter in HEVC, RHCNN is employed as a high-dimension filter following DF and SAO to enhance the quality of reconstructed frames. To facilitate the real application, we apply the proposed method to I frame, P frame, and B frame, respectively. For obtaining better performance, the entire quantization parameter (QP) range is divided into several QP bands, where a dedicated RHCNN is trained for each QP band. Furthermore, we adopt a progressive training scheme for the RHCNN where the QP band with lower value is used for early training and their weights are used as initial weights for QP band of higher values in a progressive manner. Experimental results demonstrate that the proposed method is able to not only raise the PSNR of reconstructed frame but also prominently reduce the bit-rate compared with HEVC reference software.

TU-E-217BCD-09: The Feasibility of the Dual-Dictionary Method for Breast Computed Tomography Based on Photon-Counting Detectors.

PubMed

Zhao, B; Ding, H; Lu, Y; Wang, G; Zhao, J; Molloi, S

2012-06-01

To investigate the feasibility of an Iterative Reconstruction (IR) method utilizing the algebraic reconstruction technique coupled with dual-dictionary learning for the application of dedicated breast computed tomography (CT) based on a photon-counting detector. Postmortem breast samples were scanned in an experimental fan beam CT system based on a Cadmium-Zinc-Telluride (CZT) photon-counting detector. Images were reconstructed from various numbers of projections with both IR and Filtered-Back-Projection (FBP) methods. Contrast-to-Noise Ratio (CNR) between the glandular and adipose tissue of postmortem breast samples were calculated to evaluate the quality of images reconstructed from IR and FBP. In addition to CNR, the spatial resolution was also used as a metric to evaluate the quality of images reconstructed from the two methods. This is further studied with a high-resolution phantom consisting of a 14 cm diameter, 10 cm length polymethylmethacrylate (PMMA) cylinder. A 5 cm diameter coaxial volume of Interest insert that contains fine Aluminum wires of various diameters was used to determine spatial resolution. The spatial resolution and CNR were better when identical sinograms were reconstructed in IR as compared to FBP. In comparison with FBP reconstruction, a similar CNR was achieved using IR method with up to a factor of 5 fewer projections. The results of this study suggest that IR method can significantly reduce the required number of projections for a CT reconstruction compared to FBP method to achieve an equivalent CNR. Therefore, the scanning time of a CZT-based CT system using the IR method can potentially be reduced. © 2012 American Association of Physicists in Medicine.

Evaluation of noise and blur effects with SIRT-FISTA-TV reconstruction algorithm: Application to fast environmental transmission electron tomography.

PubMed

Banjak, Hussein; Grenier, Thomas; Epicier, Thierry; Koneti, Siddardha; Roiban, Lucian; Gay, Anne-Sophie; Magnin, Isabelle; Peyrin, Françoise; Maxim, Voichita

2018-06-01

Fast tomography in Environmental Transmission Electron Microscopy (ETEM) is of a great interest for in situ experiments where it allows to observe 3D real-time evolution of nanomaterials under operating conditions. In this context, we are working on speeding up the acquisition step to a few seconds mainly with applications on nanocatalysts. In order to accomplish such rapid acquisitions of the required tilt series of projections, a modern 4K high-speed camera is used, that can capture up to 100 images per second in a 2K binning mode. However, due to the fast rotation of the sample during the tilt procedure, noise and blur effects may occur in many projections which in turn would lead to poor quality reconstructions. Blurred projections make classical reconstruction algorithms inappropriate and require the use of prior information. In this work, a regularized algebraic reconstruction algorithm named SIRT-FISTA-TV is proposed. The performance of this algorithm using blurred data is studied by means of a numerical blur introduced into simulated images series to mimic possible mechanical instabilities/drifts during fast acquisitions. We also present reconstruction results from noisy data to show the robustness of the algorithm to noise. Finally, we show reconstructions with experimental datasets and we demonstrate the interest of fast tomography with an ultra-fast acquisition performed under environmental conditions, i.e. gas and temperature, in the ETEM. Compared to classically used SIRT and SART approaches, our proposed SIRT-FISTA-TV reconstruction algorithm provides higher quality tomograms allowing easier segmentation of the reconstructed volume for a better final processing and analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Synthetic aperture ultrasound imaging with a ring transducer array: preliminary ex vivo results.

PubMed

Qu, Xiaolei; Azuma, Takashi; Yogi, Takeshi; Azuma, Shiho; Takeuchi, Hideki; Tamano, Satoshi; Takagi, Shu

2016-10-01

The conventional medical ultrasound imaging has a low lateral spatial resolution, and the image quality depends on the depth of the imaging location. To overcome these problems, this study presents a synthetic aperture (SA) ultrasound imaging method using a ring transducer array. An experimental ring transducer array imaging system was constructed. The array was composed of 2048 transducer elements, and had a diameter of 200 mm and an inter-element pitch of 0.325 mm. The imaging object was placed in the center of the ring transducer array, which was immersed in water. SA ultrasound imaging was then employed to scan the object and reconstruct the reflection image. Both wire phantom and ex vivo experiments were conducted. The proposed method was found to be capable of producing isotropic high-resolution images of the wire phantom. In addition, preliminary ex vivo experiments using porcine organs demonstrated the ability of the method to reconstruct high-quality images without any depth dependence. The proposed ring transducer array and SA ultrasound imaging method were shown to be capable of producing isotropic high-resolution images whose quality was independent of depth.

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

PubMed Central

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

2016-01-01

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

Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

2015-08-01

Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ~40-80 HU, size  >  1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of intracranial hemorrhage.

Effects of sparse sampling in combination with iterative reconstruction on quantitative bone microstructure assessment

NASA Astrophysics Data System (ADS)

Mei, Kai; Kopp, Felix K.; Fehringer, Andreas; Pfeiffer, Franz; Rummeny, Ernst J.; Kirschke, Jan S.; Noël, Peter B.; Baum, Thomas

2017-03-01

The trabecular bone microstructure is a key to the early diagnosis and advanced therapy monitoring of osteoporosis. Regularly measuring bone microstructure with conventional multi-detector computer tomography (MDCT) would expose patients with a relatively high radiation dose. One possible solution to reduce exposure to patients is sampling fewer projection angles. This approach can be supported by advanced reconstruction algorithms, with their ability to achieve better image quality under reduced projection angles or high levels of noise. In this work, we investigated the performance of iterative reconstruction from sparse sampled projection data on trabecular bone microstructure in in-vivo MDCT scans of human spines. The computed MDCT images were evaluated by calculating bone microstructure parameters. We demonstrated that bone microstructure parameters were still computationally distinguishable when half or less of the radiation dose was employed.

Elucidating Complex Surface Reconstructions with Atomic-Resolution Scanning Tunneling Microscopy: Au(100)-Aqueous Electrochemical Interface

DTIC Science & Technology

1992-05-01

that unusually high-quality STM data of this type 5-7can be obtained at ordered gold -aqueous interfaces. Reconstruction is seen 2 to be triggered on...all three low-index gold surfaces by altering the potential to values corresponding to small (10-15 pC cm-2 ) negative surface electronic 5-7 charges...connections. The former was platinum and the latter was a freshly electrooxidized gold wire. All electrode potentials quoted here, however, are

ELUCID—Exploring the Local Universe with the reConstructed Initial Density Field. II. Reconstruction Diagnostics, Applied to Numerical Halo Catalogs

NASA Astrophysics Data System (ADS)

Tweed, Dylan; Yang, Xiaohu; Wang, Huiyuan; Cui, Weiguang; Zhang, Youcai; Li, Shijie; Jing, Y. P.; Mo, H. J.

2017-05-01

The ELUCID project aims to build a series of realistic cosmological simulations that reproduce the spatial and mass distributions of the galaxies as observed in the Sloan Digital Sky Survey. This requires powerful reconstruction techniques to create constrained initial conditions (ICs). We test the reconstruction method by applying it to several N-body simulations. We use two medium-resolution simulations, which each produced three additional constrained N-body simulations. We compare the resulting friend-of-friend catalogs by using the particle indexes as tracers, and quantify the quality of the reconstruction by varying the main smoothing parameter. The cross-identification method we use proves to be efficient, and the results suggest that the most massive reconstructed halos are effectively traced from the same Lagrangian regions in the ICs. A preliminary time-dependence analysis indicates that high-mass-end halos converge only at a redshift close to the reconstruction redshift. This suggests that, for earlier snapshots, only collections of progenitors may be effectively cross-identified.

SU-F-BRCD-09: Total Variation (TV) Based Fast Convergent Iterative CBCT Reconstruction with GPU Acceleration.

PubMed

Xu, Q; Yang, D; Tan, J; Anastasio, M

2012-06-01

To improve image quality and reduce imaging dose in CBCT for radiation therapy applications and to realize near real-time image reconstruction based on use of a fast convergence iterative algorithm and acceleration by multi-GPUs. An iterative image reconstruction that sought to minimize a weighted least squares cost function that employed total variation (TV) regularization was employed to mitigate projection data incompleteness and noise. To achieve rapid 3D image reconstruction (< 1 min), a highly optimized multiple-GPU implementation of the algorithm was developed. The convergence rate and reconstruction accuracy were evaluated using a modified 3D Shepp-Logan digital phantom and a Catphan-600 physical phantom. The reconstructed images were compared with the clinical FDK reconstruction results. Digital phantom studies showed that only 15 iterations and 60 iterations are needed to achieve algorithm convergence for 360-view and 60-view cases, respectively. The RMSE was reduced to 10-4 and 10-2, respectively, by using 15 iterations for each case. Our algorithm required 5.4s to complete one iteration for the 60-view case using one Tesla C2075 GPU. The few-view study indicated that our iterative algorithm has great potential to reduce the imaging dose and preserve good image quality. For the physical Catphan studies, the images obtained from the iterative algorithm possessed better spatial resolution and higher SNRs than those obtained from by use of a clinical FDK reconstruction algorithm. We have developed a fast convergence iterative algorithm for CBCT image reconstruction. The developed algorithm yielded images with better spatial resolution and higher SNR than those produced by a commercial FDK tool. In addition, from the few-view study, the iterative algorithm has shown great potential for significantly reducing imaging dose. We expect that the developed reconstruction approach will facilitate applications including IGART and patient daily CBCT-based treatment localization. © 2012 American Association of Physicists in Medicine.

Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.

PubMed

Fromm, S A; Sachse, C

2016-01-01

Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. © 2016 Elsevier Inc. All rights reserved.

Immediate Breast Reconstruction with Abdominal Free Flap and Adjuvant Radiotherapy: Evaluation of Quality of Life and Outcomes.

PubMed

Pont, Luis Parra; Marcelli, Stefano; Robustillo, Manuel; Song, Dajiang; Grandes, Daniel; Martin, Marcos; Iglesias, Israel; Aso, Jorge; Laloumet, Iñaki; Díaz, Antonio J

2017-10-01

The effects of postoperative radiotherapy on free flap-based breast reconstruction are still controversial. Poor outcomes, breast distortion, and fat necrosis have been traditionally documented. The aim of this study was to evaluate whether adjuvant radiotherapy affects the quality of life, satisfaction, and cosmetic result in patients undergoing immediate breast reconstruction with autologous free flap. Between January of 2013 and December of 2016, 230 patients underwent mastectomy with immediate free flap reconstruction at the authors' institution. Patients were divided into two groups depending on whether they received postmastectomy radiotherapy. Quality of life measured with the BREAST-Q questionnaire, self-reported aesthetic outcomes, and general satisfaction were assessed and compared. Fat necrosis of the flap and its severity were also analyzed as the main surgical outcomes. Mean follow-up time after reconstruction was 23 months (range, 6 to 48 months). No significant difference in quality of life or satisfaction scores were found between patients that underwent postmastectomy radiotherapy and patients who did not receive adjuvant radiotherapy. There were no significant differences in rates of fat necrosis between the groups (11.1 percent versus 13.76 percent; p = 0.75). Postmastectomy radiotherapy in patients undergoing immediate breast reconstruction with free flaps does not seem to affect quality of life, satisfaction with the outcome, or the cosmetic result as perceived by the patients. The potential need for postoperative radiotherapy should not hinder women from the benefits of autologous immediate breast reconstruction. Therapeutic, III.

Segmented Separable Footprint Projector for Digital Breast Tomosynthesis and Its application for Subpixel Reconstruction

PubMed Central

Zheng, Jiabei; Fessler, Jeffrey A; Chan, Heang-Ping

2017-01-01

Purpose Digital forward and back projectors play a significant role in iterative image reconstruction. The accuracy of the projector affects the quality of the reconstructed images. Digital breast tomosynthesis (DBT) often uses the ray-tracing (RT) projector that ignores finite detector element size. This paper proposes a modified version of the separable footprint (SF) projector, called the segmented separable footprint (SG) projector, that calculates efficiently the Radon transform mean value over each detector element. The SG projector is specifically designed for DBT reconstruction because of the large height-to-width ratio of the voxels generally used in DBT. This study evaluates the effectiveness of the SG projector in reducing projection error and improving DBT reconstruction quality. Methods We quantitatively compared the projection error of the RT and the SG projector at different locations and their performance in regular and subpixel DBT reconstruction. Subpixel reconstructions used finer voxels in the imaged volume than the detector pixel size. Subpixel reconstruction with RT projector uses interpolated projection views as input to provide adequate coverage of the finer voxel grid with the traced rays. Subpixel reconstruction with the SG projector, however, uses the measured projection views without interpolation. We simulated DBT projections of a test phantom using CatSim (GE Global Research, Niskayuna, NY) under idealized imaging conditions without noise and blur, to analyze the effects of the projectors and subpixel reconstruction without other image degrading factors. The phantom contained an array of horizontal and vertical line pair patterns (1 to 9.5 line pairs/mm) and pairs of closely spaced spheres (diameters 0.053 to 0.5 mm) embedded at the mid-plane of a 5-cm-thick breast-tissue-equivalent uniform volume. The images were reconstructed with regular simultaneous algebraic reconstruction technique (SART) and subpixel SART using different projectors. The resolution and contrast of the test objects in the reconstructed images and the computation times were compared under different reconstruction conditions. Results The SG projector reduced the projector error by 1 to 2 orders of magnitude at most locations. In the worst case, the SG projector still reduced the projection error by about 50%. In the DBT reconstructed slices parallel to the detector plane, the SG projector not only increased the contrast of the line pairs and spheres, but also produced more smooth and continuous reconstructed images whereas the discrete and sparse nature of the RT projector caused artifacts appearing as patterned noise. For subpixel reconstruction, the SG projector significantly increased object contrast and computation speed, especially for high subpixel ratios, compared with the RT projector implemented with accelerated Siddon’s algorithm. The difference in the depth resolution among the projectors is negligible under the conditions studied. Our results also demonstrated that subpixel reconstruction can improve the spatial resolution of the reconstructed images, and can exceed the Nyquist limit of the detector under some conditions. Conclusions The SG projector was more accurate and faster than the RT projector. The SG projector also substantially reduced computation time and improved the image quality for the tomosynthesized images with and without subpixel reconstruction. PMID:28058719

Patients' satisfaction after ear reconstruction with autologous rib cartilage.

PubMed

Kristiansen, Martina; Öberg, Martin; Wikström, Sven Olof

2013-04-01

Patients' satisfaction is an important outcome measure in reconstructive surgery and quality assurance is today central in the clinical practice. The aim of this study was to evaluate the patients' satisfaction with the process and final result after reconstruction for congenital microtia. A questionnaire was designed and sent to 78 patients who had undergone unilateral ear reconstruction with autologous rib cartilage during the period 2000-2010. For a multidimensional view the patients answered 42 questions about aesthetic, functional, psychosocial, and clinic-related outcomes. The response rate was 76% (59/78 patients). The patients were generally satisfied with the aesthetic result of the ear and had function gain in being able to wear glasses; however, some patients did report new different functional problems after the operation. Still, almost all patients felt that the ear was a part of them and would have chosen the same operative procedure if they could do it again. The patients were overall highly satisfied with the care process. This surgery-specific questionnaire is an important tool for quality assurance in this clinical practice. These findings can help to improve the preoperative information to meet the patients' notions, expectations, and fears.

Dual-camera design for coded aperture snapshot spectral imaging.

PubMed

Wang, Lizhi; Xiong, Zhiwei; Gao, Dahua; Shi, Guangming; Wu, Feng

2015-02-01

Coded aperture snapshot spectral imaging (CASSI) provides an efficient mechanism for recovering 3D spectral data from a single 2D measurement. However, since the reconstruction problem is severely underdetermined, the quality of recovered spectral data is usually limited. In this paper we propose a novel dual-camera design to improve the performance of CASSI while maintaining its snapshot advantage. Specifically, a beam splitter is placed in front of the objective lens of CASSI, which allows the same scene to be simultaneously captured by a grayscale camera. This uncoded grayscale measurement, in conjunction with the coded CASSI measurement, greatly eases the reconstruction problem and yields high-quality 3D spectral data. Both simulation and experimental results demonstrate the effectiveness of the proposed method.

Can use of adaptive statistical iterative reconstruction reduce radiation dose in unenhanced head CT? An analysis of qualitative and quantitative image quality

PubMed Central

Heggen, Kristin Livelten; Pedersen, Hans Kristian; Andersen, Hilde Kjernlie; Martinsen, Anne Catrine T

2016-01-01

Background Iterative reconstruction can reduce image noise and thereby facilitate dose reduction. Purpose To evaluate qualitative and quantitative image quality for full dose and dose reduced head computed tomography (CT) protocols reconstructed using filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Material and Methods Fourteen patients undergoing follow-up head CT were included. All patients underwent full dose (FD) exam and subsequent 15% dose reduced (DR) exam, reconstructed using FBP and 30% ASIR. Qualitative image quality was assessed using visual grading characteristics. Quantitative image quality was assessed using ROI measurements in cerebrospinal fluid (CSF), white matter, peripheral and central gray matter. Additionally, quantitative image quality was measured in Catphan and vendor’s water phantom. Results There was no significant difference in qualitative image quality between FD FBP and DR ASIR. Comparing same scan FBP versus ASIR, a noise reduction of 28.6% in CSF and between −3.7 and 3.5% in brain parenchyma was observed. Comparing FD FBP versus DR ASIR, a noise reduction of 25.7% in CSF, and −7.5 and 6.3% in brain parenchyma was observed. Image contrast increased in ASIR reconstructions. Contrast-to-noise ratio was improved in DR ASIR compared to FD FBP. In phantoms, noise reduction was in the range of 3 to 28% with image content. Conclusion There was no significant difference in qualitative image quality between full dose FBP and dose reduced ASIR. CNR improved in DR ASIR compared to FD FBP mostly due to increased contrast, not reduced noise. Therefore, we recommend using caution if reducing dose and applying ASIR to maintain image quality. PMID:27583169

Can use of adaptive statistical iterative reconstruction reduce radiation dose in unenhanced head CT? An analysis of qualitative and quantitative image quality.

PubMed

Østerås, Bjørn Helge; Heggen, Kristin Livelten; Pedersen, Hans Kristian; Andersen, Hilde Kjernlie; Martinsen, Anne Catrine T

2016-08-01

Iterative reconstruction can reduce image noise and thereby facilitate dose reduction. To evaluate qualitative and quantitative image quality for full dose and dose reduced head computed tomography (CT) protocols reconstructed using filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Fourteen patients undergoing follow-up head CT were included. All patients underwent full dose (FD) exam and subsequent 15% dose reduced (DR) exam, reconstructed using FBP and 30% ASIR. Qualitative image quality was assessed using visual grading characteristics. Quantitative image quality was assessed using ROI measurements in cerebrospinal fluid (CSF), white matter, peripheral and central gray matter. Additionally, quantitative image quality was measured in Catphan and vendor's water phantom. There was no significant difference in qualitative image quality between FD FBP and DR ASIR. Comparing same scan FBP versus ASIR, a noise reduction of 28.6% in CSF and between -3.7 and 3.5% in brain parenchyma was observed. Comparing FD FBP versus DR ASIR, a noise reduction of 25.7% in CSF, and -7.5 and 6.3% in brain parenchyma was observed. Image contrast increased in ASIR reconstructions. Contrast-to-noise ratio was improved in DR ASIR compared to FD FBP. In phantoms, noise reduction was in the range of 3 to 28% with image content. There was no significant difference in qualitative image quality between full dose FBP and dose reduced ASIR. CNR improved in DR ASIR compared to FD FBP mostly due to increased contrast, not reduced noise. Therefore, we recommend using caution if reducing dose and applying ASIR to maintain image quality.

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

PubMed Central

Wang, Kun; Su, Richard; Oraevsky, Alexander A; Anastasio, Mark A

2012-01-01

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications. PMID:22864062

Estimation of relative effectiveness of phylogenetic programs by machine learning.

PubMed

Krivozubov, Mikhail; Goebels, Florian; Spirin, Sergei

2014-04-01

Reconstruction of phylogeny of a protein family from a sequence alignment can produce results of different quality. Our goal is to predict the quality of phylogeny reconstruction basing on features that can be extracted from the input alignment. We used Fitch-Margoliash (FM) method of phylogeny reconstruction and random forest as a predictor. For training and testing the predictor, alignments of orthologous series (OS) were used, for which the result of phylogeny reconstruction can be evaluated by comparison with trees of corresponding organisms. Our results show that the quality of phylogeny reconstruction can be predicted with more than 80% precision. Also, we tried to predict which phylogeny reconstruction method, FM or UPGMA, is better for a particular alignment. With the used set of features, among alignments for which the obtained predictor predicts a better performance of UPGMA, 56% really give a better result with UPGMA. Taking into account that in our testing set only for 34% alignments UPGMA performs better, this result shows a principal possibility to predict the better phylogeny reconstruction method basing on features of a sequence alignment.

Development of Acoustic Model-Based Iterative Reconstruction Technique for Thick-Concrete Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almansouri, Hani; Clayton, Dwight A; Kisner, Roger A

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 structuresmore » 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.« less

An improved reconstruction of May-June precipitation using tree-ring data from western Turkey and its links to volcanic eruptions.

PubMed

Köse, Nesibe; Akkemik, Unal; Güner, H Tuncay; Dalfes, H Nüzhet; Grissino-Mayer, Henri D; Ozeren, M Sinan; Kındap, Tayfun

2013-09-01

We developed a high quality reconstruction of May-June precipitation for the interior region of southwestern Turkey using regional tree-ring data calibrated with meteorological data from Burdur. In this study, three new climate sensitive black pine chronologies were built. In addition to new chronologies, four previously published black pine chronologies were used for the reconstruction. Two separate reconstructions were developed. The first reconstruction used all site chronologies over the common interval AD 1813-2004. The second reconstruction used four of the chronologies with a common interval AD 1692-2004. R² values of the reconstructions were 0.64 and 0.51 with RE values of 0.63 and 0.51, respectively. During the period AD 1692-1938, 41 dry and 48 wet events were found. Very dry years occurred in AD 1725, 1814, 1851, 1887, 1916, and 1923, while very wet years occurred in AD 1736, 1780, 1788, 1803, and 1892. The longest dry period was 16 years long between 1860 and 1875. We then explored relationships between the reconstructed rainfall patterns and major volcanic eruptions, and discovered that wetter than normal years occurred during or immediately after the years with the largest volcanic eruptions.

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

PubMed Central

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

2014-01-01

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR values were found to increase with decreasing RMSE values of projection angular gaps with strong correlations (r ≈ −0.7) regardless of the reconstruction algorithm used. Conclusions: Based on the authors’ results, displacement-based binning methods, better reconstruction algorithms, and the acquisition of even projection angular views are the most important factors to consider for improving thoracic 4D-CBCT image quality. In view of the practical issues with displacement-based binning and the fact that projection angular spacing is not currently directly controllable, development of better reconstruction algorithms represents the most effective strategy for improving image quality in thoracic 4D-CBCT for IGRT applications at the current stage. PMID:24694143

Application of Curved MPR Algorithm to High Resolution 3 Dimensional T2 Weighted CISS Images for Virtual Uncoiling of Membranous Cochlea as an Aid for Cochlear Morphometry.

PubMed

Kumar, Joish Upendra; Kavitha, Y

2017-02-01

With the use of various surgical techniques, types of implants, the preoperative assessment of cochlear dimensions is becoming increasingly relevant prior to cochlear implantation. High resolution CISS protocol MRI gives a better assessment of membranous cochlea, cochlear nerve, and membranous labyrinth. Curved Multiplanar Reconstruction (MPR) algorithm provides better images that can be used for measuring dimensions of membranous cochlea. To ascertain the value of curved multiplanar reconstruction algorithm in high resolution 3-Dimensional T2 Weighted Gradient Echo Constructive Interference Steady State (3D T2W GRE CISS) imaging for accurate morphometry of membranous cochlea. Fourteen children underwent MRI for inner ear assessment. High resolution 3D T2W GRE CISS sequence was used to obtain images of cochlea. Curved MPR reconstruction algorithm was used to virtually uncoil the membranous cochlea on the volume images and cochlear measurements were done. Virtually uncoiled images of membranous cochlea of appropriate resolution were obtained from the volume data obtained from the high resolution 3D T2W GRE CISS images, after using curved MPR reconstruction algorithm mean membranous cochlear length in the children was 27.52 mm. Maximum apical turn diameter of membranous cochlea was 1.13 mm, mid turn diameter was 1.38 mm, basal turn diameter was 1.81 mm. Curved MPR reconstruction algorithm applied to CISS protocol images facilitates in getting appropriate quality images of membranous cochlea for accurate measurements.

Metal artifact reduction software used with abdominopelvic dual-energy CT of patients with metal hip prostheses: assessment of image quality and clinical feasibility.

PubMed

Han, Seung Chol; Chung, Yong Eun; Lee, Young Han; Park, Kwan Kyu; Kim, Myeong Jin; Kim, Ki Whang

2014-10-01

The objective of our study was to determine the feasibility of using Metal Artifact Reduction (MAR) software for abdominopelvic dual-energy CT in patients with metal hip prostheses. This retrospective study included 33 patients (male-female ratio, 19:14; mean age, 63.7 years) who received total hip replacements and 20 patients who did not have metal prostheses as the control group. All of the patients underwent dual-energy CT. The quality of the images reconstructed using the MAR algorithm and of those reconstructed using the standard reconstruction was evaluated in terms of the visibility of the bladder wall, pelvic sidewall, rectal shelf, and bone-prosthesis interface and the overall diagnostic image quality with a 4-point scale. The mean and SD attenuation values in Hounsfield units were measured in the bladder, pelvic sidewall, and rectal shelf. For validation of the MAR interpolation algorithm, pelvis phantoms with small bladder "lesions" and metal hip prostheses were made, and images of the phantoms both with and without MAR reconstruction were evaluated. Image quality was significantly better with MAR reconstruction than without at all sites except the rectal shelf, where the image quality either had not changed or had worsened after MAR reconstruction. The mean attenuation value was changed after MAR reconstruction to its original expected value at the pelvic sidewall (p < 0.001) and inside the bladder (p < 0.001). The SD attenuation value was significantly decreased after MAR reconstruction at the pelvic sidewall (p = 0.019) but did not show significant differences at the bladder (p = 0.173) or rectal shelf (p = 0.478). In the phantom study, all lesions obscured by metal artifacts on the standard reconstruction images were visualized after MAR reconstruction; however, new artifacts had developed in other parts of the MAR reconstruction images. The use of MAR software with dual-energy CT decreases metal artifacts and increases diagnostic confidence in the assessment of the pelvic cavity but also introduces new artifacts that can obscure pelvic structures.

Structured Light Based 3d Scanning for Specular Surface by the Combination of Gray Code and Phase Shifting

NASA Astrophysics Data System (ADS)

Zhang, Yujia; Yilmaz, Alper

2016-06-01

Surface reconstruction using coded structured light is considered one of the most reliable techniques for high-quality 3D scanning. With a calibrated projector-camera stereo system, a light pattern is projected onto the scene and imaged by the camera. Correspondences between projected and recovered patterns are computed in the decoding process, which is used to generate 3D point cloud of the surface. However, the indirect illumination effects on the surface, such as subsurface scattering and interreflections, will raise the difficulties in reconstruction. In this paper, we apply maximum min-SW gray code to reduce the indirect illumination effects of the specular surface. We also analysis the errors when comparing the maximum min-SW gray code and the conventional gray code, which justifies that the maximum min-SW gray code has significant superiority to reduce the indirect illumination effects. To achieve sub-pixel accuracy, we project high frequency sinusoidal patterns onto the scene simultaneously. But for specular surface, the high frequency patterns are susceptible to decoding errors. Incorrect decoding of high frequency patterns will result in a loss of depth resolution. Our method to resolve this problem is combining the low frequency maximum min-SW gray code and the high frequency phase shifting code, which achieves dense 3D reconstruction for specular surface. Our contributions include: (i) A complete setup of the structured light based 3D scanning system; (ii) A novel combination technique of the maximum min-SW gray code and phase shifting code. First, phase shifting decoding with sub-pixel accuracy. Then, the maximum min-SW gray code is used to resolve the ambiguity resolution. According to the experimental results and data analysis, our structured light based 3D scanning system enables high quality dense reconstruction of scenes with a small number of images. Qualitative and quantitative comparisons are performed to extract the advantages of our new combined coding method.

l0 regularization based on a prior image incorporated non-local means for limited-angle X-ray CT reconstruction.

PubMed

Zhang, Lingli; Zeng, Li; Guo, Yumeng

2018-01-01

Restricted by the scanning environment in some CT imaging modalities, the acquired projection data are usually incomplete, which may lead to a limited-angle reconstruction problem. Thus, image quality usually suffers from the slope artifacts. The objective of this study is to first investigate the distorted domains of the reconstructed images which encounter the slope artifacts and then present a new iterative reconstruction method to address the limited-angle X-ray CT reconstruction problem. The presented framework of new method exploits the structural similarity between the prior image and the reconstructed image aiming to compensate the distorted edges. Specifically, the new method utilizes l0 regularization and wavelet tight framelets to suppress the slope artifacts and pursue the sparsity. New method includes following 4 steps to (1) address the data fidelity using SART; (2) compensate for the slope artifacts due to the missed projection data using the prior image and modified nonlocal means (PNLM); (3) utilize l0 regularization to suppress the slope artifacts and pursue the sparsity of wavelet coefficients of the transformed image by using iterative hard thresholding (l0W); and (4) apply an inverse wavelet transform to reconstruct image. In summary, this method is referred to as "l0W-PNLM". Numerical implementations showed that the presented l0W-PNLM was superior to suppress the slope artifacts while preserving the edges of some features as compared to the commercial and other popular investigative algorithms. When the image to be reconstructed is inconsistent with the prior image, the new method can avoid or minimize the distorted edges in the reconstructed images. Quantitative assessments also showed that applying the new method obtained the highest image quality comparing to the existing algorithms. This study demonstrated that the presented l0W-PNLM yielded higher image quality due to a number of unique characteristics, which include that (1) it utilizes the structural similarity between the reconstructed image and prior image to modify the distorted edges by slope artifacts; (2) it adopts wavelet tight frames to obtain the first and high derivative in several directions and levels; and (3) it takes advantage of l0 regularization to promote the sparsity of wavelet coefficients, which is effective for the inhibition of the slope artifacts. Therefore, the new method can address the limited-angle CT reconstruction problem effectively and have practical significance.

Respiratory Motion-Resolved Compressed Sensing Reconstruction of Free-Breathing Radial Acquisition for Dynamic Liver Magnetic Resonance Imaging.

PubMed

Chandarana, Hersh; Feng, Li; Ream, Justin; Wang, Annie; Babb, James S; Block, Kai Tobias; Sodickson, Daniel K; Otazo, Ricardo

2015-11-01

This study aimed to demonstrate feasibility of free-breathing radial acquisition with respiratory motion-resolved compressed sensing reconstruction [extra-dimensional golden-angle radial sparse parallel imaging (XD-GRASP)] for multiphase dynamic gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced liver imaging, and to compare image quality to compressed sensing reconstruction with respiratory motion-averaging (GRASP) and prior conventional breath-held Cartesian-sampled data sets [BH volume interpolated breath-hold examination (VIBE)] in same patients. In this Health Insurance Portability and Accountability Act-compliant prospective study, 16 subjects underwent free-breathing continuous radial acquisition during Gd-EOB-DTPA injection and had prior BH-VIBE available. Acquired data were reconstructed using motion-averaging GRASP approach in which consecutive 84 spokes were grouped in each contrast-enhanced phase for a temporal resolution of approximately 14 seconds. Additionally, respiratory motion-resolved reconstruction was performed from the same k-space data by sorting each contrast-enhanced phase into multiple respiratory motion states using compressed sensing algorithm named XD-GRASP, which exploits sparsity along both the contrast-enhancement and respiratory-state dimensions.Contrast-enhanced dynamic multiphase XD-GRASP, GRASP, and BH-VIBE images were anonymized, pooled together in a random order, and presented to 2 board-certified radiologists for independent evaluation of image quality, with higher score indicating more optimal examination. The XD-GRASP reconstructions had significantly (all P < 0.05) higher overall image quality scores compared to GRASP for early arterial (reader 1: 4.3 ± 0.6 vs 3.31 ± 0.6; reader 2: 3.81 ± 0.8 vs 3.38 ± 0.9) and late arterial (reader 1: 4.5 ± 0.6 vs 3.63 ± 0.6; reader 2: 3.56 ± 0.5 vs 2.88 ± 0.7) phases of enhancement for both readers. The XD-GRASP also had higher overall image quality score in portal venous phase, which was significant for reader 1 (4.44 ± 0.5 vs 3.75 ± 0.8; P = 0.002). In addition, the XD-GRASP had higher overall image quality score compared to BH-VIBE for early (reader 1: 4.3 ± 0.6 vs 3.88 ± 0.6; reader 2: 3.81 ± 0.8 vs 3.50 ± 1.0) and late (reader 1: 4.5 ± 0.6 vs 3.44 ± 0.6; reader 2: 3.56 ± 0.5 vs 2.94 ± 0.9) arterial phases. Free-breathing motion-resolved XD-GRASP reconstructions provide diagnostic high-quality multiphase images in patients undergoing Gd-EOB-DTPA-enhanced liver examination.

In vivo bioluminescence tomography based on multi-view projection and 3D surface reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Shuang; Wang, Kun; Leng, Chengcai; Deng, Kexin; Hu, Yifang; Tian, Jie

2015-03-01

Bioluminescence tomography (BLT) is a powerful optical molecular imaging modality, which enables non-invasive realtime in vivo imaging as well as 3D quantitative analysis in preclinical studies. In order to solve the inverse problem and reconstruct inner light sources accurately, the prior structural information is commonly necessary and obtained from computed tomography or magnetic resonance imaging. This strategy requires expensive hybrid imaging system, complicated operation protocol and possible involvement of ionizing radiation. The overall robustness highly depends on the fusion accuracy between the optical and structural information. In this study we present a pure optical bioluminescence tomographic system (POBTS) and a novel BLT method based on multi-view projection acquisition and 3D surface reconstruction. The POBTS acquired a sparse set of white light surface images and bioluminescent images of a mouse. Then the white light images were applied to an approximate surface model to generate a high quality textured 3D surface reconstruction of the mouse. After that we integrated multi-view luminescent images based on the previous reconstruction, and applied an algorithm to calibrate and quantify the surface luminescent flux in 3D.Finally, the internal bioluminescence source reconstruction was achieved with this prior information. A BALB/C mouse with breast tumor of 4T1-fLuc cells mouse model were used to evaluate the performance of the new system and technique. Compared with the conventional hybrid optical-CT approach using the same inverse reconstruction method, the reconstruction accuracy of this technique was improved. The distance error between the actual and reconstructed internal source was decreased by 0.184 mm.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

PubMed

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Low-dose CT reconstruction with patch based sparsity and similarity constraints

NASA Astrophysics Data System (ADS)

Xu, Qiong; Mou, Xuanqin

2014-03-01

As the rapid growth of CT based medical application, low-dose CT reconstruction becomes more and more important to human health. Compared with other methods, statistical iterative reconstruction (SIR) usually performs better in lowdose case. However, the reconstructed image quality of SIR highly depends on the prior based regularization due to the insufficient of low-dose data. The frequently-used regularization is developed from pixel based prior, such as the smoothness between adjacent pixels. This kind of pixel based constraint cannot distinguish noise and structures effectively. Recently, patch based methods, such as dictionary learning and non-local means filtering, have outperformed the conventional pixel based methods. Patch is a small area of image, which expresses structural information of image. In this paper, we propose to use patch based constraint to improve the image quality of low-dose CT reconstruction. In the SIR framework, both patch based sparsity and similarity are considered in the regularization term. On one hand, patch based sparsity is addressed by sparse representation and dictionary learning methods, on the other hand, patch based similarity is addressed by non-local means filtering method. We conducted a real data experiment to evaluate the proposed method. The experimental results validate this method can lead to better image with less noise and more detail than other methods in low-count and few-views cases.

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

PubMed

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

2015-12-07

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 algorithm, the code was implemented with a graphic processing unit for parallel processing purposes.Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms.The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

Detector response artefacts in spectral reconstruction

NASA Astrophysics Data System (ADS)

Olsen, Ulrik L.; Christensen, Erik D.; Khalil, Mohamad; Gu, Yun; Kehres, Jan

2017-09-01

Energy resolved detectors are gaining traction as a tool to achieve better material contrast. K-edge imaging and tomography is an example of a method with high potential that has evolved on the capabilities of photon counting energy dispersive detectors. Border security is also beginning to see instruments taking advantage of energy resolved detectors. The progress of the field is halted by the limitations of the detectors. The limitations include nonlinear response for both x-ray intensity and x-ray spectrum. In this work we investigate how the physical interactions in the energy dispersive detectors affect the quality of the reconstruction and how corrections restore the quality. We have modeled detector responses for the primary detrimental effects occurring in the detector; escape peaks, charge sharing/loss and pileup. The effect of the change in the measured spectra is evaluated based on the artefacts occurring in the reconstructed images. We also evaluate the effect of a correction algorithm for reducing these artefacts on experimental data acquired with a setup using Multix ME-100 V-2 line detector modules. The artefacts were seen to introduce 20% deviation in the reconstructed attenuation coefficient for the uncorrected detector. We performed tomography experiments on samples with various materials interesting for security applications and found the SSIM to increase > 5% below 60keV. Our work shows that effective corrections schemes are necessary for the accurate material classification in security application promised by the advent of high flux detectors for spectral tomography

Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

PubMed

O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

2017-12-06

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

Tomography for two-dimensional gas temperature distribution based on TDLAS

NASA Astrophysics Data System (ADS)

Luo, Can; Wang, Yunchu; Xing, Fei

2018-03-01

Based on tunable diode laser absorption spectroscopy (TDLAS), the tomography is used to reconstruct the combustion gas temperature distribution. The effects of number of rays, number of grids, and spacing of rays on the temperature reconstruction results for parallel ray are researched. The reconstruction quality is proportional to the ray number. The quality tends to be smoother when the ray number exceeds a certain value. The best quality is achieved when η is between 0.5 and 1. A virtual ray method combined with the reconstruction algorithms is tested. It is found that virtual ray method is effective to improve the accuracy of reconstruction results, compared with the original method. The linear interpolation method and cubic spline interpolation method, are used to improve the calculation accuracy of virtual ray absorption value. According to the calculation results, cubic spline interpolation is better. Moreover, the temperature distribution of a TBCC combustion chamber is used to validate those conclusions.

Application of a dual-resolution voxelization scheme to compressed-sensing (CS)-based iterative reconstruction in digital tomosynthesis (DTS)

NASA Astrophysics Data System (ADS)

Park, S. Y.; Kim, G. A.; Cho, H. S.; Park, C. K.; Lee, D. Y.; Lim, H. W.; Lee, H. W.; Kim, K. S.; Kang, S. Y.; Park, J. E.; Kim, W. S.; Jeon, D. H.; Je, U. K.; Woo, T. H.; Oh, J. E.

2018-02-01

In recent digital tomosynthesis (DTS), iterative reconstruction methods are often used owing to the potential to provide multiplanar images of superior image quality to conventional filtered-backprojection (FBP)-based methods. However, they require enormous computational cost in the iterative process, which has still been an obstacle to put them to practical use. In this work, we propose a new DTS reconstruction method incorporated with a dual-resolution voxelization scheme in attempt to overcome these difficulties, in which the voxels outside a small region-of-interest (ROI) containing target diagnosis are binned by 2 × 2 × 2 while the voxels inside the ROI remain unbinned. We considered a compressed-sensing (CS)-based iterative algorithm with a dual-constraint strategy for more accurate DTS reconstruction. We implemented the proposed algorithm and performed a systematic simulation and experiment to demonstrate its viability. Our results indicate that the proposed method seems to be effective for reducing computational cost considerably in iterative DTS reconstruction, keeping the image quality inside the ROI not much degraded. A binning size of 2 × 2 × 2 required only about 31.9% computational memory and about 2.6% reconstruction time, compared to those for no binning case. The reconstruction quality was evaluated in terms of the root-mean-square error (RMSE), the contrast-to-noise ratio (CNR), and the universal-quality index (UQI).

Introduction of a hybrid treatment delivery system used for quality assurance in multi-catheter interstitial brachytherapy

NASA Astrophysics Data System (ADS)

Kallis, Karoline; Kreppner, Stephan; Lotter, Michael; Fietkau, Rainer; Strnad, Vratislav; Bert, Christoph

2018-05-01

Multi-catheter interstitial brachytherapy (iBT) is a treatment option for breast cancer patients after breast conserving surgery. Typically, only a few additional quality interventions after the first irradiation have been introduced to ensure the planned treatment delivery. Therefore, the purpose of this study is to show the possibilities of an electromagnetic tracking (EMT) system integrated into the afterloader for quality assurance (QA) in high-dose rate (HDR) iBT of patients with breast cancer. The hybrid afterloader system equipped with an electromagnetic sensor was used for all phantom and patient measurements. Phantom measurements were conducted to estimate the quality of different evaluation schemes. After a coherent point drift registration of the EMT traces to the reconstructed catheters based on computed tomograms the dwell positions (DP) were defined. Different fitting and interpolation methods were analyzed for the reconstruction of DPs. All estimated DPs were compared to the DPs defined in treatment planning. Until now, the implant geometry of 20 patients treated with HDR brachytherapy was acquired and explored. Regarding the reconstruction techniques, both fitting and interpolation were able to detect manually introduced shifts and swaps. Nonetheless, interpolation showed superior results (RMSE  =  1.27 mm), whereas fitting seemed to be more stable to distortion and motion. The EMT system proved to be beneficial for QA in brachytherapy and furthermore, clinical feasibility was proven.

Online dose reconstruction for tracked volumetric arc therapy: Real-time implementation and offline quality assurance for prostate SBRT.

PubMed

Kamerling, Cornelis Ph; Fast, Martin F; Ziegenhein, Peter; Menten, Martin J; Nill, Simeon; Oelfke, Uwe

2017-11-01

Firstly, this study provides a real-time implementation of online dose reconstruction for tracked volumetric arc therapy (VMAT). Secondly, this study describes a novel offline quality assurance tool, based on commercial dose calculation algorithms. Online dose reconstruction for VMAT is a computationally challenging task in terms of computer memory usage and calculation speed. To potentially reduce the amount of memory used, we analyzed the impact of beam angle sampling for dose calculation on the accuracy of the dose distribution. To establish the performance of the method, we planned two single-arc VMAT prostate stereotactic body radiation therapy cases for delivery with dynamic MLC tracking. For quality assurance of our online dose reconstruction method we have also developed a stand-alone offline dose reconstruction tool, which utilizes the RayStation treatment planning system to calculate dose. For the online reconstructed dose distributions of the tracked deliveries, we could establish strong resemblance for 72 and 36 beam co-planar equidistant beam samples with less than 1.2% deviation for the assessed dose-volume indicators (clinical target volume D98 and D2, and rectum D2). We could achieve average runtimes of 28-31 ms per reported MLC aperture for both dose computation and accumulation, meeting our real-time requirement. To cross-validate the offline tool, we have compared the planned dose to the offline reconstructed dose for static deliveries and found excellent agreement (3%/3 mm global gamma passing rates of 99.8%-100%). Being able to reconstruct dose during delivery enables online quality assurance and online replanning strategies for VMAT. The offline quality assurance tool provides the means to validate novel online dose reconstruction applications using a commercial dose calculation engine. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Considering low-rank, sparse and gas-inflow effects constraints for accelerated pulmonary dynamic hyperpolarized 129Xe MRI

NASA Astrophysics Data System (ADS)

Xiao, Sa; Deng, He; Duan, Caohui; Xie, Junshuai; Zhang, Huiting; Sun, Xianping; Ye, Chaohui; Zhou, Xin

2018-05-01

Dynamic hyperpolarized (HP) 129Xe MRI is able to visualize the process of lung ventilation, which potentially provides unique information about lung physiology and pathophysiology. However, the longitudinal magnetization of HP 129Xe is nonrenewable, making it difficult to achieve high image quality while maintaining high temporal-spatial resolution in the pulmonary dynamic MRI. In this paper, we propose a new accelerated dynamic HP 129Xe MRI scheme incorporating the low-rank, sparse and gas-inflow effects (L + S + G) constraints. According to the gas-inflow effects of HP gas during the lung inspiratory process, a variable-flip-angle (VFA) strategy is designed to compensate for the rapid attenuation of the magnetization. After undersampling k-space data, an effective reconstruction algorithm considering the low-rank, sparse and gas-inflow effects constraints is developed to reconstruct dynamic MR images. In this way, the temporal and spatial resolution of dynamic MR images is improved and the artifacts are lessened. Simulation and in vivo experiments implemented on the phantom and healthy volunteers demonstrate that the proposed method is not only feasible and effective to compensate for the decay of the magnetization, but also has a significant improvement compared with the conventional reconstruction algorithms (P-values are less than 0.05). This confirms the superior performance of the proposed designs and their ability to maintain high quality and temporal-spatial resolution.

Iterative reconstruction of simulated low count data: a comparison of post-filtering versus regularised OSEM

NASA Astrophysics Data System (ADS)

Karaoglanis, K.; Efthimiou, N.; Tsoumpas, C.

2015-09-01

Low count PET data is a challenge for medical image reconstruction. The statistics of a dataset is a key factor of the quality of the reconstructed images. Reconstruction algorithms which would be able to compensate for low count datasets could provide the means to reduce the patient injected doses and/or reduce the scan times. It has been shown that the use of priors improve the image quality in low count conditions. In this study we compared regularised versus post-filtered OSEM for their performance on challenging simulated low count datasets. Initial visual comparison demonstrated that both algorithms improve the image quality, although the use of regularization does not introduce the undesired blurring as post-filtering.

Adaptive slab laser beam quality improvement using a weighted least-squares reconstruction algorithm.

PubMed

Chen, Shanqiu; Dong, LiZhi; Chen, XiaoJun; Tan, Yi; Liu, Wenjin; Wang, Shuai; Yang, Ping; Xu, Bing; Ye, YuTang

2016-04-10

Adaptive optics is an important technology for improving beam quality in solid-state slab lasers. However, there are uncorrectable aberrations in partial areas of the beam. In the criterion of the conventional least-squares reconstruction method, it makes the zones with small aberrations nonsensitive and hinders this zone from being further corrected. In this paper, a weighted least-squares reconstruction method is proposed to improve the relative sensitivity of zones with small aberrations and to further improve beam quality. Relatively small weights are applied to the zones with large residual aberrations. Comparisons of results show that peak intensity in the far field improved from 1242 analog digital units (ADU) to 2248 ADU, and beam quality β improved from 2.5 to 2.0. This indicates the weighted least-squares method has better performance than the least-squares reconstruction method when there are large zonal uncorrectable aberrations in the slab laser system.

Dual-Energy Contrast-Enhanced Breast Tomosynthesis: Optimization of Beam Quality for Dose and Image Quality

PubMed Central

Samei, Ehsan; Saunders, Robert S.

2014-01-01

Dual-energy contrast-enhanced breast tomosynthesis is a promising technique to obtain three-dimensional functional information from the breast with high resolution and speed. To optimize this new method, this study searched for the beam quality that maximized image quality in terms of mass detection performance. A digital tomosynthesis system was modeled using a fast ray-tracing algorithm, which created simulated projection images by tracking photons through a voxelized anatomical breast phantom containing iodinated lesions. The single-energy images were combined into dual-energy images through a weighted log subtraction process. The weighting factor was optimized to minimize anatomical noise, while the dose distribution was chosen to minimize quantum noise. The dual-energy images were analyzed for the signal difference to noise ratio (SdNR) of iodinated masses. The fast ray-tracing explored 523,776 dual-energy combinations to identify which yields optimum mass SdNR. The ray-tracing results were verified using a Monte Carlo model for a breast tomosynthesis system with a selenium-based flat-panel detector. The projection images from our voxelized breast phantom were obtained at a constant total glandular dose. The projections were combined using weighted log subtraction and reconstructed using commercial reconstruction software. The lesion SdNR was measured in the central reconstructed slice. The SdNR performance varied markedly across the kVp and filtration space. Ray-tracing results indicated that the mass SdNR was maximized with a high-energy tungsten beam at 49 kVp with 92.5 μm of copper filtration and a low-energy tungsten beam at 49 kVp with 95 μm of tin filtration. This result was consistent with Monte Carlo findings. This mammographic technique led to a mass SdNR of 0.92 ± 0.03 in the projections and 3.68 ± 0.19 in the reconstructed slices. These values were markedly higher than those for non-optimized techniques. Our findings indicate that dual-energy breast tomosynthesis can be performed optimally at 49 kVp with alternative copper and tin filters, with reconstruction following weighted subtraction. The optimum technique provides best visibility of iodine against structured breast background in dual-energy contrast-enhanced breast tomosynthesis. PMID:21908902

Development and clinical translation of a cone-beam CT scanner for high-quality imaging of intracranial hemorrhage

NASA Astrophysics Data System (ADS)

Sisniega, A.; Xu, J.; Dang, H.; Zbijewski, W.; Stayman, J. W.; Mow, M.; Koliatsos, V. E.; Aygun, N.; Wang, X.; Foos, D. H.; Siewerdsen, J. H.

2017-03-01

Purpose: Prompt, reliable detection of intracranial hemorrhage (ICH) is essential for treatment of stroke and traumatic brain injury, and would benefit from availability of imaging directly at the point-of-care. This work reports the performance evaluation of a clinical prototype of a cone-beam CT (CBCT) system for ICH imaging and introduces novel algorithms for model-based reconstruction with compensation for data truncation and patient motion. Methods: The tradeoffs in dose and image quality were investigated as a function of analytical (FBP) and model-based iterative reconstruction (PWLS) algorithm parameters using phantoms with ICH-mimicking inserts. Image quality in clinical applications was evaluated in a human cadaver imaged with simulated ICH. Objects outside of the field of view (FOV), such as the head-holder, were found to introduce challenging truncation artifacts in PWLS that were mitigated with a novel multi-resolution reconstruction strategy. Following phantom and cadaver studies, the scanner was translated to a clinical pilot study. Initial clinical experience indicates the presence of motion in some patient scans, and an image-based motion estimation method that does not require fiducial tracking or prior patient information was implemented and evaluated. Results: The weighted CTDI for a nominal scan technique was 22.8 mGy. The high-resolution FBP reconstruction protocol achieved < 0.9 mm full width at half maximum (FWHM) of the point spread function (PSF). The PWLS soft-tissue reconstruction showed <1.2 mm PSF FWHM and lower noise than FBP at the same resolution. Effects of truncation in PWLS were mitigated with the multi-resolution approach, resulting in 60% reduction in root mean squared error compared to conventional PWLS. Cadaver images showed clear visualization of anatomical landmarks (ventricles and sulci), and ICH was conspicuous. The motion compensation method was shown in clinical studies to restore visibility of fine bone structures, such as the subtle fracture, cranial sutures, and the cochlea as well as subtle low-contrast structures in the brain parenchyma. Conclusion: The imaging performance of the prototype suggests sufficient quality for ICH imaging and motivates continued clinical studies to assess the diagnosis utility of the CBCT system in realistic clinical scenarios at the point of care.

Investigation of iterative image reconstruction in low-dose breast CT

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Combined Use of Automatic Tube Voltage Selection and Current Modulation with Iterative Reconstruction for CT Evaluation of Small Hypervascular Hepatocellular Carcinomas: Effect on Lesion Conspicuity and Image Quality

PubMed Central

Lv, Peijie; Liu, Jie; Zhang, Rui; Jia, Yan

2015-01-01

Objective To assess the lesion conspicuity and image quality in CT evaluation of small (≤ 3 cm) hepatocellular carcinomas (HCCs) using automatic tube voltage selection (ATVS) and automatic tube current modulation (ATCM) with or without iterative reconstruction. Materials and Methods One hundred and five patients with 123 HCC lesions were included. Fifty-seven patients were scanned using both ATVS and ATCM and images were reconstructed using either filtered back-projection (FBP) (group A1) or sinogram-affirmed iterative reconstruction (SAFIRE) (group A2). Forty-eight patients were imaged using only ATCM, with a fixed tube potential of 120 kVp and FBP reconstruction (group B). Quantitative parameters (image noise in Hounsfield unit and contrast-to-noise ratio of the aorta, the liver, and the hepatic tumors) and qualitative visual parameters (image noise, overall image quality, and lesion conspicuity as graded on a 5-point scale) were compared among the groups. Results Group A2 scanned with the automatically chosen 80 kVp and 100 kVp tube voltages ranked the best in lesion conspicuity and subjective and objective image quality (p values ranging from < 0.001 to 0.004) among the three groups, except for overall image quality between group A2 and group B (p = 0.022). Group A1 showed higher image noise (p = 0.005) but similar lesion conspicuity and overall image quality as compared with group B. The radiation dose in group A was 19% lower than that in group B (p = 0.022). Conclusion CT scanning with combined use of ATVS and ATCM and image reconstruction with SAFIRE algorithm provides higher lesion conspicuity and better image quality for evaluating small hepatic HCCs with radiation dose reduction. PMID:25995682

Acquisition of a full-resolution image and aliasing reduction for a spatially modulated imaging polarimeter with two snapshots

PubMed Central

Zhang, Jing; Yuan, Changan; Huang, Guohua; Zhao, Yinjun; Ren, Wenyi; Cao, Qizhi; Li, Jianying; Jin, Mingwu

2018-01-01

A snapshot imaging polarimeter using spatial modulation can encode four Stokes parameters allowing instantaneous polarization measurement from a single interferogram. However, the reconstructed polarization images could suffer a severe aliasing signal if the high-frequency component of the intensity image is prominent and occurs in the polarization channels, and the reconstructed intensity image also suffers reduction of spatial resolution due to low-pass filtering. In this work, a method using two anti-phase snapshots is proposed to address the two problems simultaneously. The full-resolution target image and the pure interference fringes can be obtained from the sum and the difference of the two anti-phase interferograms, respectively. The polarization information reconstructed from the pure interference fringes does not contain the aliasing signal from the high-frequency component of the object intensity image. The principles of the method are derived and its feasibility is tested by both computer simulation and a verification experiment. This work provides a novel method for spatially modulated imaging polarization technology with two snapshots to simultaneously reconstruct a full-resolution object intensity image and high-quality polarization components. PMID:29714224

Feasibility of deep-inspiration breath-hold PET/CT with short-time acquisition: detectability for pulmonary lesions compared with respiratory-gated PET/CT.

PubMed

Yamashita, Shozo; Yokoyama, Kunihiko; Onoguchi, Masahisa; Yamamoto, Haruki; Hiko, Shigeaki; Horita, Akihiro; Nakajima, Kenichi

2014-01-01

Deep-inspiration breath-hold (DIBH) PET/CT with short-time acquisition and respiratory-gated (RG) PET/CT are performed for pulmonary lesions to reduce the respiratory motion artifacts, and to obtain more accurate standardized uptake value (SUV). DIBH PET/CT demonstrates significant advantages in terms of rapid examination, good quality of CT images and low radiation exposure. On the other hand, the image quality of DIBH PET is generally inferior to that of RG PET because of short-time acquisition resulting in poor signal-to-noise ratio. In this study, RG PET has been regarded as a gold standard, and its detectability between DIBH and RG PET studies was compared using each of the most optimal reconstruction parameters. In the phantom study, the most optimal reconstruction parameters for DIBH and RG PET were determined. In the clinical study, 19 cases were examined using each of the most optimal reconstruction parameters. In the phantom study, the most optimal reconstruction parameters for DIBH and RG PET were different. Reconstruction parameters of DIBH PET could be obtained by reducing the number of subsets for those of RG PET in the state of fixing the number of iterations. In the clinical study, high correlation in the maximum SUV was observed between DIBH and RG PET studies. The clinical result was consistent with that of the phantom study surrounded by air since most of the lesions were located in the low pulmonary radioactivity. DIBH PET/CT may be the most practical method which can be the first choice to reduce respiratory motion artifacts if the detectability of DIBH PET is equivalent with that of RG PET. Although DIBH PET may have limitations in suboptimal signal-to-noise ratio, most of the lesions surrounded by low background radioactivity could provide nearly equivalent image quality between DIBH and RG PET studies when each of the most optimal reconstruction parameters was used.

Reconstructing cone-beam CT with spatially varying qualities for adaptive radiotherapy: a proof-of-principle study.

PubMed

Lu, Wenting; Yan, Hao; Gu, Xuejun; Tian, Zhen; Luo, Ouyang; Yang, Liu; Zhou, Linghong; Cervino, Laura; Wang, Jing; Jiang, Steve; Jia, Xun

2014-10-21

With the aim of maximally reducing imaging dose while meeting requirements for adaptive radiation therapy (ART), we propose in this paper a new cone beam CT (CBCT) acquisition and reconstruction method that delivers images with a low noise level inside a region of interest (ROI) and a relatively high noise level outside the ROI. The acquired projection images include two groups: densely sampled projections at a low exposure with a large field of view (FOV) and sparsely sampled projections at a high exposure with a small FOV corresponding to the ROI. A new algorithm combining the conventional filtered back-projection algorithm and the tight-frame iterative reconstruction algorithm is also designed to reconstruct the CBCT based on these projection data. We have validated our method on a simulated head-and-neck (HN) patient case, a semi-real experiment conducted on a HN cancer patient under a full-fan scan mode, as well as a Catphan phantom under a half-fan scan mode. Relative root-mean-square errors (RRMSEs) of less than 3% for the entire image and ~1% within the ROI compared to the ground truth have been observed. These numbers demonstrate the ability of our proposed method to reconstruct high-quality images inside the ROI. As for the part outside ROI, although the images are relatively noisy, it can still provide sufficient information for radiation dose calculations in ART. Dose distributions calculated on our CBCT image and on a standard CBCT image are in agreement, with a mean relative difference of 0.082% inside the ROI and 0.038% outside the ROI. Compared with the standard clinical CBCT scheme, an imaging dose reduction of approximately 3-6 times inside the ROI was achieved, as well as an 8 times outside the ROI. Regarding computational efficiency, it takes 1-3 min to reconstruct a CBCT image depending on the number of projections used. These results indicate that the proposed method has the potential for application in ART.

Stochastic Optical Reconstruction Microscopy (STORM).

PubMed

Xu, Jianquan; Ma, Hongqiang; Liu, Yang

2017-07-05

Super-resolution (SR) fluorescence microscopy, a class of optical microscopy techniques at a spatial resolution below the diffraction limit, has revolutionized the way we study biology, as recognized by the Nobel Prize in Chemistry in 2014. Stochastic optical reconstruction microscopy (STORM), a widely used SR technique, is based on the principle of single molecule localization. STORM routinely achieves a spatial resolution of 20 to 30 nm, a ten-fold improvement compared to conventional optical microscopy. Among all SR techniques, STORM offers a high spatial resolution with simple optical instrumentation and standard organic fluorescent dyes, but it is also prone to image artifacts and degraded image resolution due to improper sample preparation or imaging conditions. It requires careful optimization of all three aspects-sample preparation, image acquisition, and image reconstruction-to ensure a high-quality STORM image, which will be extensively discussed in this unit. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Motion robust high resolution 3D free-breathing pulmonary MRI using dynamic 3D image self-navigator.

PubMed

Jiang, Wenwen; Ong, Frank; Johnson, Kevin M; Nagle, Scott K; Hope, Thomas A; Lustig, Michael; Larson, Peder E Z

2018-06-01

To achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data. Five-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states. Respiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients. An optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

PubMed

Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

2018-06-01

Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

Accelerated Optical Projection Tomography Applied to In Vivo Imaging of Zebrafish

PubMed Central

Correia, Teresa; Yin, Jun; Ramel, Marie-Christine; Andrews, Natalie; Katan, Matilda; Bugeon, Laurence; Dallman, Margaret J.; McGinty, James; Frankel, Paul; French, Paul M. W.; Arridge, Simon

2015-01-01

Optical projection tomography (OPT) provides a non-invasive 3-D imaging modality that can be applied to longitudinal studies of live disease models, including in zebrafish. Current limitations include the requirement of a minimum number of angular projections for reconstruction of reasonable OPT images using filtered back projection (FBP), which is typically several hundred, leading to acquisition times of several minutes. It is highly desirable to decrease the number of required angular projections to decrease both the total acquisition time and the light dose to the sample. This is particularly important to enable longitudinal studies, which involve measurements of the same fish at different time points. In this work, we demonstrate that the use of an iterative algorithm to reconstruct sparsely sampled OPT data sets can provide useful 3-D images with 50 or fewer projections, thereby significantly decreasing the minimum acquisition time and light dose while maintaining image quality. A transgenic zebrafish embryo with fluorescent labelling of the vasculature was imaged to acquire densely sampled (800 projections) and under-sampled data sets of transmitted and fluorescence projection images. The under-sampled OPT data sets were reconstructed using an iterative total variation-based image reconstruction algorithm and compared against FBP reconstructions of the densely sampled data sets. To illustrate the potential for quantitative analysis following rapid OPT data acquisition, a Hessian-based method was applied to automatically segment the reconstructed images to select the vasculature network. Results showed that 3-D images of the zebrafish embryo and its vasculature of sufficient visual quality for quantitative analysis can be reconstructed using the iterative algorithm from only 32 projections—achieving up to 28 times improvement in imaging speed and leading to total acquisition times of a few seconds. PMID:26308086

Atlas-based head modeling and spatial normalization for high-density diffuse optical tomography: in vivo validation against fMRI.

PubMed

Ferradal, Silvina L; Eggebrecht, Adam T; Hassanpour, Mahlega; Snyder, Abraham Z; Culver, Joseph P

2014-01-15

Diffuse optical imaging (DOI) is increasingly becoming a valuable neuroimaging tool when fMRI is precluded. Recent developments in high-density diffuse optical tomography (HD-DOT) overcome previous limitations of sparse DOI systems, providing improved image quality and brain specificity. These improvements in instrumentation prompt the need for advancements in both i) realistic forward light modeling for accurate HD-DOT image reconstruction, and ii) spatial normalization for voxel-wise comparisons across subjects. Individualized forward light models derived from subject-specific anatomical images provide the optimal inverse solutions, but such modeling may not be feasible in all situations. In the absence of subject-specific anatomical images, atlas-based head models registered to the subject's head using cranial fiducials provide an alternative solution. In addition, a standard atlas is attractive because it defines a common coordinate space in which to compare results across subjects. The question therefore arises as to whether atlas-based forward light modeling ensures adequate HD-DOT image quality at the individual and group level. Herein, we demonstrate the feasibility of using atlas-based forward light modeling and spatial normalization methods. Both techniques are validated using subject-matched HD-DOT and fMRI data sets for visual evoked responses measured in five healthy adult subjects. HD-DOT reconstructions obtained with the registered atlas anatomy (i.e. atlas DOT) had an average localization error of 2.7mm relative to reconstructions obtained with the subject-specific anatomical images (i.e. subject-MRI DOT), and 6.6mm relative to fMRI data. At the group level, the localization error of atlas DOT reconstruction was 4.2mm relative to subject-MRI DOT reconstruction, and 6.1mm relative to fMRI. These results show that atlas-based image reconstruction provides a viable approach to individual head modeling for HD-DOT when anatomical imaging is not available. Copyright © 2013. Published by Elsevier Inc.

Patient-specific geometrical modeling of orthopedic structures with high efficiency and accuracy for finite element modeling and 3D printing.

PubMed

Huang, Huajun; Xiang, Chunling; Zeng, Canjun; Ouyang, Hanbin; Wong, Kelvin Kian Loong; Huang, Wenhua

2015-12-01

We improved the geometrical modeling procedure for fast and accurate reconstruction of orthopedic structures. This procedure consists of medical image segmentation, three-dimensional geometrical reconstruction, and assignment of material properties. The patient-specific orthopedic structures reconstructed by this improved procedure can be used in the virtual surgical planning, 3D printing of real orthopedic structures and finite element analysis. A conventional modeling consists of: image segmentation, geometrical reconstruction, mesh generation, and assignment of material properties. The present study modified the conventional method to enhance software operating procedures. Patient's CT images of different bones were acquired and subsequently reconstructed to give models. The reconstruction procedures were three-dimensional image segmentation, modification of the edge length and quantity of meshes, and the assignment of material properties according to the intensity of gravy value. We compared the performance of our procedures to the conventional procedures modeling in terms of software operating time, success rate and mesh quality. Our proposed framework has the following improvements in the geometrical modeling: (1) processing time: (femur: 87.16 ± 5.90 %; pelvis: 80.16 ± 7.67 %; thoracic vertebra: 17.81 ± 4.36 %; P < 0.05); (2) least volume reduction (femur: 0.26 ± 0.06 %; pelvis: 0.70 ± 0.47, thoracic vertebra: 3.70 ± 1.75 %; P < 0.01) and (3) mesh quality in terms of aspect ratio (femur: 8.00 ± 7.38 %; pelvis: 17.70 ± 9.82 %; thoracic vertebra: 13.93 ± 9.79 %; P < 0.05) and maximum angle (femur: 4.90 ± 5.28 %; pelvis: 17.20 ± 19.29 %; thoracic vertebra: 3.86 ± 3.82 %; P < 0.05). Our proposed patient-specific geometrical modeling requires less operating time and workload, but the orthopedic structures were generated at a higher rate of success as compared with the conventional method. It is expected to benefit the surgical planning of orthopedic structures with less operating time and high accuracy of modeling.

Regularization design for high-quality cone-beam CT of intracranial hemorrhage using statistical reconstruction

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Xu, J.; Sisniega, A.; Zbijewski, W.; Wang, X.; Foos, D. H.; Aygun, N.; Koliatsos, V. E.; Siewerdsen, J. H.

2016-03-01

Intracranial hemorrhage (ICH) is associated with pathologies such as hemorrhagic stroke and traumatic brain injury. Multi-detector CT is the current front-line imaging modality for detecting ICH (fresh blood contrast 40-80 HU, down to 1 mm). Flat-panel detector (FPD) cone-beam CT (CBCT) offers a potential alternative with a smaller scanner footprint, greater portability, and lower cost potentially well suited to deployment at the point of care outside standard diagnostic radiology and emergency room settings. Previous studies have suggested reliable detection of ICH down to 3 mm in CBCT using high-fidelity artifact correction and penalized weighted least-squared (PWLS) image reconstruction with a post-artifact-correction noise model. However, ICH reconstructed by traditional image regularization exhibits nonuniform spatial resolution and noise due to interaction between the statistical weights and regularization, which potentially degrades the detectability of ICH. In this work, we propose three regularization methods designed to overcome these challenges. The first two compute spatially varying certainty for uniform spatial resolution and noise, respectively. The third computes spatially varying regularization strength to achieve uniform "detectability," combining both spatial resolution and noise in a manner analogous to a delta-function detection task. Experiments were conducted on a CBCT test-bench, and image quality was evaluated for simulated ICH in different regions of an anthropomorphic head. The first two methods improved the uniformity in spatial resolution and noise compared to traditional regularization. The third exhibited the highest uniformity in detectability among all methods and best overall image quality. The proposed regularization provides a valuable means to achieve uniform image quality in CBCT of ICH and is being incorporated in a CBCT prototype for ICH imaging.

Emerging Techniques for Dose Optimization in Abdominal CT

PubMed Central

Platt, Joel F.; Goodsitt, Mitchell M.; Al-Hawary, Mahmoud M.; Maturen, Katherine E.; Wasnik, Ashish P.; Pandya, Amit

2014-01-01

Recent advances in computed tomographic (CT) scanning technique such as automated tube current modulation (ATCM), optimized x-ray tube voltage, and better use of iterative image reconstruction have allowed maintenance of good CT image quality with reduced radiation dose. ATCM varies the tube current during scanning to account for differences in patient attenuation, ensuring a more homogeneous image quality, although selection of the appropriate image quality parameter is essential for achieving optimal dose reduction. Reducing the x-ray tube voltage is best suited for evaluating iodinated structures, since the effective energy of the x-ray beam will be closer to the k-edge of iodine, resulting in a higher attenuation for the iodine. The optimal kilovoltage for a CT study should be chosen on the basis of imaging task and patient habitus. The aim of iterative image reconstruction is to identify factors that contribute to noise on CT images with use of statistical models of noise (statistical iterative reconstruction) and selective removal of noise to improve image quality. The degree of noise suppression achieved with statistical iterative reconstruction can be customized to minimize the effect of altered image quality on CT images. Unlike with statistical iterative reconstruction, model-based iterative reconstruction algorithms model both the statistical noise and the physical acquisition process, allowing CT to be performed with further reduction in radiation dose without an increase in image noise or loss of spatial resolution. Understanding these recently developed scanning techniques is essential for optimization of imaging protocols designed to achieve the desired image quality with a reduced dose. © RSNA, 2014 PMID:24428277

Image reconstruction: an overview for clinicians.

PubMed

Hansen, Michael S; Kellman, Peter

2015-03-01

Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI). The MRI raw data is not acquired in image space and the role of the image reconstruction process is to transform the acquired raw data into images that can be interpreted clinically. This process involves multiple signal processing steps that each have an impact on the image quality. This review explains the basic terminology used for describing and quantifying image quality in terms of signal-to-noise ratio and point spread function. In this context, several commonly used image reconstruction components are discussed. The image reconstruction components covered include noise prewhitening for phased array data acquisition, interpolation needed to reconstruct square pixels, raw data filtering for reducing Gibbs ringing artifacts, Fourier transforms connecting the raw data with image space, and phased array coil combination. The treatment of phased array coils includes a general explanation of parallel imaging as a coil combination technique. The review is aimed at readers with no signal processing experience and should enable them to understand what role basic image reconstruction steps play in the formation of clinical images and how the resulting image quality is described. © 2014 Wiley Periodicals, Inc.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

An algorithm for improving the quality of structural images of turbid media in endoscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Potlov, A. Yu.; Frolov, S. V.; Proskurin, S. G.

2018-04-01

High-quality OCT structural images reconstruction algorithm for endoscopic optical coherence tomography of biological tissue is described. The key features of the presented algorithm are: (1) raster scanning and averaging of adjacent Ascans and pixels; (2) speckle level minimization. The described algorithm can be used in the gastroenterology, urology, gynecology, otorhinolaryngology for mucous membranes and skin diagnostics in vivo and in situ.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tweed, Dylan; Yang, Xiaohu; Li, Shijie

The ELUCID project aims to build a series of realistic cosmological simulations that reproduce the spatial and mass distributions of the galaxies as observed in the Sloan Digital Sky Survey. This requires powerful reconstruction techniques to create constrained initial conditions (ICs). We test the reconstruction method by applying it to several N -body simulations. We use two medium-resolution simulations, which each produced three additional constrained N -body simulations. We compare the resulting friend-of-friend catalogs by using the particle indexes as tracers, and quantify the quality of the reconstruction by varying the main smoothing parameter. The cross-identification method we use provesmore » to be efficient, and the results suggest that the most massive reconstructed halos are effectively traced from the same Lagrangian regions in the ICs. A preliminary time-dependence analysis indicates that high-mass-end halos converge only at a redshift close to the reconstruction redshift. This suggests that, for earlier snapshots, only collections of progenitors may be effectively cross-identified.« less

BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions

PubMed Central

2010-01-01

Background Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. Description We describe BiGG, a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest. Conclusions BiGG addresses a need in the systems biology community to have access to high quality curated metabolic models and reconstructions. It is freely available for academic use at http://bigg.ucsd.edu. PMID:20426874

Three-dimensional focus of attention for iterative cone-beam micro-CT reconstruction

NASA Astrophysics Data System (ADS)

Benson, T. M.; Gregor, J.

2006-09-01

Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts of computer cycles and associated memory. In this paper, we show that the computational burden can be reduced by limiting the reconstruction to a small, well-defined portion of the image volume. We first discuss using the support region defined by the set of voxels covered by all of the projection views. We then present a data-driven preprocessing technique called focus of attention that heuristically separates both image and projection data into object and background before reconstruction, thereby further reducing the reconstruction region of interest. We present experimental results for both methods based on mouse data and a parallelized implementation of the SIRT algorithm. The computational savings associated with the support region are substantial. However, the results for focus of attention are even more impressive in that only about one quarter of the computer cycles and memory are needed compared with reconstruction of the entire image volume. The image quality is not compromised by either method.

Cost-effectiveness analysis of the most common orthopaedic surgery procedures: knee arthroscopy and knee anterior cruciate ligament reconstruction.

PubMed

Lubowitz, James H; Appleby, David

2011-10-01

The purpose of this study was to determine the cost-effectiveness of knee arthroscopy and anterior cruciate ligament (ACL) reconstruction. Retrospective analysis of prospectively collected data from a single-surgeon, institutional review board-approved outcomes registry included 2 cohorts: surgically treated knee arthroscopy and ACL reconstruction patients. Our outcome measure is cost-effectiveness (cost of a quality-adjusted life-year [QALY]). The QALY is calculated by multiplying difference in health-related quality of life, before and after treatment, by life expectancy. Health-related quality of life is measured by use of the Quality of Well-Being scale, which has been validated for cost-effectiveness analysis. Costs are facility charges per the facility cost-to-charges ratio plus surgeon fee. Sensitivity analyses are performed to determine the effect of variations in costs or outcomes. There were 93 knee arthroscopy and 35 ACL reconstruction patients included at a mean follow-up of 2.1 years. Cost per QALY was $5,783 for arthroscopy and $10,326 for ACL reconstruction (2009 US dollars). Sensitivity analysis shows that our results are robust (relatively insensitive) to variations in costs or outcomes. Knee arthroscopy and knee ACL reconstruction are very cost-effective. Copyright © 2011 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

Experimental evaluation of the optical quality of DMD SLM for its application as Fourier holograms displaying device

NASA Astrophysics Data System (ADS)

Molodtsov, D. Y.; Cheremkhin, P. A.; Krasnov, V. V.; Rodin, V. G.

2016-04-01

In this paper, the optical quality of micromirror DMD spatial light modulator (SLM) is evaluated and its applicability as an output device for holographic filters in dispersive correlators is analyzed. The possibility of using of DMD SLM extracted from consumer DLP-projector was experimentally evaluated by displaying of Fourier holograms. Software for displaying of holograms was developed. Experiments on holograms reconstruction was conducted with a different number of holograms pixels (and different placement on SLM). Reduction of number of pixels of output hologram (i.e. size of minimum resolvable element) led to improvement of reconstructed image quality. The evaluation shows that not every DMD-chip has acceptable optical quality for its application as display device for Fourier holograms. It was determined that major factor of reconstructed image quality degradation is a curvature of surface of SLM or its safety glass. Ranging hologram size allowed to estimate approximate size of sufficiently flat area of SLM matrix. For tested SLM it was about 1.5 mm. Further hologram size increase led to significant reconstructed image quality degradation. Developed and applied a technique allows to quickly estimate maximum size of holograms that can be displayed with specific SLM without significant degradation of reconstructed image. Additionally it allows to identify areas on the SLM with increased curvature of the surface.

A probabilistic atlas of human brainstem pathways based on connectome imaging data.

PubMed

Tang, Yuchun; Sun, Wei; Toga, Arthur W; Ringman, John M; Shi, Yonggang

2018-04-01

The brainstem is a critical structure that regulates vital autonomic functions, houses the cranial nerves and their nuclei, relays motor and sensory information between the brain and spinal cord, and modulates cognition, mood, and emotions. As a primary relay center, the fiber pathways of the brainstem include efferent and afferent connections among the cerebral cortex, spinal cord, and cerebellum. While diffusion MRI has been successfully applied to map various brain pathways, its application for the in vivo imaging of the brainstem pathways has been limited due to inadequate resolution and large susceptibility-induced distortion artifacts. With the release of high-resolution data from the Human Connectome Project (HCP), there is increasing interest in mapping human brainstem pathways. Previous works relying on HCP data to study brainstem pathways, however, did not consider the prevalence (>80%) of large distortions in the brainstem even after the application of correction procedures from the HCP-Pipeline. They were also limited in the lack of adequate consideration of subject variability in either fiber pathways or region of interests (ROIs) used for bundle reconstruction. To overcome these limitations, we develop in this work a probabilistic atlas of 23 major brainstem bundles using high-quality HCP data passing rigorous quality control. For the large-scale data from the 500-Subject release of HCP, we conducted extensive quality controls to exclude subjects with severe distortions in the brainstem area. After that, we developed a systematic protocol to manually delineate 1300 ROIs on 20 HCP subjects (10 males; 10 females) for the reconstruction of fiber bundles using tractography techniques. Finally, we leveraged our novel connectome modeling techniques including high order fiber orientation distribution (FOD) reconstruction from multi-shell diffusion imaging and topography-preserving tract filtering algorithms to successfully reconstruct the 23 fiber bundles for each subject, which were then used to calculate the probabilistic atlases in the MNI152 space for public release. In our experimental results, we demonstrate that our method yielded anatomically faithful reconstruction of the brainstem pathways and achieved improved performance in comparison with an existing atlas of cerebellar peduncles based on HCP data. These atlases have been publicly released on NITRIC (https://www.nitrc.org/projects/brainstem_atlas/) and can be readily used by brain imaging researchers interested in studying brainstem pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

Do's and don'ts of cryo-electron microscopy: a primer on sample preparation and high quality data collection for macromolecular 3D reconstruction.

PubMed

Cabra, Vanessa; Samsó, Montserrat

2015-01-09

Cryo-electron microscopy (cryoEM) entails flash-freezing a thin layer of sample on a support, and then visualizing the sample in its frozen hydrated state by transmission electron microscopy (TEM). This can be achieved with very low quantity of protein and in the buffer of choice, without the use of any stain, which is very useful to determine structure-function correlations of macromolecules. When combined with single-particle image processing, the technique has found widespread usefulness for 3D structural determination of purified macromolecules. The protocol presented here explains how to perform cryoEM and examines the causes of most commonly encountered problems for rational troubleshooting; following all these steps should lead to acquisition of high quality cryoEM images. The technique requires access to the electron microscope instrument and to a vitrification device. Knowledge of the 3D reconstruction concepts and software is also needed for computerized image processing. Importantly, high quality results depend on finding the right purification conditions leading to a uniform population of structurally intact macromolecules. The ability of cryoEM to visualize macromolecules combined with the versatility of single particle image processing has proven very successful for structural determination of large proteins and macromolecular machines in their near-native state, identification of their multiple components by 3D difference mapping, and creation of pseudo-atomic structures by docking of x-ray structures. The relentless development of cryoEM instrumentation and image processing techniques for the last 30 years has resulted in the possibility to generate de novo 3D reconstructions at atomic resolution level.

Estimation of 3D reconstruction errors in a stereo-vision system

NASA Astrophysics Data System (ADS)

Belhaoua, A.; Kohler, S.; Hirsch, E.

2009-06-01

The paper presents an approach for error estimation for the various steps of an automated 3D vision-based reconstruction procedure of manufactured workpieces. The process is based on a priori planning of the task and built around a cognitive intelligent sensory system using so-called Situation Graph Trees (SGT) as a planning tool. Such an automated quality control system requires the coordination of a set of complex processes performing sequentially data acquisition, its quantitative evaluation and the comparison with a reference model (e.g., CAD object model) in order to evaluate quantitatively the object. To ensure efficient quality control, the aim is to be able to state if reconstruction results fulfill tolerance rules or not. Thus, the goal is to evaluate independently the error for each step of the stereo-vision based 3D reconstruction (e.g., for calibration, contour segmentation, matching and reconstruction) and then to estimate the error for the whole system. In this contribution, we analyze particularly the segmentation error due to localization errors for extracted edge points supposed to belong to lines and curves composing the outline of the workpiece under evaluation. The fitting parameters describing these geometric features are used as quality measure to determine confidence intervals and finally to estimate the segmentation errors. These errors are then propagated through the whole reconstruction procedure, enabling to evaluate their effect on the final 3D reconstruction result, specifically on position uncertainties. Lastly, analysis of these error estimates enables to evaluate the quality of the 3D reconstruction, as illustrated by the shown experimental results.

Tight-frame based iterative image reconstruction for spectral breast CT

PubMed Central

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

2013-01-01

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

Building Virtual Mars

NASA Astrophysics Data System (ADS)

Abercrombie, S. P.; Menzies, A.; Goddard, C.

2017-12-01

Virtual and augmented reality enable scientists to visualize environments that are very difficult, or even impossible to visit, such as the surface of Mars. A useful immersive visualization begins with a high quality reconstruction of the environment under study. This presentation will discuss a photogrammetry pipeline developed at the Jet Propulsion Laboratory to reconstruct 3D models of the surface of Mars using stereo images sent back to Earth by the Curiosity Mars rover. The resulting models are used to support a virtual reality tool (OnSight) that allows scientists and engineers to visualize the surface of Mars as if they were standing on the red planet. Images of Mars present challenges to existing scene reconstruction solutions. Surface images of Mars are sparse with minimal overlap, and are often taken from extremely different viewpoints. In addition, the specialized cameras used by Mars rovers are significantly different than consumer cameras, and GPS localization data is not available on Mars. This presentation will discuss scene reconstruction with an emphasis on coping with limited input data, and on creating models suitable for rendering in virtual reality at high frame rate.

Defining and reconstructing clinical processes based on IHE and BPMN 2.0.

PubMed

Strasser, Melanie; Pfeifer, Franz; Helm, Emmanuel; Schuler, Andreas; Altmann, Josef

2011-01-01

This paper describes the current status and the results of our process management system for defining and reconstructing clinical care processes, which contributes to compare, analyze and evaluate clinical processes and further to identify high cost tasks or stays. The system is founded on IHE, which guarantees standardized interfaces and interoperability between clinical information systems. At the heart of the system there is BPMN, a modeling notation and specification language, which allows the definition and execution of clinical processes. The system provides functionality to define healthcare information system independent clinical core processes and to execute the processes in a workflow engine. Furthermore, the reconstruction of clinical processes is done by evaluating an IHE audit log database, which records patient movements within a health care facility. The main goal of the system is to assist hospital operators and clinical process managers to detect discrepancies between defined and actual clinical processes and as well to identify main causes of high medical costs. Beyond that, the system can potentially contribute to reconstruct and improve clinical processes and enhance cost control and patient care quality.

Reconstruction of large diaphyseal bone defect by simplified bone transport over nail technique: A 7-case series.

PubMed

Ferchaud, F; Rony, L; Ducellier, F; Cronier, P; Steiger, V; Hubert, L

2017-11-01

Reconstruction of large diaphyseal bone defect is complex and the complications rate is high. This study aimed to assess a simplified technique of segmental bone transport by monorail external fixator over an intramedullary nail.A prospective study included 7 patients: 2 femoral and 5 tibial defects. Mean age was 31years (range: 16-61years). Mean follow-up was 62 months (range: 46-84months). Defects were post-traumatic, with a mean length of 7.2cm (range: 4 to 9.5cm). For 3 patients, reconstruction followed primary failure. In 4 cases, a covering flap was necessary. Transport used an external fixator guided by an intramedullary nail, at a rate of 1mm per day. One pin was implanted on either side of the distraction zone. The external fixator was removed 1 month after bone contact at the docking site. Mean bone transport time was 11 weeks (range: 7-15 weeks). Mean external fixation time was 5.1months (range: 3.5 to 8months). Full weight-bearing was allowed 5.7months (range: 3.5-13months) after initiation of transport. In one patient, a pin had to be repositioned. In 3 patients, the transported segment re-ascended after external fixatorablation, requiring repeat external fixation and resumption of transport. There was just 1 case of superficial pin infection. Reconstruction quality was considered "excellent" on the Paley-Marr criteria in 6 cases. The present technique provided excellent reconstruction quality in 6 of the 7 cases. External fixation time was shorter and resumption of weight-bearing earlier than with other reconstruction techniques, notably including bone autograft, vascularized bone graft or the induced membrane technique. Nailing facilitated control of limb axis and length. The complications rate was 50%, comparable to other techniques. This study raises the question of systematic internal fixation of the docking site, to avoid any mobilization of the transported segment. The bone quality, axial control and rapidity shown by the present technique make it well-adapted to reconstruction of diaphyseal bone defect. Four-case series. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Reconstruction-free sensitive wavefront sensor based on continuous position sensitive detectors.

PubMed

Godin, Thomas; Fromager, Michael; Cagniot, Emmanuel; Brunel, Marc; Aït-Ameur, Kamel

2013-12-01

We propose a new device that is able to perform highly sensitive wavefront measurements based on the use of continuous position sensitive detectors and without resorting to any reconstruction process. We demonstrate experimentally its ability to measure small wavefront distortions through the characterization of pump-induced refractive index changes in laser material. In addition, it is shown using computer-generated holograms that this device can detect phase discontinuities as well as improve the quality of sharp phase variations measurements. Results are compared to reference Shack-Hartmann measurements, and dramatic enhancements are obtained.

Magnetic resonance imaging of the subthalamic nucleus for deep brain stimulation.

PubMed

Chandran, Arjun S; Bynevelt, Michael; Lind, Christopher R P

2016-01-01

The subthalamic nucleus (STN) is one of the most important stereotactic targets in neurosurgery, and its accurate imaging is crucial. With improving MRI sequences there is impetus for direct targeting of the STN. High-quality, distortion-free images are paramount. Image reconstruction techniques appear to show the greatest promise in balancing the issue of geometrical distortion and STN edge detection. Existing spin echo- and susceptibility-based MRI sequences are compared with new image reconstruction methods. Quantitative susceptibility mapping is the most promising technique for stereotactic imaging of the STN.

Fast optical transillumination tomography with large-size projection acquisition.

PubMed

Huang, Hsuan-Ming; Xia, Jinjun; Haidekker, Mark A

2008-10-01

Techniques such as optical coherence tomography and diffuse optical tomography have been shown to effectively image highly scattering samples such as tissue. An additional modality has received much less attention: Optical transillumination (OT) tomography, a modality that promises very high acquisition speed for volumetric scans. With the motivation to image tissue-engineered blood vessels for possible biomechanical testing, we have developed a fast OT device using a collimated, noncoherent beam with a large diameter together with a large-size CMOS camera that has the ability to acquire 3D projections in a single revolution of the sample. In addition, we used accelerated iterative reconstruction techniques to improve image reconstruction speed, while at the same time obtaining better image quality than through filtered backprojection. The device was tested using ink-filled polytetrafluorethylene tubes to determine geometric reconstruction accuracy and recovery of absorbance. Even in the presence of minor refractive index mismatch, the weighted error of the measured radius was <5% in all cases, and a high linear correlation of ink absorbance determined with a photospectrometer of R(2) = 0.99 was found, although the OT device systematically underestimated absorbance. Reconstruction time was improved from several hours (standard arithmetic reconstruction) to 90 s per slice with our optimized algorithm. Composed of only a light source, two spatial filters, a sample bath, and a CMOS camera, this device was extremely simple and cost-efficient to build.

Efficacy of model-based iterative reconstruction technique in non-enhanced CT of the renal tracts for ureteric calculi.

PubMed

Tan, T J; Lau, Kenneth K; Jackson, Dana; Ardley, Nicholas; Borasu, Adina

2017-04-01

The purpose of this study was to assess the efficacy of model-based iterative reconstruction (MBIR), statistical iterative reconstruction (SIR), and filtered back projection (FBP) image reconstruction algorithms in the delineation of ureters and overall image quality on non-enhanced computed tomography of the renal tracts (NECT-KUB). This was a prospective study of 40 adult patients who underwent NECT-KUB for investigation of ureteric colic. Images were reconstructed using FBP, SIR, and MBIR techniques and individually and randomly assessed by two blinded radiologists. Parameters measured were overall image quality, presence of ureteric calculus, presence of hydronephrosis or hydroureters, image quality of each ureteric segment, total length of ureters unable to be visualized, attenuation values of image noise, and retroperitoneal fat content for each patient. There were no diagnostic discrepancies between image reconstruction modalities for urolithiasis. Overall image qualities and for each ureteric segment were superior using MBIR (67.5 % rated as 'Good to Excellent' vs. 25 % in SIR and 2.5 % in FBP). The lengths of non-visualized ureteric segments were shortest using MBIR (55.0 % measured 'less than 5 cm' vs. ASIR 33.8 % and FBP 10 %). MBIR was able to reduce overall image noise by up to 49.36 % over SIR and 71.02 % over FBP. MBIR technique improves overall image quality and visualization of ureters over FBP and SIR.

Performance evaluation of algebraic reconstruction technique (ART) for prototype chest digital tomosynthesis (CDT) system

NASA Astrophysics Data System (ADS)

Lee, Haenghwa; Choi, Sunghoon; Jo, Byungdu; Kim, Hyemi; Lee, Donghoon; Kim, Dohyeon; Choi, Seungyeon; Lee, Youngjin; Kim, Hee-Joung

2017-03-01

Chest digital tomosynthesis (CDT) is a new 3D imaging technique that can be expected to improve the detection of subtle lung disease over conventional chest radiography. Algorithm development for CDT system is challenging in that a limited number of low-dose projections are acquired over a limited angular range. To confirm the feasibility of algebraic reconstruction technique (ART) method under variations in key imaging parameters, quality metrics were conducted using LUNGMAN phantom included grand-glass opacity (GGO) tumor. Reconstructed images were acquired from the total 41 projection images over a total angular range of +/-20°. We evaluated contrast-to-noise ratio (CNR) and artifacts spread function (ASF) to investigate the effect of reconstruction parameters such as number of iterations, relaxation parameter and initial guess on image quality. We found that proper value of ART relaxation parameter could improve image quality from the same projection. In this study, proper value of relaxation parameters for zero-image (ZI) and back-projection (BP) initial guesses were 0.4 and 0.6, respectively. Also, the maximum CNR values and the minimum full width at half maximum (FWHM) of ASF were acquired in the reconstructed images after 20 iterations and 3 iterations, respectively. According to the results, BP initial guess for ART method could provide better image quality than ZI initial guess. In conclusion, ART method with proper reconstruction parameters could improve image quality due to the limited angular range in CDT system.

Spectral (Finite) Volume Method for Conservation Laws on Unstructured Grids II: Extension to Two Dimensional Scalar Equation

NASA Technical Reports Server (NTRS)

Wang, Z. J.; Liu, Yen; Kwak, Dochan (Technical Monitor)

2002-01-01

The framework for constructing a high-order, conservative Spectral (Finite) Volume (SV) method is presented for two-dimensional scalar hyperbolic conservation laws on unstructured triangular grids. Each triangular grid cell forms a spectral volume (SV), and the SV is further subdivided into polygonal control volumes (CVs) to supported high-order data reconstructions. Cell-averaged solutions from these CVs are used to reconstruct a high order polynomial approximation in the SV. Each CV is then updated independently with a Godunov-type finite volume method and a high-order Runge-Kutta time integration scheme. A universal reconstruction is obtained by partitioning all SVs in a geometrically similar manner. The convergence of the SV method is shown to depend on how a SV is partitioned. A criterion based on the Lebesgue constant has been developed and used successfully to determine the quality of various partitions. Symmetric, stable, and convergent linear, quadratic, and cubic SVs have been obtained, and many different types of partitions have been evaluated. The SV method is tested for both linear and non-linear model problems with and without discontinuities.

Automatic Texture Reconstruction of 3d City Model from Oblique Images

NASA Astrophysics Data System (ADS)

Kang, Junhua; Deng, Fei; Li, Xinwei; Wan, Fang

2016-06-01

In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets withmore » various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR values were found to increase with decreasing RMSE values of projection angular gaps with strong correlations (r ≈ −0.7) regardless of the reconstruction algorithm used. Conclusions: Based on the authors’ results, displacement-based binning methods, better reconstruction algorithms, and the acquisition of even projection angular views are the most important factors to consider for improving thoracic 4D-CBCT image quality. In view of the practical issues with displacement-based binning and the fact that projection angular spacing is not currently directly controllable, development of better reconstruction algorithms represents the most effective strategy for improving image quality in thoracic 4D-CBCT for IGRT applications at the current stage.« less

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

PubMed

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

2014-07-01

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/cm 3 ) 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.

Digital holographic image fusion for a larger size object using compressive sensing

NASA Astrophysics Data System (ADS)

Tian, Qiuhong; Yan, Liping; Chen, Benyong; Yao, Jiabao; Zhang, Shihua

2017-05-01

Digital holographic imaging fusion for a larger size object using compressive sensing is proposed. In this method, the high frequency component of the digital hologram under discrete wavelet transform is represented sparsely by using compressive sensing so that the data redundancy of digital holographic recording can be resolved validly, the low frequency component is retained totally to ensure the image quality, and multiple reconstructed images with different clear parts corresponding to a laser spot size are fused to realize the high quality reconstructed image of a larger size object. In addition, a filter combing high-pass and low-pass filters is designed to remove the zero-order term from a digital hologram effectively. The digital holographic experimental setup based on off-axis Fresnel digital holography was constructed. The feasible and comparative experiments were carried out. The fused image was evaluated by using the Tamura texture features. The experimental results demonstrated that the proposed method can improve the processing efficiency and visual characteristics of the fused image and enlarge the size of the measured object effectively.

A limited-angle CT reconstruction method based on anisotropic TV minimization.

PubMed

Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge

2013-04-07

This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.

J-pouch versus Roux-en-Y reconstruction after gastrectomy: functional assessment and quality of life (randomized trial).

PubMed

Zonča, Pavel; Malý, Tomáš; Ihnát, Peter; Peteja, Matus; Kraft, Otakar; Kuca, Kamil

2017-01-01

The aim of this study was to evaluate the quality of life and functional emptying of J-pouch versus Roux-en-Y reconstruction after total gastrectomy for malignancy. This study was designed as a prospective, nonblinded, randomized, parallel clinical trial (Trial Number: MN Ostrava, 200604). With informed consent, patients undergoing gastrectomy for malignancy were randomized to J-pouch or Roux-en-Y reconstruction. The time taken for a test semisolid meal labeled with 99m Tc-sulfur colloid to exit the reconstructed parts was measured by dynamic scintigraphy 1 year after resection. Quality of life was measured using the Eypasch questionnaire at the same time as functional emptying assessment. This trial was investigator-initiated. In all, 72 patients were included into the study. The time taken for the test meal to exit the postgastrectomy reconstruction was 16.5±10.0 minutes (mean ± standard deviation) in the Roux-en-Y group and 89.4±37.8 minutes in the "J-pouch" group; the difference was statistically significant ( P <0.001). Emptying of the J-pouch appeared to be a linear decreasing function compared to the exponential pattern seen in the Roux-en-Y group. The quality of life measurement showed scores of 106±18.8 points (mean ± standard deviation) in the Roux-en-Y group compared to 122±22.5 points in the J-pouch group; the difference was statistically significant ( P =0.0016). There were no important adverse events. After total gastrectomy, a J-pouch reconstruction empties more slowly and is associated with higher quality of life compared to Roux-en-Y reconstruction. Whether these two observations have a direct causative link remains unanswered.

Hdr Imaging for Feature Detection on Detailed Architectural Scenes

NASA Astrophysics Data System (ADS)

Kontogianni, G.; Stathopoulou, E. K.; Georgopoulos, A.; Doulamis, A.

2015-02-01

3D reconstruction relies on accurate detection, extraction, description and matching of image features. This is even truer for complex architectural scenes that pose needs for 3D models of high quality, without any loss of detail in geometry or color. Illumination conditions influence the radiometric quality of images, as standard sensors cannot depict properly a wide range of intensities in the same scene. Indeed, overexposed or underexposed pixels cause irreplaceable information loss and degrade digital representation. Images taken under extreme lighting environments may be thus prohibitive for feature detection/extraction and consequently for matching and 3D reconstruction. High Dynamic Range (HDR) images could be helpful for these operators because they broaden the limits of illumination range that Standard or Low Dynamic Range (SDR/LDR) images can capture and increase in this way the amount of details contained in the image. Experimental results of this study prove this assumption as they examine state of the art feature detectors applied both on standard dynamic range and HDR images.

High quality 4D cone-beam CT reconstruction using motion-compensated total variation regularization

NASA Astrophysics Data System (ADS)

Zhang, Hua; Ma, Jianhua; Bian, Zhaoying; Zeng, Dong; Feng, Qianjin; Chen, Wufan

2017-04-01

Four dimensional cone-beam computed tomography (4D-CBCT) has great potential clinical value because of its ability to describe tumor and organ motion. But the challenge in 4D-CBCT reconstruction is the limited number of projections at each phase, which result in a reconstruction full of noise and streak artifacts with the conventional analytical algorithms. To address this problem, in this paper, we propose a motion compensated total variation regularization approach which tries to fully explore the temporal coherence of the spatial structures among the 4D-CBCT phases. In this work, we additionally conduct motion estimation/motion compensation (ME/MC) on the 4D-CBCT volume by using inter-phase deformation vector fields (DVFs). The motion compensated 4D-CBCT volume is then viewed as a pseudo-static sequence, of which the regularization function was imposed on. The regularization used in this work is the 3D spatial total variation minimization combined with 1D temporal total variation minimization. We subsequently construct a cost function for a reconstruction pass, and minimize this cost function using a variable splitting algorithm. Simulation and real patient data were used to evaluate the proposed algorithm. Results show that the introduction of additional temporal correlation along the phase direction can improve the 4D-CBCT image quality.

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

PubMed

Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Ha, Seongmin; Kim, Woo Sun; Kim, In-One

2016-03-01

CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.

76 FR 9787 - NIOSH Dose Reconstruction Program Ten Year Review-Phase I Report on Quality of Science; Request...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-22

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention NIOSH Dose Reconstruction Program Ten Year Review--Phase I Report on Quality of Science; Request for Public Review and... Ten Year Review--Phase I Report on Quality of Science.'' This publication is part of a review by NIOSH...

Adaptive Statistical Iterative Reconstruction-V: Impact on Image Quality in Ultralow-Dose Coronary Computed Tomography Angiography.

PubMed

Benz, Dominik C; Gräni, Christoph; Mikulicic, Fran; Vontobel, Jan; Fuchs, Tobias A; Possner, Mathias; Clerc, Olivier F; Stehli, Julia; Gaemperli, Oliver; Pazhenkottil, Aju P; Buechel, Ronny R; Kaufmann, Philipp A

The clinical utility of a latest generation iterative reconstruction algorithm (adaptive statistical iterative reconstruction [ASiR-V]) has yet to be elucidated for coronary computed tomography angiography (CCTA). This study evaluates the impact of ASiR-V on signal, noise and image quality in CCTA. Sixty-five patients underwent clinically indicated CCTA on a 256-slice CT scanner using an ultralow-dose protocol. Data sets from each patient were reconstructed at 6 different levels of ASiR-V. Signal intensity was measured by placing a region of interest in the aortic root, LMA, and RCA. Similarly, noise was measured in the aortic root. Image quality was visually assessed by 2 readers. Median radiation dose was 0.49 mSv. Image noise decreased with increasing levels of ASiR-V resulting in a significant increase in signal-to-noise ratio in the RCA and LMA (P < 0.001). Correspondingly, image quality significantly increased with higher levels of ASiR-V (P < 0.001). ASiR-V yields substantial noise reduction and improved image quality enabling introduction of ultralow-dose CCTA.

ECG compression using non-recursive wavelet transform with quality control

NASA Astrophysics Data System (ADS)

Liu, Je-Hung; Hung, King-Chu; Wu, Tsung-Ching

2016-09-01

While wavelet-based electrocardiogram (ECG) data compression using scalar quantisation (SQ) yields excellent compression performance, a wavelet's SQ scheme, however, must select a set of multilevel quantisers for each quantisation process. As a result of the properties of multiple-to-one mapping, however, this scheme is not conducive for reconstruction error control. In order to address this problem, this paper presents a single-variable control SQ scheme able to guarantee the reconstruction quality of wavelet-based ECG data compression. Based on the reversible round-off non-recursive discrete periodised wavelet transform (RRO-NRDPWT), the SQ scheme is derived with a three-stage design process that first uses genetic algorithm (GA) for high compression ratio (CR), followed by a quadratic curve fitting for linear distortion control, and the third uses a fuzzy decision-making for minimising data dependency effect and selecting the optimal SQ. The two databases, Physikalisch-Technische Bundesanstalt (PTB) and Massachusetts Institute of Technology (MIT) arrhythmia, are used to evaluate quality control performance. Experimental results show that the design method guarantees a high compression performance SQ scheme with statistically linear distortion. This property can be independent of training data and can facilitate rapid error control.

A comparison of select image-compression algorithms for an electronic still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

This effort is a study of image-compression algorithms for an electronic still camera. An electronic still camera can record and transmit high-quality images without the use of film, because images are stored digitally in computer memory. However, high-resolution images contain an enormous amount of information, and will strain the camera's data-storage system. Image compression will allow more images to be stored in the camera's memory. For the electronic still camera, a compression algorithm that produces a reconstructed image of high fidelity is most important. Efficiency of the algorithm is the second priority. High fidelity and efficiency are more important than a high compression ratio. Several algorithms were chosen for this study and judged on fidelity, efficiency and compression ratio. The transform method appears to be the best choice. At present, the method is compressing images to a ratio of 5.3:1 and producing high-fidelity reconstructed images.

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

PubMed

Wenz, Holger; Maros, Máté E; Meyer, Mathias; Gawlitza, Joshua; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Groden, Christoph; Henzler, Thomas

2016-01-01

To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM. 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction. Images were reconstructed using both, FBP and IR (level 1-5). A Monte-Carlo-simulation-based analysis was used to compare organ-specific-radiation dose. Subjective image quality for various anatomic structures was evaluated using a 4-point Likert-scale and objective image quality was evaluated by comparing signal-to-noise ratios (SNR). Spiral cCT led to a significantly lower (p < 0.05) organ-specific-radiation dose in all targets including eye lense. Subjective image quality of spiral cCT datasets with an IR reconstruction level 5 was rated significantly higher compared to the sequential cCT acquisitions (p < 0.0001). Consecutive mean SNR was significantly higher in all spiral datasets (FBP, IR 1-5) when compared to sequential cCT with a mean SNR improvement of 44.77% (p < 0.0001). Spiral cCT combined with ATCM and IR allows for significant-radiation dose reduction including a reduce eye lens organ-dose when compared to a tilted sequential cCT while improving subjective and objective image quality.

Life quality of patients who underwent breast reconstruction after prophylactic mastectomy: systematic review.

PubMed

Aygin, Dilek; Cengiz, Hande

2018-05-02

Prophylactic mastectomy is used to reduce the incidence of breast cancer in women with genetic predisposition and family history of breast cancer, and the rate of application is increased nowadays. Chronic pain, body image, and sexuality may negatively affect quality of life, while patients generally have increased quality of life and satisfaction after prophylactic mastectomy. The aim of this study is the evaluation of the results of the studies about quality of life of patients who underwent breast reconstruction after prophylactic mastectomy. For the 1996-2016 literature, we searched the databases of Scopus, Science Direct, PubMed, EBSCO, Cochrane, Medline Complete, Ovid, Springer Link, Google Academic, Taylor & Francis, PsychINFO databases. For the gray literature, National Thesis Center and ULAKBIM databases were searched. Seven studies complying with the criteria were included in the review. Seven studies included in this study aimed to investigate the effect of prophylactic mastectomy on breast pain, numbness, sexuality and quality of life. When the studies were reviewed, we were found that the majority of the patients were satisfied with the results of the procedure, although the body image perception and pain/ movement/ perception and sexual problems were experienced after the breast surgery. While overall satisfaction with cosmetic results was high, most women were not satisfied with the softness of the reconstructed breasts, and had problems with breast hardness, numbness and sex. Therefore, it is very important to inform the patients about the complications that may develop after the operation, while there is not enough data about the importance of informing the patients before the operation.

Iterative reconstruction for CT perfusion with a prior-image induced hybrid nonlocal means regularization: Phantom studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Bin; Lyu, Qingwen; Ma, Jianhua

2016-04-15

Purpose: In computed tomography perfusion (CTP) imaging, an initial phase CT acquired with a high-dose protocol can be used to improve the image quality of later phase CT acquired with a low-dose protocol. For dynamic regions, signals in the later low-dose CT may not be completely recovered if the initial CT heavily regularizes the iterative reconstruction process. The authors propose a hybrid nonlocal means (hNLM) regularization model for iterative reconstruction of low-dose CTP to overcome the limitation of the conventional prior-image induced penalty. Methods: The hybrid penalty was constructed by combining the NLM of the initial phase high-dose CT inmore » the stationary region and later phase low-dose CT in the dynamic region. The stationary and dynamic regions were determined by the similarity between the initial high-dose scan and later low-dose scan. The similarity was defined as a Gaussian kernel-based distance between the patch-window of the same pixel in the two scans, and its measurement was then used to weigh the influence of the initial high-dose CT. For regions with high similarity (e.g., stationary region), initial high-dose CT played a dominant role for regularizing the solution. For regions with low similarity (e.g., dynamic region), the regularization relied on a low-dose scan itself. This new hNLM penalty was incorporated into the penalized weighted least-squares (PWLS) for CTP reconstruction. Digital and physical phantom studies were performed to evaluate the PWLS-hNLM algorithm. Results: Both phantom studies showed that the PWLS-hNLM algorithm is superior to the conventional prior-image induced penalty term without considering the signal changes within the dynamic region. In the dynamic region of the Catphan phantom, the reconstruction error measured by root mean square error was reduced by 42.9% in PWLS-hNLM reconstructed image. Conclusions: The PWLS-hNLM algorithm can effectively use the initial high-dose CT to reconstruct low-dose CTP in the stationary region while reducing its influence in the dynamic region.« less

Image quality in low-dose coronary computed tomography angiography with a new high-definition CT scanner.

PubMed

Kazakauskaite, Egle; Husmann, Lars; Stehli, Julia; Fuchs, Tobias; Fiechter, Michael; Klaeser, Bernd; Ghadri, Jelena R; Gebhard, Catherine; Gaemperli, Oliver; Kaufmann, Philipp A

2013-02-01

A new generation of high definition computed tomography (HDCT) 64-slice devices complemented by a new iterative image reconstruction algorithm-adaptive statistical iterative reconstruction, offer substantially higher resolution compared to standard definition CT (SDCT) scanners. As high resolution confers higher noise we have compared image quality and radiation dose of coronary computed tomography angiography (CCTA) from HDCT versus SDCT. Consecutive patients (n = 93) underwent HDCT, and were compared to 93 patients who had previously undergone CCTA with SDCT matched for heart rate (HR), HR variability and body mass index (BMI). Tube voltage and current were adapted to the patient's BMI, using identical protocols in both groups. The image quality of all CCTA scans was evaluated by two independent readers in all coronary segments using a 4-point scale (1, excellent image quality; 2, blurring of the vessel wall; 3, image with artefacts but evaluative; 4, non-evaluative). Effective radiation dose was calculated from DLP multiplied by a conversion factor (0.014 mSv/mGy × cm). The mean image quality score from HDCT versus SDCT was comparable (2.02 ± 0.68 vs. 2.00 ± 0.76). Mean effective radiation dose did not significantly differ between HDCT (1.7 ± 0.6 mSv, range 1.0-3.7 mSv) and SDCT (1.9 ± 0.8 mSv, range 0.8-5.5 mSv; P = n.s.). HDCT scanners allow low-dose 64-slice CCTA scanning with higher resolution than SDCT but maintained image quality and equally low radiation dose. Whether this will translate into higher accuracy of HDCT for CAD detection remains to be evaluated.

Energy and Quality Evaluation for Compressive Sensing of Fetal Electrocardiogram Signals

PubMed Central

Da Poian, Giulia; Brandalise, Denis; Bernardini, Riccardo; Rinaldo, Roberto

2016-01-01

This manuscript addresses the problem of non-invasive fetal Electrocardiogram (ECG) signal acquisition with low power/low complexity sensors. A sensor architecture using the Compressive Sensing (CS) paradigm is compared to a standard compression scheme using wavelets in terms of energy consumption vs. reconstruction quality, and, more importantly, vs. performance of fetal heart beat detection in the reconstructed signals. We show in this paper that a CS scheme based on reconstruction with an over-complete dictionary has similar reconstruction quality to one based on wavelet compression. We also consider, as a more important figure of merit, the accuracy of fetal beat detection after reconstruction as a function of the sensor power consumption. Experimental results with an actual implementation in a commercial device show that CS allows significant reduction of energy consumption in the sensor node, and that the detection performance is comparable to that obtained from original signals for compression ratios up to about 75%. PMID:28025510

Image Reconstruction Under Contact Impedance Effect in Micro Electrical Impedance Tomography Sensors.

PubMed

Liu, Xiayi; Yao, Jiafeng; Zhao, Tong; Obara, Hiromichi; Cui, Yahui; Takei, Masahiro

2018-06-01

Contact impedance has an important effect on micro electrical impedance tomography (EIT) sensors compared to conventional macro sensors. In the present work, a complex contact impedance effect ratio ξ is defined to quantitatively evaluate the effect of the contact impedance on the accuracy of the reconstructed images by micro EIT. Quality of the reconstructed image under various ξ is estimated by the phantom simulation to find the optimum algorithm. The generalized vector sampled pattern matching (GVSPM) method reveals the best image quality and the best tolerance to ξ. Moreover, the images of yeast cells sedimentary distribution in a multilayered microchannel are reconstructed by the GVSPM method under various mean magnitudes of contact impedance effect ratio |ξ|. The result shows that the best image quality that has the smallest voltage error U E = 0.581 is achieved with measurement frequency f = 1 MHz and mean magnitude |ξ| = 26. In addition, the reconstructed images of cells distribution become improper while f < 10 kHz and mean value of |ξ| > 2400.

Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI

PubMed Central

Kamesh Iyer, Srikant; Tasdizen, Tolga; Likhite, Devavrat; DiBella, Edward

2016-01-01

Purpose: Rapid reconstruction of undersampled multicoil MRI data with iterative constrained reconstruction method is a challenge. The authors sought to develop a new substitution based variable splitting algorithm for faster reconstruction of multicoil cardiac perfusion MRI data. Methods: The new method, split Bregman multicoil accelerated reconstruction technique (SMART), uses a combination of split Bregman based variable splitting and iterative reweighting techniques to achieve fast convergence. Total variation constraints are used along the spatial and temporal dimensions. The method is tested on nine ECG-gated dog perfusion datasets, acquired with a 30-ray golden ratio radial sampling pattern and ten ungated human perfusion datasets, acquired with a 24-ray golden ratio radial sampling pattern. Image quality and reconstruction speed are evaluated and compared to a gradient descent (GD) implementation and to multicoil k-t SLR, a reconstruction technique that uses a combination of sparsity and low rank constraints. Results: Comparisons based on blur metric and visual inspection showed that SMART images had lower blur and better texture as compared to the GD implementation. On average, the GD based images had an ∼18% higher blur metric as compared to SMART images. Reconstruction of dynamic contrast enhanced (DCE) cardiac perfusion images using the SMART method was ∼6 times faster than standard gradient descent methods. k-t SLR and SMART produced images with comparable image quality, though SMART was ∼6.8 times faster than k-t SLR. Conclusions: The SMART method is a promising approach to reconstruct good quality multicoil images from undersampled DCE cardiac perfusion data rapidly. PMID:27036592

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

NASA Astrophysics Data System (ADS)

Feygelman, V.; Nelms, B.

2013-06-01

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

Design of k-Space Channel Combination Kernels and Integration with Parallel Imaging

PubMed Central

Beatty, Philip J.; Chang, Shaorong; Holmes, James H.; Wang, Kang; Brau, Anja C. S.; Reeder, Scott B.; Brittain, Jean H.

2014-01-01

Purpose In this work, a new method is described for producing local k-space channel combination kernels using a small amount of low-resolution multichannel calibration data. Additionally, this work describes how these channel combination kernels can be combined with local k-space unaliasing kernels produced by the calibration phase of parallel imaging methods such as GRAPPA, PARS and ARC. Methods Experiments were conducted to evaluate both the image quality and computational efficiency of the proposed method compared to a channel-by-channel parallel imaging approach with image-space sum-of-squares channel combination. Results Results indicate comparable image quality overall, with some very minor differences seen in reduced field-of-view imaging. It was demonstrated that this method enables a speed up in computation time on the order of 3–16X for 32-channel data sets. Conclusion The proposed method enables high quality channel combination to occur earlier in the reconstruction pipeline, reducing computational and memory requirements for image reconstruction. PMID:23943602

ECG-gated interventional cardiac reconstruction for non-periodic motion.

PubMed

Rohkohl, Christopher; Lauritsch, Günter; Biller, Lisa; Hornegger, Joachim

2010-01-01

The 3-D reconstruction of cardiac vasculature using C-arm CT is an active and challenging field of research. In interventional environments patients often do have arrhythmic heart signals or cannot hold breath during the complete data acquisition. This important group of patients cannot be reconstructed with current approaches that do strongly depend on a high degree of cardiac motion periodicity for working properly. In a last year's MICCAI contribution a first algorithm was presented that is able to estimate non-periodic 4-D motion patterns. However, to some degree that algorithm still depends on periodicity, as it requires a prior image which is obtained using a simple ECG-gated reconstruction. In this work we aim to provide a solution to this problem by developing a motion compensated ECG-gating algorithm. It is built upon a 4-D time-continuous affine motion model which is capable of compactly describing highly non-periodic motion patterns. A stochastic optimization scheme is derived which minimizes the error between the measured projection data and the forward projection of the motion compensated reconstruction. For evaluation, the algorithm is applied to 5 datasets of the left coronary arteries of patients that have ignored the breath hold command and/or had arrhythmic heart signals during the data acquisition. By applying the developed algorithm the average visibility of the vessel segments could be increased by 27%. The results show that the proposed algorithm provides excellent reconstruction quality in cases where classical approaches fail. The algorithm is highly parallelizable and a clinically feasible runtime of under 4 minutes is achieved using modern graphics card hardware.

Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction.

PubMed

Yang, Qi; Zhang, Yanzhu; Zhao, Tiebiao; Chen, YangQuan

2017-04-04

Image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction aims to recover detailed information from low-resolution images and reconstruct them into high-resolution images. Due to the limited amount of data and information retrieved from low-resolution images, it is difficult to restore clear, artifact-free images, while still preserving enough structure of the image such as the texture. This paper presents a new single image super-resolution method which is based on adaptive fractional-order gradient interpolation and reconstruction. The interpolated image gradient via optimal fractional-order gradient is first constructed according to the image similarity and afterwards the minimum energy function is employed to reconstruct the final high-resolution image. Fractional-order gradient based interpolation methods provide an additional degree of freedom which helps optimize the implementation quality due to the fact that an extra free parameter α-order is being used. The proposed method is able to produce a rich texture detail while still being able to maintain structural similarity even under large zoom conditions. Experimental results show that the proposed method performs better than current single image super-resolution techniques. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Experimental study on the 3D image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector and its image characteristics

NASA Astrophysics Data System (ADS)

Hong, Daeki; Cho, Heemoon; Cho, Hyosung; Choi, Sungil; Je, Uikyu; Park, Yeonok; Park, Chulkyu; Lim, Hyunwoo; Park, Soyoung; Woo, Taeho

2015-11-01

In this work, we performed a feasibility study on the three-dimensional (3D) image reconstruction in a truncated Archimedean-like spiral geometry with a long-rectangular detector for application to high-accurate, cost-effective dental x-ray imaging. Here an x-ray tube and a detector rotate together around the rotational axis several times and, concurrently, the detector moves horizontally in the detector coordinate at a constant speed to cover the whole imaging volume during the projection data acquisition. We established a table-top setup which mainly consists of an x-ray tube (60 kVp, 5 mA), a narrow CMOS-type detector (198-μm pixel resolution, 184 (W)×1176 (H) pixel dimension), and a rotational stage for sample mounting and performed a systematic experiment to demonstrate the viability of the proposed approach to volumetric dental imaging. For the image reconstruction, we employed a compressed-sensing (CS)-based algorithm, rather than a common filtered-backprojection (FBP) one, for more accurate reconstruction. We successfully reconstructed 3D images of considerably high quality and investigated the image characteristics in terms of the image value profile, the contrast-to-noise ratio (CNR), and the spatial resolution.

Image quality of mixed convolution kernel in thoracic computed tomography.

PubMed

Neubauer, Jakob; Spira, Eva Maria; Strube, Juliane; Langer, Mathias; Voss, Christian; Kotter, Elmar

2016-11-01

The mixed convolution kernel alters his properties geographically according to the depicted organ structure, especially for the lung. Therefore, we compared the image quality of the mixed convolution kernel to standard soft and hard kernel reconstructions for different organ structures in thoracic computed tomography (CT) images.Our Ethics Committee approved this prospective study. In total, 31 patients who underwent contrast-enhanced thoracic CT studies were included after informed consent. Axial reconstructions were performed with hard, soft, and mixed convolution kernel. Three independent and blinded observers rated the image quality according to the European Guidelines for Quality Criteria of Thoracic CT for 13 organ structures. The observers rated the depiction of the structures in all reconstructions on a 5-point Likert scale. Statistical analysis was performed with the Friedman Test and post hoc analysis with the Wilcoxon rank-sum test.Compared to the soft convolution kernel, the mixed convolution kernel was rated with a higher image quality for lung parenchyma, segmental bronchi, and the border between the pleura and the thoracic wall (P < 0.03). Compared to the hard convolution kernel, the mixed convolution kernel was rated with a higher image quality for aorta, anterior mediastinal structures, paratracheal soft tissue, hilar lymph nodes, esophagus, pleuromediastinal border, large and medium sized pulmonary vessels and abdomen (P < 0.004) but a lower image quality for trachea, segmental bronchi, lung parenchyma, and skeleton (P < 0.001).The mixed convolution kernel cannot fully substitute the standard CT reconstructions. Hard and soft convolution kernel reconstructions still seem to be mandatory for thoracic CT.

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, P; Mao, T; Gong, S

2016-06-15

Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimizationmore » trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).« less

A Large-Scale Comparative Metagenomic Study Reveals the Functional Interactions in Six Bloom-Forming Microcystis-Epibiont Communities

PubMed Central

Li, Qi; Lin, Feibi; Yang, Chen; Wang, Juanping; Lin, Yan; Shen, Mengyuan; Park, Min S.; Li, Tao; Zhao, Jindong

2018-01-01

Cyanobacterial blooms are worldwide issues of societal concern and scientific interest. Lake Taihu and Lake Dianchi, two of the largest lakes in China, have been suffering from annual Microcystis-based blooms over the past two decades. These two eutrophic lakes differ in both nutrient load and environmental parameters, where Microcystis microbiota consisting of different Microcystis morphospecies and associated bacteria (epibionts) have dominated. We conducted a comprehensive metagenomic study that analyzed species diversity, community structure, functional components, metabolic pathways and networks to investigate functional interactions among the members of six Microcystis-epibiont communities in these two lakes. Our integrated metagenomic pipeline consisted of efficient assembly, binning, annotation, and quality assurance methods that ensured high-quality genome reconstruction. This study provides a total of 68 reconstructed genomes including six complete Microcystis genomes and 28 high quality bacterial genomes of epibionts belonging to 14 distinct taxa. This metagenomic dataset constitutes the largest reference genome catalog available for genome-centric studies of the Microcystis microbiome. Epibiont community composition appears to be dynamic rather than fixed, and the functional profiles of communities were related to the environment of origin. This study demonstrates mutualistic interactions between Microcystis and epibionts at genetic and metabolic levels. Metabolic pathway reconstruction provided evidence for functional complementation in nitrogen and sulfur cycles, fatty acid catabolism, vitamin synthesis, and aromatic compound degradation among community members. Thus, bacterial social interactions within Microcystis-epibiont communities not only shape species composition, but also stabilize the communities functional profiles. These interactions appear to play an important role in environmental adaptation of Microcystis colonies. PMID:29731741

The ALICE data quality monitoring system

NASA Astrophysics Data System (ADS)

von Haller, B.; Telesca, A.; Chapeland, S.; Carena, F.; Carena, W.; Chibante Barroso, V.; Costa, F.; Denes, E.; Divià, R.; Fuchs, U.; Simonetti, G.; Soós, C.; Vande Vyvre, P.; ALICE Collaboration

2011-12-01

ALICE (A Large Ion Collider Experiment) is the heavy-ion detector designed to study the physics of strongly interacting matter and the quark-gluon plasma at the CERN Large Hadron Collider (LHC). The online Data Quality Monitoring (DQM) is a key element of the Data Acquisition's software chain. It provide shifters with precise and complete information to quickly identify and overcome problems, and as a consequence to ensure acquisition of high quality data. DQM typically involves the online gathering, the analysis by user-defined algorithms and the visualization of monitored data. This paper describes the final design of ALICE'S DQM framework called AMORE (Automatic MOnitoRing Environment), as well as its latest and coming features like the integration with the offline analysis and reconstruction framework, a better use of multi-core processors by a parallelization effort, and its interface with the eLogBook. The concurrent collection and analysis of data in an online environment requires the framework to be highly efficient, robust and scalable. We will describe what has been implemented to achieve these goals and the procedures we follow to ensure appropriate robustness and performance. We finally review the wide range of usages people make of this framework, from the basic monitoring of a single sub-detector to the most complex ones within the High Level Trigger farm or using the Prompt Reconstruction and we describe the various ways of accessing the monitoring results. We conclude with our experience, before and after the LHC startup, when monitoring the data quality in a challenging environment.

Effect of High-Grade Preoperative Knee Laxity on Anterior Cruciate Ligament Reconstruction Outcomes.

PubMed

Magnussen, Robert A; Reinke, Emily K; Huston, Laura J; Hewett, Timothy E; Spindler, Kurt P

2016-12-01

Knee laxity in the setting of suspected anterior cruciate ligament (ACL) injury is frequently assessed through physical examination using the Lachman, pivot-shift, and anterior drawer tests. The degree of laxity noted on these examinations may influence treatment decisions and prognosis. Increased preoperative knee laxity would be associated with increased risk of subsequent revision ACL reconstruction and worse patient-reported outcomes 2 years postoperatively. Cohort study; Level of evidence, 2. From an ongoing prospective cohort study, 2333 patients who underwent primary isolated ACL reconstruction without collateral or posterior cruciate ligament injury were identified. Patients reported by the operating surgeons as having an International Knee Documentation Committee (IKDC) grade D for Lachman, anterior drawer, or pivot-shift examination were classified as having high-grade laxity. Multiple logistic regression modeling was used to evaluate whether having high-grade preoperative laxity was associated with increased odds of undergoing revision ACL reconstruction within 2 years of the index procedure, controlling for patient age, sex, Marx activity level, level of competition, and graft type. Multiple linear regression modeling was used to evaluate whether having high-grade preoperative laxity was associated with worse IKDC score or Knee injury and Osteoarthritis Outcome Score Knee-Related Quality of Life subscale (KOOS-QOL) scores at a minimum 2 years postoperatively, controlling for baseline score, patient age, ethnicity, sex, body mass index, marital status, smoking status, sport participation, competition level, Marx activity rating score, graft type, and articular cartilage and meniscus status. Pre-reconstruction laxity data were available for 2325 patients (99.7%). Two-year revision data were available for 2259 patients (96.8%), and patient-reported outcomes were available for 1979 patients (84.8%). High-grade preoperative laxity was noted in 743 patients (31.9%). The mean postoperative IKDC score was 81.8 ± 15.9, and the mean KOOS-QOL score was 72.0 ± 22.0. The presence of high-grade pre-reconstruction laxity was associated with significantly increased odds of ACL graft revision (odds ratio [OR] = 1.87 [95% CI, 1.19-2.95]; P = .007). The presence of high-grade pre-reconstruction laxity was not associated with any difference in postoperative IKDC (β = -0.56, P = .44) or KOOS-QOL (β = 0.04, P = .97). The presence of high-grade pre-reconstruction knee laxity as assessed by manual physical examination under anesthesia is associated with significantly increased odds of revision ACL surgery but has no association with patient-reported outcome scores at 2 years after ACL reconstruction. © 2016 The Author(s).

Integrating prior information into microwave tomography Part 1: Impact of detail on image quality.

PubMed

Kurrant, Douglas; Baran, Anastasia; LoVetri, Joe; Fear, Elise

2017-12-01

The authors investigate the impact that incremental increases in the level of detail of patient-specific prior information have on image quality and the convergence behavior of an inversion algorithm in the context of near-field microwave breast imaging. A methodology is presented that uses image quality measures to characterize the ability of the algorithm to reconstruct both internal structures and lesions embedded in fibroglandular tissue. The approach permits key aspects that impact the quality of reconstruction of these structures to be identified and quantified. This provides insight into opportunities to improve image reconstruction performance. Patient-specific information is acquired using radar-based methods that form a regional map of the breast. This map is then incorporated into a microwave tomography algorithm. Previous investigations have demonstrated the effectiveness of this approach to improve image quality when applied to data generated with two-dimensional (2D) numerical models. The present study extends this work by generating prior information that is customized to vary the degree of structural detail to facilitate the investigation of the role of prior information in image formation. Numerical 2D breast models constructed from magnetic resonance (MR) scans, and reconstructions formed with a three-dimensional (3D) numerical breast model are used to assess if trends observed for the 2D results can be extended to 3D scenarios. For the blind reconstruction scenario (i.e., no prior information), the breast surface is not accurately identified and internal structures are not clearly resolved. A substantial improvement in image quality is achieved by incorporating the skin surface map and constraining the imaging domain to the breast. Internal features within the breast appear in the reconstructed image. However, it is challenging to discriminate between adipose and glandular regions and there are inaccuracies in both the structural properties of the glandular region and the dielectric properties reconstructed within this structure. Using a regional map with a skin layer only marginally improves this situation. Increasing the structural detail in the prior information to include internal features leads to reconstructions for which the interface that delineates the fat and gland regions can be inferred. Different features within the glandular region corresponding to tissues with varying relative permittivity values, such as a lesion embedded within glandular structure, emerge in the reconstructed images. Including knowledge of the breast surface and skin layer leads to a substantial improvement in image quality compared to the blind case, but the images have limited diagnostic utility for applications such as tumor response tracking. The diagnostic utility of the reconstruction technique is improved considerably when patient-specific structural information is used. This qualitative observation is supported quantitatively with image metrics. © 2017 American Association of Physicists in Medicine.

Joint Chroma Subsampling and Distortion-Minimization-Based Luma Modification for RGB Color Images With Application.

PubMed

Chung, Kuo-Liang; Hsu, Tsu-Chun; Huang, Chi-Chao

2017-10-01

In this paper, we propose a novel and effective hybrid method, which joins the conventional chroma subsampling and the distortion-minimization-based luma modification together, to improve the quality of the reconstructed RGB full-color image. Assume the input RGB full-color image has been transformed to a YUV image, prior to compression. For each 2×2 UV block, one 4:2:0 subsampling is applied to determine the one subsampled U and V components, U s and V s . Based on U s , V s , and the corresponding 2×2 original RGB block, a main theorem is provided to determine the ideally modified 2×2 luma block in constant time such that the color peak signal-to-noise ratio (CPSNR) quality distortion between the original 2×2 RGB block and the reconstructed 2×2 RGB block can be minimized in a globally optimal sense. Furthermore, the proposed hybrid method and the delivered theorem are adjusted to tackle the digital time delay integration images and the Bayer mosaic images whose Bayer CFA structure has been widely used in modern commercial digital cameras. Based on the IMAX, Kodak, and screen content test image sets, the experimental results demonstrate that in high efficiency video coding, the proposed hybrid method has substantial quality improvement, in terms of the CPSNR quality, visual effect, CPSNR-bitrate trade-off, and Bjøntegaard delta PSNR performance, of the reconstructed RGB images when compared with existing chroma subsampling schemes.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

Compared to 3D cone beam computed tomography (3D CBCT), the image quality of commercially available four-dimensional (4D) CBCT is severely impaired due to the insufficient amount of projection data available for each phase. Since the traditional Feldkamp-Davis-Kress (FDK)-based algorithm is infeasible for reconstructing high quality 4D CBCT images with limited projections, investigators had developed several compress-sensing (CS) based algorithms to improve image quality. The aim of this study is to develop a novel algorithm which can provide better image quality than the FDK and other CS based algorithms with limited projections. We named this algorithm ‘the common mask guided image reconstruction’ (c-MGIR). In c-MGIR, the unknown CBCT volume is mathematically modeled as a combination of phase-specific motion vectors and phase-independent static vectors. The common-mask matrix, which is the key concept behind the c-MGIR algorithm, separates the common static part across all phase images from the possible moving part in each phase image. The moving part and the static part of the volumes were then alternatively updated by solving two sub-minimization problems iteratively. As the novel mathematical transformation allows the static volume and moving volumes to be updated (during each iteration) with global projections and ‘well’ solved static volume respectively, the algorithm was able to reduce the noise and under-sampling artifact (an issue faced by other algorithms) to the maximum extent. To evaluate the performance of our proposed c-MGIR, we utilized imaging data from both numerical phantoms and a lung cancer patient. The qualities of the images reconstructed with c-MGIR were compared with (1) standard FDK algorithm, (2) conventional total variation (CTV) based algorithm, (3) prior image constrained compressed sensing (PICCS) algorithm, and (4) motion-map constrained image reconstruction (MCIR) algorithm, respectively. To improve the efficiency of the algorithm, the code was implemented with a graphic processing unit for parallel processing purposes. Root mean square error (RMSE) between the ground truth and reconstructed volumes of the numerical phantom were in the descending order of FDK, CTV, PICCS, MCIR, and c-MGIR for all phases. Specifically, the means and the standard deviations of the RMSE of FDK, CTV, PICCS, MCIR and c-MGIR for all phases were 42.64  ±  6.5%, 3.63  ±  0.83%, 1.31%  ±  0.09%, 0.86%  ±  0.11% and 0.52 %  ±  0.02%, respectively. The image quality of the patient case also indicated the superiority of c-MGIR compared to other algorithms. The results indicated that clinically viable 4D CBCT images can be reconstructed while requiring no more projection data than a typical clinical 3D CBCT scan. This makes c-MGIR a potential online reconstruction algorithm for 4D CBCT, which can provide much better image quality than other available algorithms, while requiring less dose and potentially less scanning time.

SU-F-I-49: Vendor-Independent, Model-Based Iterative Reconstruction On a Rotating Grid with Coordinate-Descent Optimization for CT Imaging Investigations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, S; Hoffman, J; McNitt-Gray, M

Purpose: Iterative reconstruction methods show promise for improving image quality and lowering the dose in helical CT. We aim to develop a novel model-based reconstruction method that offers potential for dose reduction with reasonable computation speed and storage requirements for vendor-independent reconstruction from clinical data on a normal desktop computer. Methods: In 2012, Xu proposed reconstructing on rotating slices to exploit helical symmetry and reduce the storage requirements for the CT system matrix. Inspired by this concept, we have developed a novel reconstruction method incorporating the stored-system-matrix approach together with iterative coordinate-descent (ICD) optimization. A penalized-least-squares objective function with amore » quadratic penalty term is solved analytically voxel-by-voxel, sequentially iterating along the axial direction first, followed by the transaxial direction. 8 in-plane (transaxial) neighbors are used for the ICD algorithm. The forward problem is modeled via a unique approach that combines the principle of Joseph’s method with trilinear B-spline interpolation to enable accurate reconstruction with low storage requirements. Iterations are accelerated with multi-CPU OpenMP libraries. For preliminary evaluations, we reconstructed (1) a simulated 3D ellipse phantom and (2) an ACR accreditation phantom dataset exported from a clinical scanner (Definition AS, Siemens Healthcare). Image quality was evaluated in the resolution module. Results: Image quality was excellent for the ellipse phantom. For the ACR phantom, image quality was comparable to clinical reconstructions and reconstructions using open-source FreeCT-wFBP software. Also, we did not observe any deleterious impact associated with the utilization of rotating slices. The system matrix storage requirement was only 4.5GB, and reconstruction time was 50 seconds per iteration. Conclusion: Our reconstruction method shows potential for furthering research in low-dose helical CT, in particular as part of our ongoing development of an acquisition/reconstruction pipeline for generating images under a wide range of conditions. Our algorithm will be made available open-source as “FreeCT-ICD”. NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less

Image quality comparison of two adaptive statistical iterative reconstruction (ASiR, ASiR-V) algorithms and filtered back projection in routine liver CT.

PubMed

Chen, Li-Hong; Jin, Chao; Li, Jian-Ying; Wang, Ge-Liang; Jia, Yong-Jun; Duan, Hai-Feng; Pan, Ning; Guo, Jianxin

2018-06-06

To compare image quality of two adaptive statistical iterative reconstruction (ASiR and ASiR-V) algorithms using objective and subjective metrics for routine liver CT, with the conventional filtered back projection (FBP) reconstructions as reference standards. This institutional review board-approved study included 52 patients with clinically suspected hepatic metastases. Patients were divided equally into ASiR and ASiR-V groups with same scan parameters. Images were reconstructed with ASiR and ASiR-V from 0 (FBP) to 100% blending percentages at 10% interval in its respective group. Mean and standard deviation of CT numbers for liver parenchyma were recorded. Two experienced radiologists reviewed all images for image quality blindly and independently. Data were statistically analyzed. There was no difference in CT dose index between ASiR and ASiR-V groups. As the percentage of ASiR and ASiR-V increased from 10 to 100% , image noise reduced by 8.6 -57.9% and 8.9-81.6%, respectively, compared with FBP. There was substantial interobserver agreement in image quality assessment for ASiR and ASiR-V images. Compared with FBP reconstruction, subjective image quality scores of ASiR and ASiR-V improved significantly as percentage increased from 10 to 80% for ASiR (peaked at 50% with 32.2% noise reduction) and from 10 to 90% (peaked at 60% with 51.5% noise reduction) for ASiR-V. Both ASiR and ASiR-V improved the objective and subjective image quality for routine liver CT compared with FBP. ASiR-V provided further image quality improvement with higher acceptable percentage than ASiR, and ASiR-V60% had the highest image quality score. Advances in knowledge: (1) Both ASiR and ASiR-V significantly reduce image noise compared with conventional FBP reconstruction. (2) ASiR-V with 60 blending percentage provides the highest image quality score in routine liver CT.

An image compression algorithm for a high-resolution digital still camera

NASA Technical Reports Server (NTRS)

Nerheim, Rosalee

1989-01-01

The Electronic Still Camera (ESC) project will provide for the capture and transmission of high-quality images without the use of film. The image quality will be superior to video and will approach the quality of 35mm film. The camera, which will have the same general shape and handling as a 35mm camera, will be able to send images to earth in near real-time. Images will be stored in computer memory (RAM) in removable cartridges readable by a computer. To save storage space, the image will be compressed and reconstructed at the time of viewing. Both lossless and loss-y image compression algorithms are studied, described, and compared.

Video Capture of Plastic Surgery Procedures Using the GoPro HERO 3+.

PubMed

Graves, Steven Nicholas; Shenaq, Deana Saleh; Langerman, Alexander J; Song, David H

2015-02-01

Significant improvements can be made in recoding surgical procedures, particularly in capturing high-quality video recordings from the surgeons' point of view. This study examined the utility of the GoPro HERO 3+ Black Edition camera for high-definition, point-of-view recordings of plastic and reconstructive surgery. The GoPro HERO 3+ Black Edition camera was head-mounted on the surgeon and oriented to the surgeon's perspective using the GoPro App. The camera was used to record 4 cases: 2 fat graft procedures and 2 breast reconstructions. During cases 1-3, an assistant remotely controlled the GoPro via the GoPro App. For case 4 the GoPro was linked to a WiFi remote, and controlled by the surgeon. Camera settings for case 1 were as follows: 1080p video resolution; 48 fps; Protune mode on; wide field of view; 16:9 aspect ratio. The lighting contrast due to the overhead lights resulted in limited washout of the video image. Camera settings were adjusted for cases 2-4 to a narrow field of view, which enabled the camera's automatic white balance to better compensate for bright lights focused on the surgical field. Cases 2-4 captured video sufficient for teaching or presentation purposes. The GoPro HERO 3+ Black Edition camera enables high-quality, cost-effective video recording of plastic and reconstructive surgery procedures. When set to a narrow field of view and automatic white balance, the camera is able to sufficiently compensate for the contrasting light environment of the operating room and capture high-resolution, detailed video.

High quality 3D shape reconstruction via digital refocusing and pupil apodization in multi-wavelength holographic interferometry

NASA Astrophysics Data System (ADS)

Xu, Li

Multi-wavelength holographic interferometry (MWHI) has good potential for evolving into a high quality 3D shape reconstruction technique. There are several remaining challenges, including I) depth-of-field limitation, leading to axial dimension inaccuracy of out-of-focus objects; and 2) smearing from shiny smooth objects to their dark dull neighbors, generating fake measurements within the dark area. This research is motivated by the goal of developing an advanced optical metrology system that provides accurate 3D profiles for target object or objects of axial dimension larger than the depth-of-field, and for objects with dramatically different surface conditions. The idea of employing digital refocusing in MWHI has been proposed as a solution to the depth-of-field limitation. One the one hand, traditional single wavelength refocusing formula is revised to reduce sensitivity to wavelength error. Investigation over real example demonstrates promising accuracy and repeatability of reconstructed 3D profiles. On the other hand, a phase contrast based focus detection criterion is developed especially for MWHI, which overcomes the problem of phase unwrapping. The combination for these two innovations gives birth to a systematic strategy of acquiring high quality 3D profiles. Following the first phase contrast based focus detection step, interferometric distance measurement by MWHI is implemented as a next step to conduct relative focus detection with high accuracy. This strategy results in +/-100mm 3D profile with micron level axial accuracy, which is not available in traditional extended focus image (EFI) solutions. Pupil apodization has been implemented to address the second challenge of smearing. The process of reflective rough surface inspection has been mathematically modeled, which explains the origin of stray light and the necessity of replacing hard-edged pupil with one of gradually attenuating transmission (apodization). Metrics to optimize pupil types and parameters have been chosen especially for MWHI. A Gaussian apodized pupil has been installed and tested. A reduction of smearing in measurement result has been experimentally demonstrated.

{sup 90}Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carlier, Thomas, E-mail: thomas.carlier@chu-nantes.fr; Willowson, Kathy P.; Fourkal, Eugene

Purpose: {sup 90}Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with {sup 90}Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging {sup 90}Y and to compare experimental results with clinical data from two types of commercially available {sup 90}Y microspheres. Methods: Data were acquired on both Siemens Biograph TruePointmore » [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of {sup 90}Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a {sup 90}Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere{sup ®} and 24 with SIR-Spheres{sup ®}) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. Results: The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely high random fraction and low counts for iterative algorithms. Point spread function (PSF) correction and TOF reconstruction in general reduce background variability and noise and increase recovered concentration. Results for patient data indicated a good correlation between the expected and PET reconstructed activities. A linear relationship between the expected and the measured activities in the organ of interest was observed for all reconstruction method used: a linearity coefficient of 0.89 ± 0.05 for the Biograph mCT and 0.81 ± 0.05 for the Biograph TruePoint. Conclusions: Due to the low counts and high random fraction, accurate image quantification of {sup 90}Y during selective internal radionuclide therapy is affected by random coincidence estimation, scatter correction, and any positivity constraint of the algorithm. Nevertheless, phantom and patient studies showed that the impact of number of true and random coincidences on quantitative results was found to be limited as long as ordinary Poisson ordered subsets expectation maximization reconstruction algorithms with random smoothing are used. Adding PSF correction and TOF information to the reconstruction greatly improves the image quality in terms of bias, variability, noise reduction, and detectability. On the patient studies, the total activity in the field of view is in general accurately measured by Biograph mCT and slightly overestimated by the Biograph TruePoint.« less

Digital tomosynthesis (DTS) with a Circular X-ray tube: Its image reconstruction based on total-variation minimization and the image characteristics

NASA Astrophysics Data System (ADS)

Park, Y. O.; Hong, D. K.; Cho, H. S.; Je, U. K.; Oh, J. E.; Lee, M. S.; Kim, H. J.; Lee, S. H.; Jang, W. S.; Cho, H. M.; Choi, S. I.; Koo, Y. S.

2013-09-01

In this paper, we introduce an effective imaging system for digital tomosynthesis (DTS) with a circular X-ray tube, the so-called circular-DTS (CDTS) system, and its image reconstruction algorithm based on the total-variation (TV) minimization method for low-dose, high-accuracy X-ray imaging. Here, the X-ray tube is equipped with a series of cathodes distributed around a rotating anode, and the detector remains stationary throughout the image acquisition. We considered a TV-based reconstruction algorithm that exploited the sparsity of the image with substantially high image accuracy. We implemented the algorithm for the CDTS geometry and successfully reconstructed images of high accuracy. The image characteristics were investigated quantitatively by using some figures of merit, including the universal-quality index (UQI) and the depth resolution. For selected tomographic angles of 20, 40, and 60°, the corresponding UQI values in the tomographic view were estimated to be about 0.94, 0.97, and 0.98, and the depth resolutions were about 4.6, 3.1, and 1.2 voxels in full width at half maximum (FWHM), respectively. We expect the proposed method to be applicable to developing a next-generation dental or breast X-ray imaging system.

Iterative Reconstruction Techniques in Abdominopelvic CT: Technical Concepts and Clinical Implementation.

PubMed

Patino, Manuel; Fuentes, Jorge M; Singh, Sarabjeet; Hahn, Peter F; Sahani, Dushyant V

2015-07-01

This article discusses the clinical challenge of low-radiation-dose examinations, the commonly used approaches for dose optimization, and their effect on image quality. We emphasize practical aspects of the different iterative reconstruction techniques, along with their benefits, pitfalls, and clinical implementation. The widespread use of CT has raised concerns about potential radiation risks, motivating diverse strategies to reduce the radiation dose associated with CT. CT manufacturers have developed alternative reconstruction algorithms intended to improve image quality on dose-optimized CT studies, mainly through noise and artifact reduction. Iterative reconstruction techniques take unique approaches to noise reduction and provide distinct strength levels or settings.

Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

NASA Astrophysics Data System (ADS)

Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.

2017-10-01

In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists’ information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

Effects of illumination differences on photometric stereo shape-and-albedo-from-shading for precision lunar surface reconstruction

NASA Astrophysics Data System (ADS)

Chung Liu, Wai; Wu, Bo; Wöhler, Christian

2018-02-01

Photoclinometric surface reconstruction techniques such as Shape-from-Shading (SfS) and Shape-and-Albedo-from-Shading (SAfS) retrieve topographic information of a surface on the basis of the reflectance information embedded in the image intensity of each pixel. SfS or SAfS techniques have been utilized to generate pixel-resolution digital elevation models (DEMs) of the Moon and other planetary bodies. Photometric stereo SAfS analyzes images under multiple illumination conditions to improve the robustness of reconstruction. In this case, the directional difference in illumination between the images is likely to affect the quality of the reconstruction result. In this study, we quantitatively investigate the effects of illumination differences on photometric stereo SAfS. Firstly, an algorithm for photometric stereo SAfS is developed, and then, an error model is derived to analyze the relationships between the azimuthal and zenith angles of illumination of the images and the reconstruction qualities. The developed algorithm and error model were verified with high-resolution images collected by the Narrow Angle Camera (NAC) of the Lunar Reconnaissance Orbiter Camera (LROC). Experimental analyses reveal that (1) the resulting error in photometric stereo SAfS depends on both the azimuthal and the zenith angles of illumination as well as the general intensity of the images and (2) the predictions from the proposed error model are consistent with the actual slope errors obtained by photometric stereo SAfS using the LROC NAC images. The proposed error model enriches the theory of photometric stereo SAfS and is of significance for optimized lunar surface reconstruction based on SAfS techniques.

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

NASA Astrophysics Data System (ADS)

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.

Entropy-aware projected Landweber reconstruction for quantized block compressive sensing of aerial imagery

NASA Astrophysics Data System (ADS)

Liu, Hao; Li, Kangda; Wang, Bing; Tang, Hainie; Gong, Xiaohui

2017-01-01

A quantized block compressive sensing (QBCS) framework, which incorporates the universal measurement, quantization/inverse quantization, entropy coder/decoder, and iterative projected Landweber reconstruction, is summarized. Under the QBCS framework, this paper presents an improved reconstruction algorithm for aerial imagery, QBCS, with entropy-aware projected Landweber (QBCS-EPL), which leverages the full-image sparse transform without Wiener filter and an entropy-aware thresholding model for wavelet-domain image denoising. Through analyzing the functional relation between the soft-thresholding factors and entropy-based bitrates for different quantization methods, the proposed model can effectively remove wavelet-domain noise of bivariate shrinkage and achieve better image reconstruction quality. For the overall performance of QBCS reconstruction, experimental results demonstrate that the proposed QBCS-EPL algorithm significantly outperforms several existing algorithms. With the experiment-driven methodology, the QBCS-EPL algorithm can obtain better reconstruction quality at a relatively moderate computational cost, which makes it more desirable for aerial imagery applications.

A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

NASA Astrophysics Data System (ADS)

Wu, Wei; Zhao, Dewei; Zhang, Huan

2015-12-01

Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

Healing and Building Soil on Prairie Birthday Farm

USDA-ARS?s Scientific Manuscript database

Native tallgrass prairie was restored as an integral part of a small, food-producing farm called Prairie Birthday Farm in Clay County, Missouri. Reconstruction of native prairie was essential to the farm’s goal of producing high quality food for the family, area residents and restaurant chefs. Impro...

Progressive low-bitrate digital color/monochrome image coding by neuro-fuzzy clustering

NASA Astrophysics Data System (ADS)

Mitra, Sunanda; Meadows, Steven

1997-10-01

Color image coding at low bit rates is an area of research that is just being addressed in recent literature since the problems of storage and transmission of color images are becoming more prominent in many applications. Current trends in image coding exploit the advantage of subband/wavelet decompositions in reducing the complexity in optimal scalar/vector quantizer (SQ/VQ) design. Compression ratios (CRs) of the order of 10:1 to 20:1 with high visual quality have been achieved by using vector quantization of subband decomposed color images in perceptually weighted color spaces. We report the performance of a recently developed adaptive vector quantizer, namely, AFLC-VQ for effective reduction in bit rates while maintaining high visual quality of reconstructed color as well as monochrome images. For 24 bit color images, excellent visual quality is maintained upto a bit rate reduction to approximately 0.48 bpp (for each color plane or monochrome 0.16 bpp, CR 50:1) by using the RGB color space. Further tuning of the AFLC-VQ, and addition of an entropy coder module after the VQ stage results in extremely low bit rates (CR 80:1) for good quality, reconstructed images. Our recent study also reveals that for similar visual quality, RGB color space requires less bits/pixel than either the YIQ, or HIS color space for storing the same information when entropy coding is applied. AFLC-VQ outperforms other standard VQ and adaptive SQ techniques in retaining visual fidelity at similar bit rate reduction.

A maximum entropy reconstruction technique for tomographic particle image velocimetry

NASA Astrophysics Data System (ADS)

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.

Dynamic magnetic resonance imaging method based on golden-ratio cartesian sampling and compressed sensing.

PubMed

Li, Shuo; Zhu, Yanchun; Xie, Yaoqin; Gao, Song

2018-01-01

Dynamic magnetic resonance imaging (DMRI) is used to noninvasively trace the movements of organs and the process of drug delivery. The results can provide quantitative or semiquantitative pathology-related parameters, thus giving DMRI great potential for clinical applications. However, conventional DMRI techniques suffer from low temporal resolution and long scan time owing to the limitations of the k-space sampling scheme and image reconstruction algorithm. In this paper, we propose a novel DMRI sampling scheme based on a golden-ratio Cartesian trajectory in combination with a compressed sensing reconstruction algorithm. The results of two simulation experiments, designed according to the two major DMRI techniques, showed that the proposed method can improve the temporal resolution and shorten the scan time and provide high-quality reconstructed images.

Modelling the physics in iterative reconstruction for transmission computed tomography

PubMed Central

Nuyts, Johan; De Man, Bruno; Fessler, Jeffrey A.; Zbijewski, Wojciech; Beekman, Freek J.

2013-01-01

There is an increasing interest in iterative reconstruction (IR) as a key tool to improve quality and increase applicability of X-ray CT imaging. IR has the ability to significantly reduce patient dose, it provides the flexibility to reconstruct images from arbitrary X-ray system geometries and it allows to include detailed models of photon transport and detection physics, to accurately correct for a wide variety of image degrading effects. This paper reviews discretisation issues and modelling of finite spatial resolution, Compton scatter in the scanned object, data noise and the energy spectrum. Widespread implementation of IR with highly accurate model-based correction, however, still requires significant effort. In addition, new hardware will provide new opportunities and challenges to improve CT with new modelling. PMID:23739261

Optimizing and evaluating the reconstruction of Metagenome-assembled microbial genomes.

PubMed

Papudeshi, Bhavya; Haggerty, J Matthew; Doane, Michael; Morris, Megan M; Walsh, Kevin; Beattie, Douglas T; Pande, Dnyanada; Zaeri, Parisa; Silva, Genivaldo G Z; Thompson, Fabiano; Edwards, Robert A; Dinsdale, Elizabeth A

2017-11-28

Microbiome/host interactions describe characteristics that affect the host's health. Shotgun metagenomics includes sequencing a random subset of the microbiome to analyze its taxonomic and metabolic potential. Reconstruction of DNA fragments into genomes from metagenomes (called metagenome-assembled genomes) assigns unknown fragments to taxa/function and facilitates discovery of novel organisms. Genome reconstruction incorporates sequence assembly and sorting of assembled sequences into bins, characteristic of a genome. However, the microbial community composition, including taxonomic and phylogenetic diversity may influence genome reconstruction. We determine the optimal reconstruction method for four microbiome projects that had variable sequencing platforms (IonTorrent and Illumina), diversity (high or low), and environment (coral reefs and kelp forests), using a set of parameters to select for optimal assembly and binning tools. We tested the effects of the assembly and binning processes on population genome reconstruction using 105 marine metagenomes from 4 projects. Reconstructed genomes were obtained from each project using 3 assemblers (IDBA, MetaVelvet, and SPAdes) and 2 binning tools (GroopM and MetaBat). We assessed the efficiency of assemblers using statistics that including contig continuity and contig chimerism and the effectiveness of binning tools using genome completeness and taxonomic identification. We concluded that SPAdes, assembled more contigs (143,718 ± 124 contigs) of longer length (N50 = 1632 ± 108 bp), and incorporated the most sequences (sequences-assembled = 19.65%). The microbial richness and evenness were maintained across the assembly, suggesting low contig chimeras. SPAdes assembly was responsive to the biological and technological variations within the project, compared with other assemblers. Among binning tools, we conclude that MetaBat produced bins with less variation in GC content (average standard deviation: 1.49), low species richness (4.91 ± 0.66), and higher genome completeness (40.92 ± 1.75) across all projects. MetaBat extracted 115 bins from the 4 projects of which 66 bins were identified as reconstructed metagenome-assembled genomes with sequences belonging to a specific genus. We identified 13 novel genomes, some of which were 100% complete, but show low similarity to genomes within databases. In conclusion, we present a set of biologically relevant parameters for evaluation to select for optimal assembly and binning tools. For the tools we tested, SPAdes assembler and MetaBat binning tools reconstructed quality metagenome-assembled genomes for the four projects. We also conclude that metagenomes from microbial communities that have high coverage of phylogenetically distinct, and low taxonomic diversity results in highest quality metagenome-assembled genomes.

Association Between Hospital Financial Distress and Immediate Breast Reconstruction Surgery After Mastectomy Among Women With Ductal Carcinoma In Situ.

PubMed

Richards, Catherine A; Rundle, Andrew G; Wright, Jason D; Hershman, Dawn L

2018-04-01

Hospital financial distress (HFD) is a state in which a hospital is at risk of closure because of its financial condition. Hospital financial distress may reduce the services a hospital can offer, particularly unprofitable ones. Few studies have assessed the association of HFD with quality of care. To examine the association between HFD and receipt of immediate breast reconstruction surgery after mastectomy among women diagnosed with ductal carcinoma in situ (DCIS). This retrospective cohort study assessed data from the Nationwide Inpatient Sample of 5760 women older than 18 years (mean [SD] age: 57.5 [13.2]) with DCIS who underwent mastectomy in 2008-2012 at hospitals categorized by financial distress. Women treated at 1156 hospitals located in 538 different counties across Arkansas, Arizona, California, Colorado, Connecticut, Florida, Iowa, Kentucky, Massachusetts, Maryland, Missouri, North Carolina, New Hampshire, New Jersey, Nevada, New York, Oregon, Pennsylvania, Rhode Island, Utah, Virginia, Vermont, Washington, Wisconsin, West Virginia, and Wyoming were included. Of these, 2385 women (41.4%) underwent immediate breast reconstruction surgery. Women with invasive cancer were excluded. The database included unique hospital identification variables, and participants were identified using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Data were analyzed from January 1, 2012, to February 28, 2014. The primary outcome was the adjusted association between HFD and receipt of immediate breast reconstruction surgery after mastectomy. In this analysis of database information, 2385 of 5760 women (41.4%) received immediate breast reconstruction surgery. Of these, 693 (36.7%) were treated at a hospital under high HFD and received immediate breast reconstruction surgery compared with 863 (44.0%) treated at a hospital under low HFD (P < .001). Reconstruction surgery was associated with younger age, white race, private insurance, treatment at a teaching and cancer hospital, private hospital ownership, and the percentage of individuals in the county with insurance. After adjustment, women treated at hospitals under high HFD (OR, 0.79; 95% CI, 0.62-0.99) and medium HFD (OR, 0.76; 95% CI, 0.61-0.94) were significantly less likely to receive reconstruction than women treated at hospitals with low to no HFD. The financial strength of the hospital where a patient receives treatment is associated with receipt of immediate breast reconstruction surgery. In addition to focusing on patient-related factors, efforts to improve quality should also focus on hospital-related factors.

Personality Traits and Decision on Breast Reconstruction in Women after Mastectomy.

PubMed

Miśkiewicz, Halina; Antoszewski, Bogusław; Iljin, Aleksandra

2016-09-01

The aim of the study was evaluation of the correlation between selected personality traits in women after mastectomy and their decision on breast reconstruction. The study was conducted between 2013‑2015, in the Department of Plastic, Reconstructive and Aesthetic Surgery, Medical University of Lodz, and Department of Oncological and Breast Surgery, CZMP. Comparative analysis comprised 40 patients, in whom mastectomy and breast reconstruction was done, and 40 women after breast amputation, who did not undergo reconstructive surgery. Basing on self-constructed questionnaire, five features of personality were evaluated in these women: pursue of success in life, ability to motivate others, openness to other people, impact of belonging to a social group on sense of security and the importance of opinion of others about the respondent. Apart from the questionnaire, in both groups of women a psychologic tool was used (SUPIN S30 and C30 tests) to determine the intensity of positive and negative emotions. Women who did not choose the reconstructive option were statistically significantly older at mastectomy than women who underwent breast reconstruction. There were statistically significant differences between both groups in response to question on being open to other people and value of other people's opinion. The differences in responses to question on the impact of belonging to a social group on personal sense of safety were hardly statistically significant. In psychometric studies there were significant differences in responses to SUPIN C30 test for negative emotions and S-30 for positive emotions. The level of negative emotions - feature of group A was in 47.5% in the range of high scores and in 47.5% within low and low-average scores. Among women from group B 57.5% had high scores, while 37.5% low and average scores. There were significant differences in the results of positive emotions evaluation in S-30. Women who did not undergo breast reconstruction usually had high scores, while those who decided on reconstructive surgery usually had low scores and low-high scores. 1. The decision on breast reconstruction after mastectomy is connected with personality features of patients. Introvert women, who base their self-opinion on opinion of others and their sense of security on belonging to a social group, rarely choose to undergo breast reconstruction. 2. Younger patients after mastectomy more frequently choose the breast reconstructive option. 3. A special algorithm of medical and psychological care in patients after mastectomy should be created to improve their further quality of life.

Reconstruction of piano hammer force from string velocity.

PubMed

Chaigne, Antoine

2016-11-01

A method is presented for reconstructing piano hammer forces through appropriate filtering of the measured string velocity. The filter design is based on the analysis of the pulses generated by the hammer blow and propagating along the string. In the five lowest octaves, the hammer force is reconstructed by considering two waves only: the incoming wave from the hammer and its first reflection at the front end. For the higher notes, four- or eight-wave schemes must be considered. The theory is validated on simulated string velocities by comparing imposed and reconstructed forces. The simulations are based on a nonlinear damped stiff string model previously developed by Chabassier, Chaigne, and Joly [J. Acoust. Soc. Am. 134(1), 648-665 (2013)]. The influence of absorption, dispersion, and amplitude of the string waves on the quality of the reconstruction is discussed. Finally, the method is applied to real piano strings. The measured string velocity is compared to the simulated velocity excited by the reconstructed force, showing a high degree of accuracy. A number of simulations are compared to simulated strings excited by a force derived from measurements of mass and acceleration of the hammer head. One application to an historic piano is also presented.

BPF-type region-of-interest reconstruction for parallel translational computed tomography.

PubMed

Wu, Weiwen; Yu, Hengyong; Wang, Shaoyu; Liu, Fenglin

2017-01-01

The objective of this study is to present and test a new ultra-low-cost linear scan based tomography architecture. Similar to linear tomosynthesis, the source and detector are translated in opposite directions and the data acquisition system targets on a region-of-interest (ROI) to acquire data for image reconstruction. This kind of tomographic architecture was named parallel translational computed tomography (PTCT). In previous studies, filtered backprojection (FBP)-type algorithms were developed to reconstruct images from PTCT. However, the reconstructed ROI images from truncated projections have severe truncation artefact. In order to overcome this limitation, we in this study proposed two backprojection filtering (BPF)-type algorithms named MP-BPF and MZ-BPF to reconstruct ROI images from truncated PTCT data. A weight function is constructed to deal with data redundancy for multi-linear translations modes. Extensive numerical simulations are performed to evaluate the proposed MP-BPF and MZ-BPF algorithms for PTCT in fan-beam geometry. Qualitative and quantitative results demonstrate that the proposed BPF-type algorithms cannot only more accurately reconstruct ROI images from truncated projections but also generate high-quality images for the entire image support in some circumstances.

3D reconstruction based on compressed-sensing (CS)-based framework by using a dental panoramic detector.

PubMed

Je, U K; Cho, H M; Hong, D K; Cho, H S; Park, Y O; Park, C K; Kim, K S; Lim, H W; Kim, G A; Park, S Y; Woo, T H; Cho, S I

2016-01-01

In this work, we propose a practical method that can combine the two functionalities of dental panoramic and cone-beam CT (CBCT) features in one by using a single panoramic detector. We implemented a CS-based reconstruction algorithm for the proposed method and performed a systematic simulation to demonstrate its viability for 3D dental X-ray imaging. We successfully reconstructed volumetric images of considerably high accuracy by using a panoramic detector having an active area of 198.4 mm × 6.4 mm and evaluated the reconstruction quality as a function of the pitch (p) and the angle step (Δθ). Our simulation results indicate that the CS-based reconstruction almost completely recovered the phantom structures, as in CBCT, for p≤2.0 and θ≤6°, indicating that it seems very promising for accurate image reconstruction even for large-pitch and few-view data. We expect the proposed method to be applicable to developing a cost-effective, volumetric dental X-ray imaging system. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Novel Fourier-based iterative reconstruction for sparse fan projection using alternating direction total variation minimization

NASA Astrophysics Data System (ADS)

Zhao, Jin; Han-Ming, Zhang; Bin, Yan; Lei, Li; Lin-Yuan, Wang; Ai-Long, Cai

2016-03-01

Sparse-view x-ray computed tomography (CT) imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform (NUFFT) is presented in this work along with advanced total variation (TV) regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively. Projected supported by the National High Technology Research and Development Program of China (Grant No. 2012AA011603) and the National Natural Science Foundation of China (Grant No. 61372172).

Tomographic iterative reconstruction of a passive scalar in a 3D turbulent flow

NASA Astrophysics Data System (ADS)

Pisso, Ignacio; Kylling, Arve; Cassiani, Massimo; Solveig Dinger, Anne; Stebel, Kerstin; Schmidbauer, Norbert; Stohl, Andreas

2017-04-01

Turbulence in stable planetary boundary layers often encountered in high latitudes influences the exchange fluxes of heat, momentum, water vapor and greenhouse gases between the Earth's surface and the atmosphere. In climate and meteorological models, such effects of turbulence need to be parameterized, ultimately based on experimental data. A novel experimental approach is being developed within the COMTESSA project in order to study turbulence statistics at high resolution. Using controlled tracer releases, high-resolution camera images and estimates of the background radiation, different tomographic algorithms can be applied in order to obtain time series of 3D representations of the scalar dispersion. In this preliminary work, using synthetic data, we investigate different reconstruction algorithms with emphasis on algebraic methods. We study the dependence of the reconstruction quality on the discretization resolution and the geometry of the experimental device in both 2 and 3-D cases. We assess the computational aspects of the iterative algorithms focusing of the phenomenon of semi-convergence applying a variety of stopping rules. We discuss different strategies for error reduction and regularization of the ill-posed problem.

A method for brain 3D surface reconstruction from MR images

NASA Astrophysics Data System (ADS)

Zhao, De-xin

2014-09-01

Due to the encephalic tissues are highly irregular, three-dimensional (3D) modeling of brain always leads to complicated computing. In this paper, we explore an efficient method for brain surface reconstruction from magnetic resonance (MR) images of head, which is helpful to surgery planning and tumor localization. A heuristic algorithm is proposed for surface triangle mesh generation with preserved features, and the diagonal length is regarded as the heuristic information to optimize the shape of triangle. The experimental results show that our approach not only reduces the computational complexity, but also completes 3D visualization with good quality.

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

PubMed

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 < 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. • Model-Based 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.

Quality of life among patients after bilateral prophylactic mastectomy: a systematic review of patient-reported outcomes.

PubMed

Razdan, Shantanu N; Patel, Vishal; Jewell, Sarah; McCarthy, Colleen M

2016-06-01

Bilateral prophylactic mastectomy (BPM) is effective in reducing the risk of breast cancer in women with a well-defined family history of breast cancer or in women with BRCA 1 or 2 mutations. Evaluating patient-reported outcomes following BPM are thus essential for evaluating success of BPM from patient's perspective. Our systematic review aimed to: (1) identify studies describing health-related quality of life (HRQOL) in patients following BPM with or without reconstruction; (2) assess the effect of BPM with or without reconstruction on HRQOL; and (3) identify predictors of HRQOL post-BPM. We performed a systematic review of literature using the PRISMA guidelines. PubMed, Embase, PsycINFO, Web of Science, Scopus and Cochrane databases were searched. The initial search resulted in 1082 studies; 22 of these studies fulfilled our inclusion criteria. Post-BPM, patients are satisfied with the outcomes and report high psychosocial well-being and positive body image. Sexual well-being and somatosensory function are most negatively affected. Vulnerability, psychological distress and preoperative cancer distress are significant negative predictors of quality of life and body image post-BPM. There is a paucity of high-quality data on outcomes of different HRQOL domains post-BPM. Future studies should strive to use validated and breast-specific PRO instruments for measuring HRQOL. This will facilitate shared decision-making by enabling surgeons to provide evidence-based answers to women contemplating BPM.

A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT

NASA Astrophysics Data System (ADS)

Yan, Hao; Cervino, Laura; Jia, Xun; Jiang, Steve B.

2012-04-01

While compressed sensing (CS)-based algorithms have been developed for the low-dose cone beam CT (CBCT) reconstruction, a clear understanding of the relationship between the image quality and imaging dose at low-dose levels is needed. In this paper, we qualitatively investigate this subject in a comprehensive manner with extensive experimental and simulation studies. The basic idea is to plot both the image quality and imaging dose together as functions of the number of projections and mAs per projection over the whole clinically relevant range. On this basis, a clear understanding of the tradeoff between the image quality and imaging dose can be achieved and optimal low-dose CBCT scan protocols can be developed to maximize the dose reduction while minimizing the image quality loss for various imaging tasks in image-guided radiation therapy (IGRT). Main findings of this work include (1) under the CS-based reconstruction framework, image quality has little degradation over a large range of dose variation. Image quality degradation becomes evident when the imaging dose (approximated with the x-ray tube load) is decreased below 100 total mAs. An imaging dose lower than 40 total mAs leads to a dramatic image degradation, and thus should be used cautiously. Optimal low-dose CBCT scan protocols likely fall in the dose range of 40-100 total mAs, depending on the specific IGRT applications. (2) Among different scan protocols at a constant low-dose level, the super sparse-view reconstruction with the projection number less than 50 is the most challenging case, even with strong regularization. Better image quality can be acquired with low mAs protocols. (3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is around 72.8 total mAs or below and when the ROI is a low-contrast or high-resolution object. Based on our results, the optimal number of projections is around 90 to 120. (4) The clinically acceptable lowest imaging dose level is task dependent. In our study, 72.8 mAs is a safe dose level for visualizing low-contrast objects, while 12.2 total mAs is sufficient for detecting high-contrast objects of diameter greater than 3 mm.

Evaluation of the low dose cardiac CT imaging using ASIR technique

NASA Astrophysics Data System (ADS)

Fan, Jiahua; Hsieh, Jiang; Deubig, Amy; Sainath, Paavana; Crandall, Peter

2010-04-01

Today Cardiac imaging is one of the key driving forces for the research and development activities of Computed Tomography (CT) imaging. It requires high spatial and temporal resolution and is often associated with high radiation dose. The newly introduced ASIR technique presents an efficient method that offers the dose reduction benefits while maintaining image quality and providing fast reconstruction speed. This paper discusses the study of image quality of the ASIR technique for Cardiac CT imaging. Phantoms as well as clinical data have been evaluated to demonstrate the effectiveness of ASIR technique for Cardiac CT applications.

Penalized maximum likelihood simultaneous longitudinal PET image reconstruction with difference-image priors.

PubMed

Ellis, Sam; Reader, Andrew J

2018-04-26

Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example, to observe and quantitate changes in functional behaviour in tumors after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalizing voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high-activity lesions. Here, we present two additional novel longitudinal difference-image priors and evaluate their performance using two-dimesional (2D) simulation studies and a three-dimensional (3D) real dataset case study. We have previously proposed a simultaneous difference-image-based penalized maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have (a) low entropy (DE-PML), and (b) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D-simulated treatment response [ 18 F]fluorodeoxyglucose (FDG) brain tumor datasets and compared to standard maximum likelihood expectation-maximization (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumor behaviour, and interscan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods. Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard reconstructions with increased counts levels. In tumor regions, each method produces subtly different results in terms of preservation of tumor quantitation and reconstruction root mean-squared error (RMSE). In particular, in the two-scan simulations, the DE-PML method produced tumor means in close agreement with MLEM reconstructions, while the DTV-PML method produced the lowest errors due to noise reduction within the tumor. Across a range of tumor responses and different numbers of scans, similar results were observed, with DTV-PML producing the lowest errors of the three priors and DE-PML producing the lowest bias. Similar improvements were observed in the reconstructions of the real longitudinal datasets, although imperfect alignment of the two PET images resulted in additional changes in the difference image that affected the performance of the proposed methods. Reconstruction of longitudinal datasets by penalizing difference images between pairs of scans from a data series allows for noise reduction in all reconstructed images. An appropriate choice of penalty term and penalty strength allows for this noise reduction to be achieved while maintaining reconstruction performance in regions of change, either in terms of quantitation of mean intensity via DE-PML, or in terms of tumor RMSE via DTV-PML. Overall, improving the image quality of longitudinal datasets via simultaneous reconstruction has the potential to improve upon currently used methods, allow dose reduction, or reduce scan time while maintaining image quality at current levels. © 2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Integrated Approach to Reconstruction of Microbial Regulatory Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodionov, Dmitry A; Novichkov, Pavel S

2013-11-04

This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated inmore » RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.« less

[The dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modeling language (VRML)].

PubMed

Yu, Zhengyang; Zheng, Shusen; Chen, Huaiqing; Wang, Jianjun; Xiong, Qingwen; Jing, Wanjun; Zeng, Yu

2006-10-01

This research studies the process of dynamic concision and 3D reconstruction from medical body data using VRML and JavaScript language, focuses on how to realize the dynamic concision of 3D medical model built with VRML. The 2D medical digital images firstly are modified and manipulated by 2D image software. Then, based on these images, 3D mould is built with VRML and JavaScript language. After programming in JavaScript to control 3D model, the function of dynamic concision realized by Script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be formed in high quality near to those got in traditional methods. By this way, with the function of dynamic concision, VRML browser can offer better windows of man-computer interaction in real time environment than before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and has a promising prospect in the fields of medical image.

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE.

PubMed

Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M

2018-01-01

Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.

Varying-energy CT imaging method based on EM-TV

NASA Astrophysics Data System (ADS)

Chen, Ping; Han, Yan

2016-11-01

For complicated structural components with wide x-ray attenuation ranges, conventional fixed-energy computed tomography (CT) imaging cannot obtain all the structural information. This limitation results in a shortage of CT information because the effective thickness of the components along the direction of x-ray penetration exceeds the limit of the dynamic range of the x-ray imaging system. To address this problem, a varying-energy x-ray CT imaging method is proposed. In this new method, the tube voltage is adjusted several times with the fixed lesser interval. Next, the fusion of grey consistency and logarithm demodulation are applied to obtain full and lower noise projection with a high dynamic range (HDR). In addition, for the noise suppression problem of the analytical method, EM-TV (expectation maximization-total Jvariation) iteration reconstruction is used. In the process of iteration, the reconstruction result obtained at one x-ray energy is used as the initial condition of the next iteration. An accompanying experiment demonstrates that this EM-TV reconstruction can also extend the dynamic range of x-ray imaging systems and provide a higher reconstruction quality relative to the fusion reconstruction method.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Gu, Xuejun

2013-10-15

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstructionmore » to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.« less

Sparse coded image super-resolution using K-SVD trained dictionary based on regularized orthogonal matching pursuit.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2015-01-01

Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L1-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes.

Reconstruction following traumatic partial amputation of the ear.

PubMed

Pearl, Robert A; Sabbagh, Walid

2011-02-01

Reconstruction following traumatic amputation of the external ear remains a unique challenge to the plastic surgeon. The authors report a series of ear reconstructions with autologous costal cartilage in patients following traumatic partial amputation of the ear. Technical points regarding the carving of the cartilage framework and methods of skin coverage are discussed. Fifty partial ear reconstructions with autologous costal cartilage were performed over a 4-year period. All patients had suffered previous traumatic amputation of part of the external auricle due to bite injuries (n = 36), road traffic accidents (n = 6), burns (n = 5), or torture (n = 3). A two-stage technique of reconstruction with autologous cartilage graft was used based on Nagata's adaptations of Brent's original technique. In nine cases, skin shortage or extensive scarring required preoperative tissue expansion (n = 4) or a temporoparietal fascial flap (n = 5) to provide adequate coverage of the cartilage framework. Forty-seven patients had a successful surgical outcome without complication. Two patients developed small areas of skin necrosis resulting in exposure of the cartilage framework. These healed with conservative management with minor loss of definition. One case of wound infection resulted in significant loss of definition of the construct, which required a further surgical procedure with additional costal cartilage graft. Reconstruction of the external ear with autologous costal cartilage following traumatic amputation can produce high-quality auricles consistently and is becoming the treatment of choice for such injuries, given access to a specialist center with exposure to a high volume of cases.

GPU-based cone beam computed tomography.

PubMed

Noël, Peter B; Walczak, Alan M; Xu, Jinhui; Corso, Jason J; Hoffmann, Kenneth R; Schafer, Sebastian

2010-06-01

The use of cone beam computed tomography (CBCT) is growing in the clinical arena due to its ability to provide 3D information during interventions, its high diagnostic quality (sub-millimeter resolution), and its short scanning times (60 s). In many situations, the short scanning time of CBCT is followed by a time-consuming 3D reconstruction. The standard reconstruction algorithm for CBCT data is the filtered backprojection, which for a volume of size 256(3) takes up to 25 min on a standard system. Recent developments in the area of Graphic Processing Units (GPUs) make it possible to have access to high-performance computing solutions at a low cost, allowing their use in many scientific problems. We have implemented an algorithm for 3D reconstruction of CBCT data using the Compute Unified Device Architecture (CUDA) provided by NVIDIA (NVIDIA Corporation, Santa Clara, California), which was executed on a NVIDIA GeForce GTX 280. Our implementation results in improved reconstruction times from minutes, and perhaps hours, to a matter of seconds, while also giving the clinician the ability to view 3D volumetric data at higher resolutions. We evaluated our implementation on ten clinical data sets and one phantom data set to observe if differences occur between CPU and GPU-based reconstructions. By using our approach, the computation time for 256(3) is reduced from 25 min on the CPU to 3.2 s on the GPU. The GPU reconstruction time for 512(3) volumes is 8.5 s. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Combining Acceleration Techniques for Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction.

PubMed

Huang, Hsuan-Ming; Hsiao, Ing-Tsung

2017-01-01

Over the past decade, image quality in low-dose computed tomography has been greatly improved by various compressive sensing- (CS-) based reconstruction methods. However, these methods have some disadvantages including high computational cost and slow convergence rate. Many different speed-up techniques for CS-based reconstruction algorithms have been developed. The purpose of this paper is to propose a fast reconstruction framework that combines a CS-based reconstruction algorithm with several speed-up techniques. First, total difference minimization (TDM) was implemented using the soft-threshold filtering (STF). Second, we combined TDM-STF with the ordered subsets transmission (OSTR) algorithm for accelerating the convergence. To further speed up the convergence of the proposed method, we applied the power factor and the fast iterative shrinkage thresholding algorithm to OSTR and TDM-STF, respectively. Results obtained from simulation and phantom studies showed that many speed-up techniques could be combined to greatly improve the convergence speed of a CS-based reconstruction algorithm. More importantly, the increased computation time (≤10%) was minor as compared to the acceleration provided by the proposed method. In this paper, we have presented a CS-based reconstruction framework that combines several acceleration techniques. Both simulation and phantom studies provide evidence that the proposed method has the potential to satisfy the requirement of fast image reconstruction in practical CT.

High-performance 3D compressive sensing MRI reconstruction.

PubMed

Kim, Daehyun; Trzasko, Joshua D; Smelyanskiy, Mikhail; Haider, Clifton R; Manduca, Armando; Dubey, Pradeep

2010-01-01

Compressive Sensing (CS) is a nascent sampling and reconstruction paradigm that describes how sparse or compressible signals can be accurately approximated using many fewer samples than traditionally believed. In magnetic resonance imaging (MRI), where scan duration is directly proportional to the number of acquired samples, CS has the potential to dramatically decrease scan time. However, the computationally expensive nature of CS reconstructions has so far precluded their use in routine clinical practice - instead, more-easily generated but lower-quality images continue to be used. We investigate the development and optimization of a proven inexact quasi-Newton CS reconstruction algorithm on several modern parallel architectures, including CPUs, GPUs, and Intel's Many Integrated Core (MIC) architecture. Our (optimized) baseline implementation on a quad-core Core i7 is able to reconstruct a 256 × 160×80 volume of the neurovasculature from an 8-channel, 10 × undersampled data set within 56 seconds, which is already a significant improvement over existing implementations. The latest six-core Core i7 reduces the reconstruction time further to 32 seconds. Moreover, we show that the CS algorithm benefits from modern throughput-oriented architectures. Specifically, our CUDA-base implementation on NVIDIA GTX480 reconstructs the same dataset in 16 seconds, while Intel's Knights Ferry (KNF) of the MIC architecture even reduces the time to 12 seconds. Such level of performance allows the neurovascular dataset to be reconstructed within a clinically viable time.

Linearized image reconstruction method for ultrasound modulated electrical impedance tomography based on power density distribution

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2017-04-01

Electrical resistance tomography (ERT) is a promising measurement technique with important industrial and clinical applications. However, with limited effective measurements, it suffers from poor spatial resolution due to the ill-posedness of the inverse problem. Recently, there has been an increasing research interest in hybrid imaging techniques, utilizing couplings of physical modalities, because these techniques obtain much more effective measurement information and promise high resolution. Ultrasound modulated electrical impedance tomography (UMEIT) is one of the newly developed hybrid imaging techniques, which combines electric and acoustic modalities. A linearized image reconstruction method based on power density is proposed for UMEIT. The interior data, power density distribution, is adopted to reconstruct the conductivity distribution with the proposed image reconstruction method. At the same time, relating the power density change to the change in conductivity, the Jacobian matrix is employed to make the nonlinear problem into a linear one. The analytic formulation of this Jacobian matrix is derived and its effectiveness is also verified. In addition, different excitation patterns are tested and analyzed, and opposite excitation provides the best performance with the proposed method. Also, multiple power density distributions are combined to implement image reconstruction. Finally, image reconstruction is implemented with the linear back-projection (LBP) algorithm. Compared with ERT, with the proposed image reconstruction method, UMEIT can produce reconstructed images with higher quality and better quantitative evaluation results.

A high-resolution photon-counting breast CT system with tensor-framelet based iterative image reconstruction for radiation dose reduction

NASA Astrophysics Data System (ADS)

Ding, Huanjun; Gao, Hao; Zhao, Bo; Cho, Hyo-Min; Molloi, Sabee

2014-10-01

Both computer simulations and experimental phantom studies were carried out to investigate the radiation dose reduction with tensor framelet based iterative image reconstruction (TFIR) for a dedicated high-resolution spectral breast computed tomography (CT) based on a silicon strip photon-counting detector. The simulation was performed with a 10 cm-diameter water phantom including three contrast materials (polyethylene, 8 mg ml-1 iodine and B-100 bone-equivalent plastic). In the experimental study, the data were acquired with a 1.3 cm-diameter polymethylmethacrylate (PMMA) phantom containing iodine in three concentrations (8, 16 and 32 mg ml-1) at various radiation doses (1.2, 2.4 and 3.6 mGy) and then CT images were reconstructed using the filtered-back-projection (FBP) technique and the TFIR technique, respectively. The image quality between these two techniques was evaluated by the quantitative analysis on contrast-to-noise ratio (CNR) and spatial resolution that was evaluated using the task-based modulation transfer function (MTF). Both the simulation and experimental results indicated that the task-based MTF obtained from TFIR reconstruction with one-third of the radiation dose was comparable to that from the FBP reconstruction for low contrast target. For high contrast target, the TFIR was substantially superior to the FBP reconstruction in terms of spatial resolution. In addition, TFIR was able to achieve a factor of 1.6-1.8 increase in CNR, depending on the target contrast level. This study demonstrates that the TFIR can reduce the required radiation dose by a factor of two-thirds for a CT image reconstruction compared to the FBP technique. It achieves much better CNR and spatial resolution for high contrast target in addition to retaining similar spatial resolution for low contrast target. This TFIR technique has been implemented with a graphic processing unit system and it takes approximately 10 s to reconstruct a single-slice CT image, which can potentially be used in a future multi-slit multi-slice spiral CT system.

Ultralow-dose CT of the craniofacial bone for navigated surgery using adaptive statistical iterative reconstruction and model-based iterative reconstruction: 2D and 3D image quality.

PubMed

Widmann, Gerlig; Schullian, Peter; Gassner, Eva-Maria; Hoermann, Romed; Bale, Reto; Puelacher, Wolfgang

2015-03-01

OBJECTIVE. The purpose of this article is to evaluate 2D and 3D image quality of high-resolution ultralow-dose CT images of the craniofacial bone for navigated surgery using adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) in comparison with standard filtered backprojection (FBP). MATERIALS AND METHODS. A formalin-fixed human cadaver head was scanned using a clinical reference protocol at a CT dose index volume of 30.48 mGy and a series of five ultralow-dose protocols at 3.48, 2.19, 0.82, 0.44, and 0.22 mGy using FBP and ASIR at 50% (ASIR-50), ASIR at 100% (ASIR-100), and MBIR. Blinded 2D axial and 3D volume-rendered images were compared with each other by three readers using top-down scoring. Scores were analyzed per protocol or dose and reconstruction. All images were compared with the FBP reference at 30.48 mGy. A nonparametric Mann-Whitney U test was used. Statistical significance was set at p < 0.05. RESULTS. For 2D images, the FBP reference at 30.48 mGy did not statistically significantly differ from ASIR-100 at 3.48 mGy, ASIR-100 at 2.19 mGy, and MBIR at 0.82 mGy. MBIR at 2.19 and 3.48 mGy scored statistically significantly better than the FBP reference (p = 0.032 and 0.001, respectively). For 3D images, the FBP reference at 30.48 mGy did not statistically significantly differ from all reconstructions at 3.48 mGy; FBP and ASIR-100 at 2.19 mGy; FBP, ASIR-100, and MBIR at 0.82 mGy; MBIR at 0.44 mGy; and MBIR at 0.22 mGy. CONCLUSION. MBIR (2D and 3D) and ASIR-100 (2D) may significantly improve subjective image quality of ultralow-dose images and may allow more than 90% dose reductions.

Evaluation of automatic image quality assessment in chest CT - A human cadaver study.

PubMed

Franck, Caro; De Crop, An; De Roo, Bieke; Smeets, Peter; Vergauwen, Merel; Dewaele, Tom; Van Borsel, Mathias; Achten, Eric; Van Hoof, Tom; Bacher, Klaus

2017-04-01

The evaluation of clinical image quality (IQ) is important to optimize CT protocols and to keep patient doses as low as reasonably achievable. Considering the significant amount of effort needed for human observer studies, automatic IQ tools are a promising alternative. The purpose of this study was to evaluate automatic IQ assessment in chest CT using Thiel embalmed cadavers. Chest CT's of Thiel embalmed cadavers were acquired at different exposures. Clinical IQ was determined by performing a visual grading analysis. Physical-technical IQ (noise, contrast-to-noise and contrast-detail) was assessed in a Catphan phantom. Soft and sharp reconstructions were made with filtered back projection and two strengths of iterative reconstruction. In addition to the classical IQ metrics, an automatic algorithm was used to calculate image quality scores (IQs). To be able to compare datasets reconstructed with different kernels, the IQs values were normalized. Good correlations were found between IQs and the measured physical-technical image quality: noise (ρ=-1.00), contrast-to-noise (ρ=1.00) and contrast-detail (ρ=0.96). The correlation coefficients between IQs and the observed clinical image quality of soft and sharp reconstructions were 0.88 and 0.93, respectively. The automatic scoring algorithm is a promising tool for the evaluation of thoracic CT scans in daily clinical practice. It allows monitoring of the image quality of a chest protocol over time, without human intervention. Different reconstruction kernels can be compared after normalization of the IQs. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Three-dimensional propagation in near-field tomographic X-ray phase retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruhlandt, Aike, E-mail: aruhlan@gwdg.de; Salditt, Tim

An extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions is presented, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. This paper presents an extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. The approach is based on a novel three-dimensional propagator and is derived for the case of optically weak objects. It can be easily implemented in current phase retrieval architectures, is computationally efficient and reduces the need for restrictive prior assumptions, resultingmore » in superior reconstruction quality.« less

MO-DE-207A-01: Impact of Statistical Weights On Detection of Low-Contrast Details in Model-Based Iterative CT Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noo, F; Guo, Z

2016-06-15

Purpose: Penalized-weighted least-square reconstruction has become an important research topic in CT, to reduce dose without affecting image quality. Two components impact image quality in this reconstruction: the statistical weights and the use of an edge-preserving penalty term. We are interested in assessing the influence of statistical weights on their own, without the edge-preserving feature. Methods: The influence of statistical weights on image quality was assessed in terms of low-contrast detail detection using LROC analysis. The task amounted to detect and localize a 6-mm lesion with random contrast inside the FORBILD head phantom. A two-alternative forced-choice experiment was used withmore » two human observers performing the task. Reconstructions without and with statistical weights were compared, both using the same quadratic penalty term. The beam energy was set to 30keV to amplify spatial differences in attenuation and thereby the role of statistical weights. A fan-beam data acquisition geometry was used. Results: Visual inspection of images clearly showed a difference in noise between the two reconstructions methods. As expected, the reconstruction without statistical weights exhibited noise streaks. The other reconstruction appeared better in this aspect, but presented other disturbing noise patterns and artifacts induced by the weights. The LROC analysis yield the following 95-percent confidence interval for the difference in reader-averaged AUC (reconstruction without weights minus reconstruction with weights): [0.0026,0.0599]. The mean AUC value was 0.9094. Conclusion: We have investigated the impact of statistical weights without the use of edge-preserving penalty in penalized weighted least-square reconstruction. A decrease rather than increase in image quality was observed when using statistical weights. Thus, the observers were better able to cope with the noise streaks than the noise patterns and artifacts induced by the statistical weights. It may be that different results would be obtained if the penalty term was used with a pixel-dependent weight. F Noo receives research support from Siemens Healthcare GmbH.« less

Complex amplitude reconstruction for dynamic beam quality M² factor measurement with self-referencing interferometer wavefront sensor.

PubMed

Du, Yongzhao; Fu, Yuqing; Zheng, Lixin

2016-12-20

A real-time complex amplitude reconstruction method for determining the dynamic beam quality M² factor based on a Mach-Zehnder self-referencing interferometer wavefront sensor is developed. By using the proposed complex amplitude reconstruction method, full characterization of the laser beam, including amplitude (intensity profile) and phase information, can be reconstructed from a single interference pattern with the Fourier fringe pattern analysis method in a one-shot measurement. With the reconstructed complex amplitude, the beam fields at any position z along its propagation direction can be obtained by first utilizing the diffraction integral theory. Then the beam quality M² factor of the dynamic beam is calculated according to the specified method of the Standard ISO11146. The feasibility of the proposed method is demonstrated with the theoretical analysis and experiment, including the static and dynamic beam process. The experimental method is simple, fast, and operates without movable parts and is allowed in order to investigate the laser beam in inaccessible conditions using existing methods.

Network design and quality checks in automatic orientation of close-range photogrammetric blocks.

PubMed

Dall'Asta, Elisa; Thoeni, Klaus; Santise, Marina; Forlani, Gianfranco; Giacomini, Anna; Roncella, Riccardo

2015-04-03

Due to the recent improvements of automatic measurement procedures in photogrammetry, multi-view 3D reconstruction technologies are becoming a favourite survey tool. Rapidly widening structure-from-motion (SfM) software packages offer significantly easier image processing workflows than traditional photogrammetry packages. However, while most orientation and surface reconstruction strategies will almost always succeed in any given task, estimating the quality of the result is, to some extent, still an open issue. An assessment of the precision and reliability of block orientation is necessary and should be included in every processing pipeline. Such a need was clearly felt from the results of close-range photogrammetric surveys of in situ full-scale and laboratory-scale experiments. In order to study the impact of the block control and the camera network design on the block orientation accuracy, a series of Monte Carlo simulations was performed. Two image block configurations were investigated: a single pseudo-normal strip and a circular highly-convergent block. The influence of surveying and data processing choices, such as the number and accuracy of the ground control points, autofocus and camera calibration was investigated. The research highlights the most significant aspects and processes to be taken into account for adequate in situ and laboratory surveys, when modern SfM software packages are used, and evaluates their effect on the quality of the results of the surface reconstruction.

Stakeholders’ Perspectives on Postmastectomy Breast Reconstruction: Recognizing Ways to Improve Shared Decision Making

PubMed Central

Hasak, Jessica M.; Myckatyn, Terence M.; Grabinski, Victoria F.; Philpott, Sydney E.; Parikh, Rajiv P.

2017-01-01

Background: Postmastectomy breast reconstruction (PMBR) is an elective, preference-sensitive decision made during a stressful, time-pressured period after a cancer diagnosis. Shared decision making (SDM) can improve decision quality about preference-sensitive choices. Stakeholders’ perspectives on ways to support PMBR decision-making were explored. Methods: Forty semi-structured interviews with stakeholders (20 postmastectomy patients, 10 PMBR surgeons, 10 PMBR nurses) were conducted. Clinicians were recruited from diverse practices across the United States. Patients were recruited using purposive sampling with varying PMBR experiences, including no reconstruction. The interview guide was based on an implementation research framework. Themes were identified using grounded theory approach, based on frequency and emotive force conveyed. Results: Engagement in SDM was variable. Some patients wanted more information about PMBR from clinicians, particularly about risks. Some clinicians acknowledged highlighting benefits and downplaying risks. Many patients felt pressured to make a choice by their clinicians. Clinicians who successfully engaged patients through decisions often used outside resources to supplement conversations. Conclusions: Patient–clinician trust was critical to high-quality decisions, and many patients expressed decision regret when they were not engaged in PMBR discussions. Patients often perceived a race- or age-related bias in clinician information sharing. Interventions to support SDM may enhance decision quality and reduce decision regret about PMBR, ultimately improving patient-centered care for women with breast cancer. PMID:29263969

Online geometric calibration of cone-beam computed tomography for arbitrary imaging objects.

PubMed

Meng, Yuanzheng; Gong, Hui; Yang, Xiaoquan

2013-02-01

A novel online method based on the symmetry property of the sum of projections (SOP) is proposed to obtain the geometric parameters in cone-beam computed tomography (CBCT). This method requires no calibration phantom and can be used in circular trajectory CBCT with arbitrary cone angles. An objective function is deduced to illustrate the dependence of the symmetry of SOP on geometric parameters, which will converge to its minimum when the geometric parameters achieve their true values. Thus, by minimizing the objective function, we can obtain the geometric parameters for image reconstruction. To validate this method, numerical phantom studies with different noise levels are simulated. The results show that our method is insensitive to the noise and can determine the skew (in-plane rotation angle of the detector), the roll (rotation angle around the projection of the rotation axis on the detector), and the rotation axis with high accuracy, while the mid-plane and source-to-detector distance will be obtained with slightly lower accuracy. However, our simulation studies validate that the errors of the latter two parameters brought by our method will hardly degrade the quality of reconstructed images. The small animal studies show that our method is able to deal with arbitrary imaging objects. In addition, the results of the reconstructed images in different slices demonstrate that we have achieved comparable image quality in the reconstructions as some offline methods.

Iterative image reconstruction that includes a total variation regularization for radial MRI.

PubMed

Kojima, Shinya; Shinohara, Hiroyuki; Hashimoto, Takeyuki; Hirata, Masami; Ueno, Eiko

2015-07-01

This paper presents an iterative image reconstruction method for radial encodings in MRI based on a total variation (TV) regularization. The algebraic reconstruction method combined with total variation regularization (ART_TV) is implemented with a regularization parameter specifying the weight of the TV term in the optimization process. We used numerical simulations of a Shepp-Logan phantom, as well as experimental imaging of a phantom that included a rectangular-wave chart, to evaluate the performance of ART_TV, and to compare it with that of the Fourier transform (FT) method. The trade-off between spatial resolution and signal-to-noise ratio (SNR) was investigated for different values of the regularization parameter by experiments on a phantom and a commercially available MRI system. ART_TV was inferior to the FT with respect to the evaluation of the modulation transfer function (MTF), especially at high frequencies; however, it outperformed the FT with regard to the SNR. In accordance with the results of SNR measurement, visual impression suggested that the image quality of ART_TV was better than that of the FT for reconstruction of a noisy image of a kiwi fruit. In conclusion, ART_TV provides radial MRI with improved image quality for low-SNR data; however, the regularization parameter in ART_TV is a critical factor for obtaining improvement over the FT.

Autocalibrating motion-corrected wave-encoding for highly accelerated free-breathing abdominal MRI.

PubMed

Chen, Feiyu; Zhang, Tao; Cheng, Joseph Y; Shi, Xinwei; Pauly, John M; Vasanawala, Shreyas S

2017-11-01

To develop a motion-robust wave-encoding technique for highly accelerated free-breathing abdominal MRI. A comprehensive 3D wave-encoding-based method was developed to enable fast free-breathing abdominal imaging: (a) auto-calibration for wave-encoding was designed to avoid extra scan for coil sensitivity measurement; (b) intrinsic butterfly navigators were used to track respiratory motion; (c) variable-density sampling was included to enable compressed sensing; (d) golden-angle radial-Cartesian hybrid view-ordering was incorporated to improve motion robustness; and (e) localized rigid motion correction was combined with parallel imaging compressed sensing reconstruction to reconstruct the highly accelerated wave-encoded datasets. The proposed method was tested on six subjects and image quality was compared with standard accelerated Cartesian acquisition both with and without respiratory triggering. Inverse gradient entropy and normalized gradient squared metrics were calculated, testing whether image quality was improved using paired t-tests. For respiratory-triggered scans, wave-encoding significantly reduced residual aliasing and blurring compared with standard Cartesian acquisition (metrics suggesting P < 0.05). For non-respiratory-triggered scans, the proposed method yielded significantly better motion correction compared with standard motion-corrected Cartesian acquisition (metrics suggesting P < 0.01). The proposed methods can reduce motion artifacts and improve overall image quality of highly accelerated free-breathing abdominal MRI. Magn Reson Med 78:1757-1766, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Algorithm-enabled exploration of image-quality potential of cone-beam CT in image-guided radiation therapy

NASA Astrophysics Data System (ADS)

Han, Xiao; Pearson, Erik; Pelizzari, Charles; Al-Hallaq, Hania; Sidky, Emil Y.; Bian, Junguo; Pan, Xiaochuan

2015-06-01

Kilo-voltage (KV) cone-beam computed tomography (CBCT) unit mounted onto a linear accelerator treatment system, often referred to as on-board imager (OBI), plays an increasingly important role in image-guided radiation therapy. While the FDK algorithm is currently used for reconstructing images from clinical OBI data, optimization-based reconstruction has also been investigated for OBI CBCT. An optimization-based reconstruction involves numerous parameters, which can significantly impact reconstruction properties (or utility). The success of an optimization-based reconstruction for a particular class of practical applications thus relies strongly on appropriate selection of parameter values. In the work, we focus on tailoring the constrained-TV-minimization-based reconstruction, an optimization-based reconstruction previously shown of some potential for CBCT imaging conditions of practical interest, to OBI imaging through appropriate selection of parameter values. In particular, for given real data of phantoms and patient collected with OBI CBCT, we first devise utility metrics specific to OBI-quality-assurance tasks and then apply them to guiding the selection of parameter values in constrained-TV-minimization-based reconstruction. The study results show that the reconstructions are with improvement, relative to clinical FDK reconstruction, in both visualization and quantitative assessments in terms of the devised utility metrics.

A fast 4D cone beam CT reconstruction method based on the OSC-TV algorithm.

PubMed

Mascolo-Fortin, Julia; Matenine, Dmitri; Archambault, Louis; Després, Philippe

2018-01-01

Four-dimensional cone beam computed tomography allows for temporally resolved imaging with useful applications in radiotherapy, but raises particular challenges in terms of image quality and computation time. The purpose of this work is to develop a fast and accurate 4D algorithm by adapting a GPU-accelerated ordered subsets convex algorithm (OSC), combined with the total variation minimization regularization technique (TV). Different initialization schemes were studied to adapt the OSC-TV algorithm to 4D reconstruction: each respiratory phase was initialized either with a 3D reconstruction or a blank image. Reconstruction algorithms were tested on a dynamic numerical phantom and on a clinical dataset. 4D iterations were implemented for a cluster of 8 GPUs. All developed methods allowed for an adequate visualization of the respiratory movement and compared favorably to the McKinnon-Bates and adaptive steepest descent projection onto convex sets algorithms, while the 4D reconstructions initialized from a prior 3D reconstruction led to better overall image quality. The most suitable adaptation of OSC-TV to 4D CBCT was found to be a combination of a prior FDK reconstruction and a 4D OSC-TV reconstruction with a reconstruction time of 4.5 minutes. This relatively short reconstruction time could facilitate a clinical use.

Averaging scheme for atomic resolution off-axis electron holograms.

PubMed

Niermann, T; Lehmann, M

2014-08-01

All micrographs are limited by shot-noise, which is intrinsic to the detection process of electrons. For beam insensitive specimen this limitation can in principle easily be circumvented by prolonged exposure times. However, in the high-resolution regime several instrumental instabilities limit the applicable exposure time. Particularly in the case of off-axis holography the holograms are highly sensitive to the position and voltage of the electron-optical biprism. We present a novel reconstruction algorithm to average series of off-axis holograms while compensating for specimen drift, biprism drift, drift of biprism voltage, and drift of defocus, which all might cause problematic changes from exposure to exposure. We show an application of the algorithm utilizing also the possibilities of double biprism holography, which results in a high quality exit-wave reconstruction with 75 pm resolution at a very high signal-to-noise ratio. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography.

PubMed

Hirata, Kenichiro; Utsunomiya, Daisuke; Kidoh, Masafumi; Funama, Yoshinori; Oda, Seitaro; Yuki, Hideaki; Nagayama, Yasunori; Iyama, Yuji; Nakaura, Takeshi; Sakabe, Daisuke; Tsujita, Kenichi; Yamashita, Yasuyuki

2018-05-01

We aimed to evaluate the image quality performance of coronary CT angiography (CTA) under the different settings of forward-projected model-based iterative reconstruction solutions (FIRST).Thirty patients undergoing coronary CTA were included. Each image was reconstructed using filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR-3D), and 2 model-based iterative reconstructions including FIRST-body and FIRST-cardiac sharp (CS). CT number and noise were measured in the coronary vessels and plaque. Subjective image-quality scores were obtained for noise and structure visibility.In the objective image analysis, FIRST-body produced the significantly highest contrast-to-noise ratio. Regarding subjective image quality, FIRST-CS had the highest score for structure visibility, although the image noise score was inferior to that of FIRST-body.In conclusion, FIRST provides significant improvements in objective and subjective image quality compared with FBP and AIDR-3D. FIRST-body effectively reduces image noise, but the structure visibility with FIRST-CS was superior to FIRST-body.

The artificial retina for track reconstruction at the LHC crossing rate

NASA Astrophysics Data System (ADS)

Abba, A.; Bedeschi, F.; Citterio, M.; Caponio, F.; Cusimano, A.; Geraci, A.; Marino, P.; Morello, M. J.; Neri, N.; Punzi, G.; Piucci, A.; Ristori, L.; Spinella, F.; Stracka, S.; Tonelli, D.

2016-04-01

We present the results of an R&D study for a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel and silicon strip detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired to the current understanding of the mechanisms adopted by the primary visual cortex of mammals in the early stages of visual-information processing. The detailed geometry and charged-particle's activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. We find that high-quality tracking in large detectors is possible with sub-microsecond latencies when the algorithm is implemented in modern, high-speed, high-bandwidth FPGA devices.

Image Quality Performance Measurement of the microPET Focus 120

NASA Astrophysics Data System (ADS)

Ballado, Fernando Trejo; López, Nayelli Ortega; Flores, Rafael Ojeda; Ávila-Rodríguez, Miguel A.

2010-12-01

The aim of this work is to evaluate the characteristics involved in the image reconstruction of the microPET Focus 120. For this evaluation were used two different phantoms; a miniature hot-rod Derenzo phantom and a National Electrical Manufacturers Association (NEMA) NU4-2008 image quality (IQ) phantom. The best image quality was obtained when using OSEM3D as the reconstruction method reaching a spatial resolution of 1.5 mm with the Derenzo phantom filled with 18F. Image quality test results indicate a superior image quality for the Focus 120 when compared to previous microPET models.

Subjective and objective appearance of head and neck cancer patients following microsurgical reconstruction and associated quality of life─A cross-sectional study.

PubMed

Kansy, Katinka; Hoffmann, Jürgen; Alhalabi, Obada; Mistele, Nicole; Freier, Kolja; Mertens, Christian; Freudlsperger, Christian; Engel, Michael

2018-06-01

Depending on the site and size of head and neck cancer, the disease affects patients' appearance and subsequently their quality of life. The aim of this study was to correlate subjective and objective evaluation of facial appearance and associated quality of life following ablative tumor surgery and microsurgical reconstruction. A total of 99 patients with combined ablative and reconstructive microsurgical procedure for head and neck malignancy and seven patients with non-malignant disease were examined by three-dimensional (3D) (photogrammetry at least 6 months post-surgery and were evaluated by two-dimensional (2D) and 3D means for symmetry and facial proportions. Measurements were correlated with subjective reporting from the University of Washington Quality of Life Questionnaire and observer ratings. Of the 106 patients, three patients scored themselves as significantly disfigured (2.8%), 19 were bothered by their appearance (17.9%), 27 (25.5%) reported no change, and 57 (53.8%) reported minor changes in their appearance. On 2D evaluation, 10 patients (9.4%) showed severely abnormal facial proportions. On 3D analysis, 17 patients showed major asymmetry. There was a high correlation (0.67) between patient and observer subjective rating (p < 0.05). While 2D evaluation alone showed no significant correlation with subjective rating, 3D evaluation showed a moderate correlation (0.37; p < 0.05). The best results were achieved by combining 2D and 3D measurements (0.5; p < 0.05). Young female patients were most critical about their appearance. Following combined ablative and microsurgical reconstructive procedures, patients have a realistic perception of their appearance compared with observer ratings and a combination of 2D and 3D objective evaluation. Copyright © 2018 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Characterization of photon-counting multislit breast tomosynthesis.

PubMed

Berggren, Karl; Cederström, Björn; Lundqvist, Mats; Fredenberg, Erik

2018-02-01

It has been shown that breast tomosynthesis may improve sensitivity and specificity compared to two-dimensional mammography, resulting in increased detection-rate of cancers or lowered call-back rates. The purpose of this study is to characterize a spectral photon-counting multislit breast tomosynthesis system that is able to do single-scan spectral imaging with multiple collimated x-ray beams. The system differs in many aspects compared to conventional tomosynthesis using energy-integrating flat-panel detectors. The investigated system was a prototype consisting of a dual-threshold photon-counting detector with 21 collimated line detectors scanning across the compressed breast. A review of the system is done in terms of detector, acquisition geometry, and reconstruction methods. Three reconstruction methods were used, simple back-projection, filtered back-projection and an iterative algebraic reconstruction technique. The image quality was evaluated by measuring the modulation transfer-function (MTF), normalized noise-power spectrum, detective quantum-efficiency (DQE), and artifact spread-function (ASF) on reconstructed spectral tomosynthesis images for a total-energy bin (defined by a low-energy threshold calibrated to remove electronic noise) and for a high-energy bin (with a threshold calibrated to split the spectrum in roughly equal parts). Acquisition was performed using a 29 kVp W/Al x-ray spectrum at a 0.24 mGy exposure. The difference in MTF between the two energy bins was negligible, that is, there was no energy dependence on resolution. The MTF dropped to 50% at 1.5 lp/mm to 2.3 lp/mm in the scan direction and 2.4 lp/mm to 3.3 lp/mm in the slit direction, depending on the reconstruction method. The full width at half maximum of the ASF was found to range from 13.8 mm to 18.0 mm for the different reconstruction methods. The zero-frequency DQE of the system was found to be 0.72. The fraction of counts in the high-energy bin was measured to be 59% of the total detected spectrum. Scantimes ranged from 4 s to 16.5 s depending on voltage and current settings. The characterized system generates spectral tomosynthesis images with a dual-energy photon-counting detector. Measurements show a high DQE, enabling high image quality at a low dose, which is beneficial for low-dose applications such as screening. The single-scan spectral images open up for applications such as quantitative material decomposition and contrast-enhanced tomosynthesis. © 2017 American Association of Physicists in Medicine.

Compression of computer generated phase-shifting hologram sequence using AVC and HEVC

NASA Astrophysics Data System (ADS)

Xing, Yafei; Pesquet-Popescu, Béatrice; Dufaux, Frederic

2013-09-01

With the capability of achieving twice the compression ratio of Advanced Video Coding (AVC) with similar reconstruction quality, High Efficiency Video Coding (HEVC) is expected to become the newleading technique of video coding. In order to reduce the storage and transmission burden of digital holograms, in this paper we propose to use HEVC for compressing the phase-shifting digital hologram sequences (PSDHS). By simulating phase-shifting digital holography (PSDH) interferometry, interference patterns between illuminated three dimensional( 3D) virtual objects and the stepwise phase changed reference wave are generated as digital holograms. The hologram sequences are obtained by the movement of the virtual objects and compressed by AVC and HEVC. The experimental results show that AVC and HEVC are efficient to compress PSDHS, with HEVC giving better performance. Good compression rate and reconstruction quality can be obtained with bitrate above 15000kbps.

Patch-based anisotropic diffusion scheme for fluorescence diffuse optical tomography--part 2: image reconstruction.

PubMed

Correia, Teresa; Koch, Maximilian; Ale, Angelique; Ntziachristos, Vasilis; Arridge, Simon

2016-02-21

Fluorescence diffuse optical tomography (fDOT) provides 3D images of fluorescence distributions in biological tissue, which represent molecular and cellular processes. The image reconstruction problem is highly ill-posed and requires regularisation techniques to stabilise and find meaningful solutions. Quadratic regularisation tends to either oversmooth or generate very noisy reconstructions, depending on the regularisation strength. Edge preserving methods, such as anisotropic diffusion regularisation (AD), can preserve important features in the fluorescence image and smooth out noise. However, AD has limited ability to distinguish an edge from noise. We propose a patch-based anisotropic diffusion regularisation (PAD), where regularisation strength is determined by a weighted average according to the similarity between patches around voxels within a search window, instead of a simple local neighbourhood strategy. However, this method has higher computational complexity and, hence, we wavelet compress the patches (PAD-WT) to speed it up, while simultaneously taking advantage of the denoising properties of wavelet thresholding. Furthermore, structural information can be incorporated into the image reconstruction with PAD-WT to improve image quality and resolution. In this case, the weights used to average voxels in the image are calculated using the structural image, instead of the fluorescence image. The regularisation strength depends on both structural and fluorescence images, which guarantees that the method can preserve fluorescence information even when it is not structurally visible in the anatomical images. In part 1, we tested the method using a denoising problem. Here, we use simulated and in vivo mouse fDOT data to assess the algorithm performance. Our results show that the proposed PAD-WT method provides high quality and noise free images, superior to those obtained using AD.

Cone-beam CT of traumatic brain injury using statistical reconstruction with a post-artifact-correction noise model

NASA Astrophysics Data System (ADS)

Dang, H.; Stayman, J. W.; Sisniega, A.; Xu, J.; Zbijewski, W.; Yorkston, J.; Aygun, N.; Koliatsos, V.; Siewerdsen, J. H.

2015-03-01

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered back-projection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

A Comparison of Compressed Sensing and Sparse Recovery Algorithms Applied to Simulation Data

DOE PAGES

Fan, Ya Ju; Kamath, Chandrika

2016-09-01

The move toward exascale computing for scientific simulations is placing new demands on compression techniques. It is expected that the I/O system will not be able to support the volume of data that is expected to be written out. To enable quantitative analysis and scientific discovery, we are interested in techniques that compress high-dimensional simulation data and can provide perfect or near-perfect reconstruction. In this paper, we explore the use of compressed sensing (CS) techniques to reduce the size of the data before they are written out. Using large-scale simulation data, we investigate how the sufficient sparsity condition and themore » contrast in the data affect the quality of reconstruction and the degree of compression. Also, we provide suggestions for the practical implementation of CS techniques and compare them with other sparse recovery methods. Finally, our results show that despite longer times for reconstruction, compressed sensing techniques can provide near perfect reconstruction over a range of data with varying sparsity.« less

A Comparison of Compressed Sensing and Sparse Recovery Algorithms Applied to Simulation Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Ya Ju; Kamath, Chandrika

The move toward exascale computing for scientific simulations is placing new demands on compression techniques. It is expected that the I/O system will not be able to support the volume of data that is expected to be written out. To enable quantitative analysis and scientific discovery, we are interested in techniques that compress high-dimensional simulation data and can provide perfect or near-perfect reconstruction. In this paper, we explore the use of compressed sensing (CS) techniques to reduce the size of the data before they are written out. Using large-scale simulation data, we investigate how the sufficient sparsity condition and themore » contrast in the data affect the quality of reconstruction and the degree of compression. Also, we provide suggestions for the practical implementation of CS techniques and compare them with other sparse recovery methods. Finally, our results show that despite longer times for reconstruction, compressed sensing techniques can provide near perfect reconstruction over a range of data with varying sparsity.« less

Burns: Treatment and Outcomes

PubMed Central

Burd, Andrew

2010-01-01

Burns can cause extensive and devastating injuries of the head and neck. Prevention of the initial injury must always be a priority, but once an injury has occurred, then prevention of progression of the damage together with survival of the patient must be the immediate goals. The acute care will have a major influence on the subsequent scarring, reconstructive need, and long-term outcome. In the majority of cases, the reconstruction will involve restoration of form and function to the soft tissues, and the methods used will depend very much on the extent of scarring locally and elsewhere in the body. In nearly all cases, a significant improvement in functional and aesthetic outcomes can be achieved, which, in conjunction with intensive psychosocial rehabilitation, can lead to high-quality patient outcomes. With the prospect of facial transplantation being a clinical reality, the reconstructive spectrum has opened up even further, and, with appropriate reconstruction and support, no patient should be left economically deprived or socially isolated after a burn injury. PMID:22550448

Exploiting Mirrors in 3d Reconstruction of Small Artefacts

NASA Astrophysics Data System (ADS)

Kontogianni, G.; Thomaidis, A. T.; Chliverou, R.; Georgopoulos, A.

2018-05-01

3D reconstruction of small artefacts is very significant in order to capture the details of the whole object irrespective of the documentation method which is used (Ranged Based or Image Based). Sometimes it is very difficult to achieve it because of hidden parts, occlusions, and obstructions which the object has. Hence, more data are necessary in order to 3D digitise the whole of the artefact leading to increased time for collecting and consequently processing the data. A methodology is necessary in order to reduce the collection of the data and therefore their processing time especially in cases of mass digitisation. So in this paper, the use of mirrors in particular high-quality mirrors in the data acquisition phase for the 3D reconstruction of small artefacts is investigated. Two case studies of 3D reconstruction are presented: the first one concerns Range-Based modelling especially a Time of Flight laser scanner is utilised and in the second one Image-Based modelling technique is implemented.

Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: a review

PubMed Central

Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong

2017-01-01

Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail. PMID:28303644

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brady, S. L.; Yee, B. S.; Kaufman, R. A.

Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metricmore » was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more smoothed appearance than the pre-ASiR Trade-Mark-Sign 100% FBP image. Finally, relative to non-ASiR Trade-Mark-Sign images with 100% of standard dose across the pediatric phantom age spectrum, similar noise levels were obtained in the images at a dose reduction of 48% with 40% ASIR Trade-Mark-Sign and a dose reduction of 82% with 100% ASIR Trade-Mark-Sign . Conclusions: The authors' work was conducted to identify the dose reduction limits of ASiR Trade-Mark-Sign for a pediatric oncology population using automatic tube current modulation. Improvements in noise levels from ASiR Trade-Mark-Sign reconstruction were adapted to provide lower radiation exposure (i.e., lower mA) instead of improved image quality. We have demonstrated for the image quality standards required at our institution, a maximum dose reduction of 82% can be achieved using 100% ASiR Trade-Mark-Sign ; however, to negate changes in the appearance of reconstructed images using ASiR Trade-Mark-Sign with a medium to low frequency noise preserving reconstruction filter (i.e., standard), 40% ASiR Trade-Mark-Sign was implemented in our clinic for 42%-48% dose reduction at all pediatric ages without a visually perceptible change in image quality or image noise.« less

Optimizing Cone Beam Computed Tomography (CBCT) System for Image Guided Radiation Therapy

NASA Astrophysics Data System (ADS)

Park, Chun Joo

Cone Beam Computed Tomography (CBCT) system is the most widely used imaging device in image guided radiation therapy (IGRT), where set of 3D volumetric image of patient can be reconstructed to identify and correct position setup errors prior to the radiation treatment. This CBCT system can significantly improve precision of on-line setup errors of patient position and tumor target localization prior to the treatment. However, there are still a number of issues that needs to be investigated with CBCT system such as 1) progressively increasing defective pixels in imaging detectors by its frequent usage, 2) hazardous radiation exposure to patients during the CBCT imaging, 3) degradation of image quality due to patients' respiratory motion when CBCT is acquired and 4) unknown knowledge of certain anatomical features such as liver, due to lack of soft-tissue contrast which makes tumor motion verification challenging. In this dissertation, we explore on optimizing the use of cone beam computed tomography (CBCT) system under such circumstances. We begin by introducing general concept of IGRT. We then present the development of automated defective pixel detection algorithm for X-ray imagers that is used for CBCT imaging using wavelet analysis. We next investigate on developing fast and efficient low-dose volumetric reconstruction techniques which includes 1) fast digital tomosynthesis reconstruction using general-purpose graphics processing unit (GPGPU) programming and 2) fast low-dose CBCT image reconstruction based on the Gradient-Projection-Barzilai-Borwein formulation (GP-BB). We further developed two efficient approaches that could reduce the degradation of CBCT images from respiratory motion. First, we propose reconstructing four dimensional (4D) CBCT and DTS using respiratory signal extracted from fiducial markers implanted in liver. Second, novel motion-map constrained image reconstruction (MCIR) is proposed that allows reconstruction of high quality and high phase resolution 4DCBCT images with no more than the imaging dose used in a standard Free Breathing 3DCBCT (FB-3DCBCT) scan. Finally, we demonstrate a method to analyze motion characteristics of liver that are particularly important for image guided stereotactic body radiation therapy (IG-SBRT). It is anticipated that all the approaches proposed in this study, which are both technically and clinically feasible, will allow much improvement in IGRT process.

Weighted nonnegative tensor factorization for atmospheric tomography reconstruction

NASA Astrophysics Data System (ADS)

Carmona-Ballester, David; Trujillo-Sevilla, Juan M.; Bonaque-González, Sergio; Gómez-Cárdenes, Óscar; Rodríguez-Ramos, José M.

2018-06-01

Context. Increasing the area on the sky over which atmospheric turbulences can be corrected is a matter of wide interest in astrophysics, especially when a new generation of extremely large telescopes (ELT) is to come in the near future. Aims: In this study we tested if a method for visual representation in three-dimensional displays, the weighted nonnegative tensor factorization (WNTF), is able to improve the quality of the atmospheric tomography (AT) reconstruction as compared to a more standardized method like a randomized Kaczmarz algorithm. Methods: A total of 1000 different atmospheres were simulated and recovered by both methods. Recovering was computed for two and three layers and for four different constellations of laser guiding stars (LGS). The goodness of both methods was tested by means of the radial average of the Strehl ratio across the field of view of a telescope of 8m diameter with a sky coverage of 97.8 arcsec. Results: The proposed method significantly outperformed the Kaczmarz in all tested cases (p ≤ 0.05). In WNTF, three-layers configuration provided better outcomes, but there was no clear relation between different LGS constellations and the quality of Strehl ratio maps. Conclusions: The WNTF method is a novel technique in astronomy and its use to recover atmospheric turbulence profiles was proposed and tested. It showed better quality of reconstruction than a conventional Kaczmarz algorithm independently of the number and height of recovered atmospheric layers and of the constellation of laser guide star used. The WNTF method was shown to be a useful tool in highly ill-posed AT problems, where the difficulty of classical algorithms produce high Strehl value maps.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

PubMed

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Synthetic aperture radar signal data compression using block adaptive quantization

NASA Technical Reports Server (NTRS)

Kuduvalli, Gopinath; Dutkiewicz, Melanie; Cumming, Ian

1994-01-01

This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

Speckle imaging techniques of the turbulence degraded images

NASA Astrophysics Data System (ADS)

Liu, Jin; Huang, Zongfu; Mao, Hongjun; Liang, Yonghui

2018-03-01

We propose a speckle imaging algorithm in which we use the improved form of spectral ratio to obtain the Fried parameter, we also use a filter to reduce the high frequency noise effects. Our algorithm makes an improvement in the quality of the reconstructed images. The performance is illustrated by computer simulations.

Diagnostic accuracy of 256-row multidetector CT coronary angiography with prospective ECG-gating combined with fourth-generation iterative reconstruction algorithm in the assessment of coronary artery bypass: evaluation of dose reduction and image quality.

PubMed

Ippolito, Davide; Fior, Davide; Franzesi, Cammillo Talei; Riva, Luca; Casiraghi, Alessandra; Sironi, Sandro

2017-12-01

Effective radiation dose in coronary CT angiography (CTCA) for coronary artery bypass graft (CABG) evaluation is remarkably high because of long scan lengths. Prospective electrocardiographic gating with iterative reconstruction can reduce effective radiation dose. To evaluate the diagnostic performance of low-kV CT angiography protocol with prospective ecg-gating technique and iterative reconstruction (IR) algorithm in follow-up of CABG patients compared with standard retrospective protocol. Seventy-four non-obese patients with known coronary disease treated with artery bypass grafting were prospectively enrolled. All the patients underwent 256 MDCT (Brilliance iCT, Philips) CTCA using low-dose protocol (100 kV; 800 mAs; rotation time: 0.275 s) combined with prospective ECG-triggering acquisition and fourth-generation IR technique (iDose 4 ; Philips); all the lengths of the bypass graft were included in the evaluation. A control group of 42 similar patients was evaluated with a standard retrospective ECG-gated CTCA (100 kV; 800 mAs).On both CT examinations, ROIs were placed to calculate standard deviation of pixel values and intra-vessel density. Diagnostic quality was also evaluated using a 4-point quality scale. Despite the statistically significant reduction of radiation dose evaluated with DLP (study group mean DLP: 274 mGy cm; control group mean DLP: 1224 mGy cm; P value < 0.001). No statistical differences were found between PGA group and RGH group regarding intra-vessel density absolute values and SNR. Qualitative analysis, evaluated by two radiologists in "double blind", did not reveal any significant difference in diagnostic quality of the two groups. The development of high-speed MDCT scans combined with modern IR allows an accurate evaluation of CABG with prospective ECG-gating protocols in a single breath hold, obtaining a significant reduction in radiation dose.

Holographic Subsurface Radar Technique for Nondestructive Testing of Dielectric Structures

NASA Astrophysics Data System (ADS)

Ivashov, S. I.; Bugaev, A. S.; Zhuravlev, A. V.; Razevig, V. V.; Chizh, M. A.; Ivashov, A. I.

2018-02-01

Holographic subsurface radar method is compared with the conventional technology of impulse radars. Basic relationships needed for the reconstruction of complex microwave holograms are presented. Possible applications of the proposed technology are discussed. Diagnostics of polyurethane foam coatings of spacecrafts is used as an example of the efficiency of holographic subsurface radars. Results of reconstruction of complex and amplitude microwave holograms are compared. It is demonstrated that the image quality that results from reconstruction of complex microwave holograms is higher than the image quality obtained with the aid of amplitude holograms.

Does bone debris in anterior cruciate ligament reconstruction really matter? A cohort study of a protocol for bone debris debridement

PubMed Central

Imam, Mohamed A.; Abdelkafy, Ashraf; Dinah, Feroz; Adhikari, Ajeya

2015-01-01

Background: The purpose of the current study was to determine whether a systematic five-step protocol for debridement and evacuation of bone debris during anterior cruciate ligament reconstruction (ACLR) reduces the presence of such debris on post-operative radiographs. Methods: A five-step protocol for removal of bone debris during arthroscopic assisted ACLR was designed. It was applied to 60 patients undergoing ACLR (Group 1), and high-quality digital radiographs were taken post-operatively in each case to assess for the presence of intra-articular bone debris. A control group of 60 consecutive patients in whom no specific bone debris protocol was applied (Group 2) and their post-operative radiographs were also checked for the presence of intra-articular bone debris. Results: In Group 1, only 15% of post-operative radiographs showed residual bone debris, compared to 69% in Group 2 (p < 0.001). Conclusion: A five-step systematic protocol for bone debris removal during arthroscopic assisted ACLR resulted in a significant decrease in residual bone debris seen on high-quality post-operative radiographs. PMID:27163060

Imaging diffusive media using time-independent and time-harmonic sources: dependence of image quality on imaging algorithms, target volume, weight matrix, and view angles

NASA Astrophysics Data System (ADS)

Chang, Jenghwa; Aronson, Raphael; Graber, Harry L.; Barbour, Randall L.

1995-05-01

We present results examining the dependence of image quality for imaging in dense scattering media as influenced by the choice of parameters pertaining to the physical measurement and factors influencing the efficiency of the computation. The former includes the density of the weight matrix as affected by the target volume, view angle, and source condition. The latter includes the density of the weight matrix and type of algorithm used. These were examined by solving a one-step linear perturbation equation derived from the transport equation using three different algorithms: POCS, CGD, and SART algorithms with contraints. THe above were explored by evaluating four different 3D cylindrical phantom media: a homogeneous medium, an media containing a single black rod on the axis, a single black rod parallel to the axis, and thirteen black rods arrayed in the shape of an 'X'. Solutions to the forward problem were computed using Monte Carlo methods for an impulse source, from which was calculated time- independent and time harmonic detector responses. The influence of target volume on image quality and computational efficiency was studied by computing solution to three types of reconstructions: 1) 3D reconstruction, which considered each voxel individually, 2) 2D reconstruction, which assumed that symmetry along the cylinder axis was know a proiri, 3) 2D limited reconstruction, which assumed that only those voxels in the plane of the detectors contribute information to the detecot readings. The effect of view angle was explored by comparing computed images obtained from a single source, whose position was varied, as well as for the type of tomographic measurement scheme used (i.e., radial scan versus transaxial scan). The former condition was also examined for the dependence of the above on choice of source condition [ i.e., cw (2D reconstructions) versus time-harmonic (2D limited reconstructions) source]. The efficiency of the computational effort was explored, principally, by conducting a weight matrix 'threshold titration' study. This involved computing the ratio of each matrix element to the maximum element of its row and setting this to zero if the ratio was less than a preselected threshold. Results obtained showed that all three types of reconstructions provided good image quality. The 3D reconstruction outperformed the other two reconstructions. The time required for 2D and 2D limited reconstruction is much less (< 10%) than that for the 3D reconstruction. The 'threshold titration' study shows that artifacts were present when the threshold was 5% or higher, and no significant differences of image quality were observed when the thresholds were less tha 1%, in which case 38% (21,849 of 57,600) of the total weight elements were set to zero. Restricting the view angle produced degradation in image quality, but, in all cases, clearly recognizable images were obtained.

Transvaginal single-incision mesh reconstruction for recurrent or advanced anterior vaginal wall prolapse.

PubMed

Marschke, J; Hengst, L; Schwertner-Tiepelmann, N; Beilecke, K; Tunn, R

2015-05-01

Single-incision transvaginal mesh for reconstruction of Level I and II prolapses in women with recurrent or advanced prolapse. We evaluated functional, anatomical, sonomorphological and quality-of-life outcome. Data were collected retrospectively for preoperative parameters and at follow-up visits. Anatomical cure was assessed with vaginal examination using the ICS-POP-Q system; introital-ultrasound scan for postvoidal residual and description of mesh characteristics was performed. We applied a visual analogue scale (VAS) and the German Pelvic Floor Questionnaire to assess quality-of-life. Seventy women with cystocele (III: 61.3%/IV: 16%), all post-hysterectomy and in majority (81.4%) after previous cystocele repair, were operated using a single-incision transvaginal technique. Overall anatomical success rate was 95.7% with significant improvement in quality-of-life (p < 0.0001). Mesh erosion occurred in 5.7%, one patient presented symptomatic vaginal vault prolapse. Postvoidal residual declined significantly (58 vs. 2.9%). Sonographic mesh length was 55.7% of implanted mesh with a wide range of mesh position, but no signs of mesh dislocation. There was no de novo dyspareunia reported, one case of preoperative existing dyspareunia worsened. No severe adverse event was observed. We hereby present a trial of a high-risk group of patients requiring reconstruction of anterior and apical vaginal wall in mostly recurrent prolapse situation. Our data support the hypothesis of improved anatomical and functional results and less mesh shrinkage caused by the single-incision technique with fixation in sacrospinous ligament in combination with modification in mesh quality compared to former multi-incision techniques.

Resolution and quality enhancement in terahertz in-line holography by sub-pixel sampling with double-distance reconstruction.

PubMed

Li, Zeyu; Li, Lei; Qin, Yu; Li, Guangbin; Wang, Du; Zhou, Xun

2016-09-05

We demonstrate the enhancement of resolution and image quality in terahertz (THz) lens-free in-line digital holography by sub-pixel sampling with double-distance reconstruction. Multiple sub-pixel shifted low-resolution (LR) holograms recorded by a pyroelectric array detector (100 μm × 100 μm pixel pitch, 124 × 124 pixels) are aligned precisely to synthesize a high-resolution (HR) hologram. By this method, the lateral resolution is no more limited by the pixel pitch, and lateral resolution of 150 μm is obtained, which corresponds to 1.26λ with respect to the illuminating wavelength of 118.8 μm (2.52 THz). Compared with other published works, to date, this is the highest resolution in THz digital holography when considering the illuminating wavelength. In addition, to suppress the twin-image and zero-order artifacts, the complex amplitude distributions of both object and illuminaing background wave fields are reconstructed simultaneously. This is achieved by iterative phase retrieval between the double HR holograms and background images at two recording planes, which does not require any constraints on object plane or a priori knowledge of the sample.

Microtomography with photon counting detectors: improving the quality of tomographic reconstruction by voxel-space oversampling

NASA Astrophysics Data System (ADS)

Dudak, J.; Zemlicka, J.; Karch, J.; Hermanova, Z.; Kvacek, J.; Krejci, F.

2017-01-01

Photon counting detectors Timepix are known for their unique properties enabling X-ray imaging with extremely high contrast-to-noise ratio. Their applicability has been recently further improved since a dedicated technique for assembling large area Timepix detector arrays was introduced. Despite the fact that the sensitive area of Timepix detectors has been significantly increased, the pixel pitch is kept unchanged (55 microns). This value is much larger compared to widely used and popular X-ray imaging cameras utilizing scintillation crystals and CCD-based read-out. On the other hand, photon counting detectors provide steeper point-spread function. Therefore, with given effective pixel size of an acquired radiography, Timepix detectors provide higher spatial resolution than X-ray cameras with scintillation-based devices unless the image is affected by penumbral blur. In this paper we take an advance of steep PSF of photon counting detectors and test the possibility to improve the quality of computed tomography reconstruction using finer sampling of reconstructed voxel space. The achieved results are presented in comparison with data acquired under the same conditions using a commercially available state-of-the-art CCD X-ray camera.

An improved algorithm to reduce noise in high-order thermal ghost imaging.

PubMed

Chen, Xi-Hao; Wu, Shuang-Shuang; Wu, Wei; Guo, Wang-Yuan; Meng, Shao-Ying; Sun, Zhi-Bin; Zhai, Guang-Jie; Li, Ming-Fei; Wu, Ling-An

2014-09-01

A modified Nth-order correlation function is derived that can effectively remove the noise background encountered in high-order thermal light ghost imaging (GI). Based on this, the quality of the reconstructed images in an Nth-order lensless GI setup has been greatly enhanced compared to former high-order schemes for the same sampling number. In addition, the dependence of the visibility and signal-to-noise ratio for different high-order images on the sampling number has been measured and compared.

Breast reconstruction after mastectomy at a comprehensive cancer center.

PubMed

Connors, Shahnjayla K; Goodman, Melody S; Myckatyn, Terence; Margenthaler, Julie; Gehlert, Sarah

2016-01-01

Breast reconstruction after mastectomy is an integral part of breast cancer treatment that positively impacts quality of life in breast cancer survivors. Although breast reconstruction rates have increased over time, African American women remain less likely to receive breast reconstruction compared to Caucasian women. National Cancer Institute-designated Comprehensive Cancer Centers, specialized institutions with more standardized models of cancer treatment, report higher breast reconstruction rates than primary healthcare facilities. Whether breast reconstruction disparities are reduced for women treated at comprehensive cancer centers is unclear. The purpose of this study was to further investigate breast reconstruction rates and determinants at a comprehensive cancer center in St. Louis, Missouri. Sociodemographic and clinical data were obtained for women who received mastectomy for definitive surgical treatment for breast cancer between 2000 and 2012. Logistic regression was used to identify factors associated with the receipt of breast reconstruction. We found a breast reconstruction rate of 54 % for the study sample. Women who were aged 55 and older, had public insurance, received unilateral mastectomy, and received adjuvant radiation therapy were significantly less likely to receive breast reconstruction. African American women were 30 % less likely to receive breast reconstruction than Caucasian women. These findings suggest that racial disparities in breast reconstruction persist in comprehensive cancer centers. Future research should further delineate the determinants of breast reconstruction disparities across various types of healthcare institutions. Only then can we develop interventions to ensure all eligible women have access to breast reconstruction and the improved quality of life it affords breast cancer survivors.

Real-time demonstration hardware for enhanced DPCM video compression algorithm

NASA Technical Reports Server (NTRS)

Bizon, Thomas P.; Whyte, Wayne A., Jr.; Marcopoli, Vincent R.

1992-01-01

The lack of available wideband digital links as well as the complexity of implementation of bandwidth efficient digital video CODECs (encoder/decoder) has worked to keep the cost of digital television transmission too high to compete with analog methods. Terrestrial and satellite video service providers, however, are now recognizing the potential gains that digital video compression offers and are proposing to incorporate compression systems to increase the number of available program channels. NASA is similarly recognizing the benefits of and trend toward digital video compression techniques for transmission of high quality video from space and therefore, has developed a digital television bandwidth compression algorithm to process standard National Television Systems Committee (NTSC) composite color television signals. The algorithm is based on differential pulse code modulation (DPCM), but additionally utilizes a non-adaptive predictor, non-uniform quantizer and multilevel Huffman coder to reduce the data rate substantially below that achievable with straight DPCM. The non-adaptive predictor and multilevel Huffman coder combine to set this technique apart from other DPCM encoding algorithms. All processing is done on a intra-field basis to prevent motion degradation and minimize hardware complexity. Computer simulations have shown the algorithm will produce broadcast quality reconstructed video at an average transmission rate of 1.8 bits/pixel. Hardware implementation of the DPCM circuit, non-adaptive predictor and non-uniform quantizer has been completed, providing realtime demonstration of the image quality at full video rates. Video sampling/reconstruction circuits have also been constructed to accomplish the analog video processing necessary for the real-time demonstration. Performance results for the completed hardware compare favorably with simulation results. Hardware implementation of the multilevel Huffman encoder/decoder is currently under development along with implementation of a buffer control algorithm to accommodate the variable data rate output of the multilevel Huffman encoder. A video CODEC of this type could be used to compress NTSC color television signals where high quality reconstruction is desirable (e.g., Space Station video transmission, transmission direct-to-the-home via direct broadcast satellite systems or cable television distribution to system headends and direct-to-the-home).

Task-based statistical image reconstruction for high-quality cone-beam CT

NASA Astrophysics Data System (ADS)

Dang, Hao; Webster Stayman, J.; Xu, Jennifer; Zbijewski, Wojciech; Sisniega, Alejandro; Mow, Michael; Wang, Xiaohui; Foos, David H.; Aygun, Nafi; Koliatsos, Vassilis E.; Siewerdsen, Jeffrey H.

2017-11-01

Task-based analysis of medical imaging performance underlies many ongoing efforts in the development of new imaging systems. In statistical image reconstruction, regularization is often formulated in terms to encourage smoothness and/or sharpness (e.g. a linear, quadratic, or Huber penalty) but without explicit formulation of the task. We propose an alternative regularization approach in which a spatially varying penalty is determined that maximizes task-based imaging performance at every location in a 3D image. We apply the method to model-based image reconstruction (MBIR—viz., penalized weighted least-squares, PWLS) in cone-beam CT (CBCT) of the head, focusing on the task of detecting a small, low-contrast intracranial hemorrhage (ICH), and we test the performance of the algorithm in the context of a recently developed CBCT prototype for point-of-care imaging of brain injury. Theoretical predictions of local spatial resolution and noise are computed via an optimization by which regularization (specifically, the quadratic penalty strength) is allowed to vary throughout the image to maximize local task-based detectability index ({{d}\\prime} ). Simulation studies and test-bench experiments were performed using an anthropomorphic head phantom. Three PWLS implementations were tested: conventional (constant) penalty; a certainty-based penalty derived to enforce constant point-spread function, PSF; and the task-based penalty derived to maximize local detectability at each location. Conventional (constant) regularization exhibited a fairly strong degree of spatial variation in {{d}\\prime} , and the certainty-based method achieved uniform PSF, but each exhibited a reduction in detectability compared to the task-based method, which improved detectability up to ~15%. The improvement was strongest in areas of high attenuation (skull base), where the conventional and certainty-based methods tended to over-smooth the data. The task-driven reconstruction method presents a promising regularization method in MBIR by explicitly incorporating task-based imaging performance as the objective. The results demonstrate improved ICH conspicuity and support the development of high-quality CBCT systems.

Video Capture of Plastic Surgery Procedures Using the GoPro HERO 3+

PubMed Central

Graves, Steven Nicholas; Shenaq, Deana Saleh; Langerman, Alexander J.

2015-01-01

Background: Significant improvements can be made in recoding surgical procedures, particularly in capturing high-quality video recordings from the surgeons’ point of view. This study examined the utility of the GoPro HERO 3+ Black Edition camera for high-definition, point-of-view recordings of plastic and reconstructive surgery. Methods: The GoPro HERO 3+ Black Edition camera was head-mounted on the surgeon and oriented to the surgeon’s perspective using the GoPro App. The camera was used to record 4 cases: 2 fat graft procedures and 2 breast reconstructions. During cases 1-3, an assistant remotely controlled the GoPro via the GoPro App. For case 4 the GoPro was linked to a WiFi remote, and controlled by the surgeon. Results: Camera settings for case 1 were as follows: 1080p video resolution; 48 fps; Protune mode on; wide field of view; 16:9 aspect ratio. The lighting contrast due to the overhead lights resulted in limited washout of the video image. Camera settings were adjusted for cases 2-4 to a narrow field of view, which enabled the camera’s automatic white balance to better compensate for bright lights focused on the surgical field. Cases 2-4 captured video sufficient for teaching or presentation purposes. Conclusions: The GoPro HERO 3+ Black Edition camera enables high-quality, cost-effective video recording of plastic and reconstructive surgery procedures. When set to a narrow field of view and automatic white balance, the camera is able to sufficiently compensate for the contrasting light environment of the operating room and capture high-resolution, detailed video. PMID:25750851

Dose reduction with adaptive statistical iterative reconstruction for paediatric CT: phantom study and clinical experience on chest and abdomen CT.

PubMed

Gay, F; Pavia, Y; Pierrat, N; Lasalle, S; Neuenschwander, S; Brisse, H J

2014-01-01

To assess the benefit and limits of iterative reconstruction of paediatric chest and abdominal computed tomography (CT). The study compared adaptive statistical iterative reconstruction (ASIR) with filtered back projection (FBP) on 64-channel MDCT. A phantom study was first performed using variable tube potential, tube current and ASIR settings. The assessed image quality indices were the signal-to-noise ratio (SNR), the noise power spectrum, low contrast detectability (LCD) and spatial resolution. A clinical retrospective study of 26 children (M:F = 14/12, mean age: 4 years, range: 1-9 years) was secondarily performed allowing comparison of 18 chest and 14 abdominal CT pairs, one with a routine CT dose and FBP reconstruction, and the other with 30 % lower dose and 40 % ASIR reconstruction. Two radiologists independently compared the images for overall image quality, noise, sharpness and artefacts, and measured image noise. The phantom study demonstrated a significant increase in SNR without impairment of the LCD or spatial resolution, except for tube current values below 30-50 mA. On clinical images, no significant difference was observed between FBP and reduced dose ASIR images. Iterative reconstruction allows at least 30 % dose reduction in paediatric chest and abdominal CT, without impairment of image quality. • Iterative reconstruction helps lower radiation exposure levels in children undergoing CT. • Adaptive statistical iterative reconstruction (ASIR) significantly increases SNR without impairing spatial resolution. • For abdomen and chest CT, ASIR allows at least a 30 % dose reduction.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

Analyzing spatial variability of soil properties in the urban park before and after reconstruction to support decision-making in landscaping

NASA Astrophysics Data System (ADS)

Romzaikina, Olga; Vasenev, Viacheslav; Khakimova, Rita

2017-04-01

On-going urbanization stresses a necessity for structural and aesthetically organized urban landscapes to improve citizen's life quality. Urban soils and vegetation are the main components of urban ecosystems. Urban greenery regulates the climate, controls and air quality and supports biodiversity in urban areas. Soils play a key role in supporting urban greenery. However, soils of urban parks also perform other important environmental functions. Urban soils are influenced by a variety of environmental and anthropogenic factors and, in the result, are highly heterogeneous and dynamic. Reconstructions of green zones and urban parks, usually occurring in cities, alter soil properties. Analyzing spatial variability and dynamics of soil properties is important to support decision-making in landscaping. Therefore, the research aimed to analyze the spatial distribution of the key soil properties (acidity, soil organic carbon (SOC) and nutrient contents) in the urban park before and after reconstruction to support decision-making in selecting ornamental plants for landscaping. The research was conducted in the urban park named after Artyom Borovik in Moscow before (2012) and after (2014) the reconstruction. Urban soil's properties maps for both periods were created by interpolation of the field data. The observed urban soils included recreazems, urbanozems and constuctozems. Before the reconstruction soils were sampled using the uniform design (the net with 100 m side and key plots with 50m size). After the reconstructions the additional samples were collected at locations, where the land cover and functional zones changed in a result of the reconstruction.We sample from the depths 0-30, 30-50 and 50-100 cm. The following soil properties were measured: pH, SOC, K2O and P2O5. The maps of the analyzed properties were developed using open QGIS2.4 software by IDW. The vegetation in the park was examined using the scale of the visual assessment. The results of the visual assessment were processed using QGIS2.4 and the maps of the vegetation condition were created. High spatial variability was shown for observed soil properties with the highest variance reported for nutrient concentrations. High heterogeneity in P2O5 and K2O was obtained both in topsoil and subsoil, before and after reconstruction. We showed that average concentrations of P2O5 and K2O were correspondingly above and below legal threshold taken for the Moscow city. In result of the reconstruction the pH has changed from slightly acid and acidic to neutral and slightly alkaline. The topsoil SOC content has increased in the result of reconstruction but still was below threshold, recommended by municipal regulations. The potassium content and acidity were the main factors, influencing the vegetation condition. The 'weakened' condition of wood vegetation was reported with the lowest values obtained for the Pinus sylvestris, Thuja occidentals and, Sorbus aucuparia. References have developed for planting vegetation. The spatial heterogeneity and high dynamics of urban soils constraints the quantitative assessment of their properties and functions and the use of this information in landscaping. The successful experience of digital soil mapping techniques in urban park allowed solving this problem and highlighted the importance of soil data for creating urban green infrastructure.

Clinical evaluation of reducing acquisition time on single-photon emission computed tomography image quality using proprietary resolution recovery software.

PubMed

Aldridge, Matthew D; Waddington, Wendy W; Dickson, John C; Prakash, Vineet; Ell, Peter J; Bomanji, Jamshed B

2013-11-01

A three-dimensional model-based resolution recovery (RR) reconstruction algorithm that compensates for collimator-detector response, resulting in an improvement in reconstructed spatial resolution and signal-to-noise ratio of single-photon emission computed tomography (SPECT) images, was tested. The software is said to retain image quality even with reduced acquisition time. Clinically, any improvement in patient throughput without loss of quality is to be welcomed. Furthermore, future restrictions in radiotracer supplies may add value to this type of data analysis. The aims of this study were to assess improvement in image quality using the software and to evaluate the potential of performing reduced time acquisitions for bone and parathyroid SPECT applications. Data acquisition was performed using the local standard SPECT/CT protocols for 99mTc-hydroxymethylene diphosphonate bone and 99mTc-methoxyisobutylisonitrile parathyroid SPECT imaging. The principal modification applied was the acquisition of an eight-frame gated data set acquired using an ECG simulator with a fixed signal as the trigger. This had the effect of partitioning the data such that the effect of reduced time acquisitions could be assessed without conferring additional scanning time on the patient. The set of summed data sets was then independently reconstructed using the RR software to permit a blinded assessment of the effect of acquired counts upon reconstructed image quality as adjudged by three experienced observers. Data sets reconstructed with the RR software were compared with the local standard processing protocols; filtered back-projection and ordered-subset expectation-maximization. Thirty SPECT studies were assessed (20 bone and 10 parathyroid). The images reconstructed with the RR algorithm showed improved image quality for both full-time and half-time acquisitions over local current processing protocols (P<0.05). The RR algorithm improved image quality compared with local processing protocols and has been introduced into routine clinical use. SPECT acquisitions are now acquired at half of the time previously required. The method of binning the data can be applied to any other camera system to evaluate the reduction in acquisition time for similar processes. The potential for dose reduction is also inherent with this approach.

Computer-generated holographic near-eye display system based on LCoS phase only modulator

NASA Astrophysics Data System (ADS)

Sun, Peng; Chang, Shengqian; Zhang, Siman; Xie, Ting; Li, Huaye; Liu, Siqi; Wang, Chang; Tao, Xiao; Zheng, Zhenrong

2017-09-01

Augmented reality (AR) technology has been applied in various areas, such as large-scale manufacturing, national defense, healthcare, movie and mass media and so on. An important way to realize AR display is using computer-generated hologram (CGH), which is accompanied by low image quality and heavy computing defects. Meanwhile, the diffraction of Liquid Crystal on Silicon (LCoS) has a negative effect on image quality. In this paper, a modified algorithm based on traditional Gerchberg-Saxton (GS) algorithm was proposed to improve the image quality, and new method to establish experimental system was used to broaden field of view (FOV). In the experiment, undesired zero-order diffracted light was eliminated and high definition 2D image was acquired with FOV broadened to 36.1 degree. We have also done some pilot research in 3D reconstruction with tomography algorithm based on Fresnel diffraction. With the same experimental system, experimental results demonstrate the feasibility of 3D reconstruction. These modifications are effective and efficient, and may provide a better solution in AR realization.

Dynamic intensity-weighted region of interest imaging for conebeam CT

PubMed Central

Pearson, Erik; Pan, Xiaochuan; Pelizzari, Charles

2017-01-01

BACKGROUND Patient dose from image guidance in radiotherapy is small compared to the treatment dose. However, the imaging beam is untargeted and deposits dose equally in tumor and healthy tissues. It is desirable to minimize imaging dose while maintaining efficacy. OBJECTIVE Image guidance typically does not require full image quality throughout the patient. Dynamic filtration of the kV beam allows local control of CT image noise for high quality around the target volume and lower quality elsewhere, with substantial dose sparing and reduced scatter fluence on the detector. METHODS The dynamic Intensity-Weighted Region of Interest (dIWROI) technique spatially varies beam intensity during acquisition with copper filter collimation. Fluence is reduced by 95% under the filters with the aperture conformed dynamically to the ROI during cone-beam CT scanning. Preprocessing to account for physical effects of the collimator before reconstruction is described. RESULTS Reconstructions show image quality comparable to a standard scan in the ROI, with higher noise and streak artifacts in the outer region but still adequate quality for patient localization. Monte Carlo modeling shows dose reduction by 10–15% in the ROI due to reduced scatter, and up to 75% outside. CONCLUSIONS The presented technique offers a method to reduce imaging dose by accepting increased image noise outside the ROI, while maintaining full image quality inside the ROI. PMID:27257875

Effects of silicone expanders and implants on echocardiographic image quality after breast reconstruction.

PubMed

Pignatti, Marco; Mantovani, Francesca; Bertelli, Luca; Barbieri, Andrea; Pacchioni, Lucrezia; Loschi, Pietro; De Santis, Giorgio

2013-08-01

Use of silicone expanders and implants is the most common breast reconstruction technique after mastectomy. Postmastectomy patients often need echocardiographic monitoring of potential cardiotoxicity induced by cancer chemotherapy. The impairment of the echocardiographic acoustic window caused by silicone implants for breast augmentation has been reported. This study investigates whether the echocardiographic image quality was impaired in women reconstructed with silicone expanders and implants. The records of 44 consecutive women who underwent echocardiographic follow-up after breast reconstruction with expanders and implants at the authors' institution from January of 2000 to August of 2012 were reviewed. The population was divided into a study group (left or bilateral breast expanders/implants, n=30) and a control group (right breast expanders/implants, n=14). The impact of breast expanders/implants on echocardiographic image quality was tested (analysis of covariance model). Patients with a breast expander/implant (left or bilateral and right breast expanders/implants) were included. The mean volume of the breast devices was 353.2±125.5 cc. The quality of the echocardiographic images was good or sufficient in the control group; in the study group, it was judged as adequate in only 50 percent of cases (15 patients) and inadequate in the remaining 15 patients (p<0.001). At multivariable analysis, a persistent relationship between device position (left versus right) and image quality (p=0.001) was shown, independent from other factors. Silicone expanders and implants in postmastectomy left breast reconstruction considerably reduce the image quality of echocardiography. This may have important clinical implications, given the need for periodic echocardiographic surveillance before and during chemotherapy. Therapeutic, III.

Effect of masking phase-only holograms on the quality of reconstructed images.

PubMed

Deng, Yuanbo; Chu, Daping

2016-04-20

A phase-only hologram modulates the phase of the incident light and diffracts it efficiently with low energy loss because of the minimum absorption. Much research attention has been focused on how to generate phase-only holograms, and little work has been done to understand the effect and limitation of their partial implementation, possibly due to physical defects and constraints, in particular as in the practical situations where a phase-only hologram is confined or needs to be sliced or tiled. The present study simulates the effect of masking phase-only holograms on the quality of reconstructed images in three different scenarios with different filling factors, filling positions, and illumination intensity profiles. Quantitative analysis confirms that the width of the image point spread function becomes wider and the image quality decreases, as expected, when the filling factor decreases, and the image quality remains the same for different filling positions as well. The width of the image point spread function as derived from different filling factors shows a consistent behavior to that as measured directly from the reconstructed image, especially as the filling factor becomes small. Finally, mask profiles of different shapes and intensity distributions are shown to have more complicated effects on the image point spread function, which in turn affects the quality and textures of the reconstructed image.

Penalized maximum likelihood reconstruction for x-ray differential phase-contrast tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brendel, Bernhard, E-mail: bernhard.brendel@philips.com; Teuffenbach, Maximilian von; Noël, Peter B.

2016-01-15

Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods: We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penaltymore » comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts.« less

PSF reconstruction for Compton-based prompt gamma imaging

NASA Astrophysics Data System (ADS)

Jan, Meei-Ling; Lee, Ming-Wei; Huang, Hsuan-Ming

2018-02-01

Compton-based prompt gamma (PG) imaging has been proposed for in vivo range verification in proton therapy. However, several factors degrade the image quality of PG images, some of which are due to inherent properties of a Compton camera such as spatial resolution and energy resolution. Moreover, Compton-based PG imaging has a spatially variant resolution loss. In this study, we investigate the performance of the list-mode ordered subset expectation maximization algorithm with a shift-variant point spread function (LM-OSEM-SV-PSF) model. We also evaluate how well the PG images reconstructed using an SV-PSF model reproduce the distal falloff of the proton beam. The SV-PSF parameters were estimated from simulation data of point sources at various positions. Simulated PGs were produced in a water phantom irradiated with a proton beam. Compared to the LM-OSEM algorithm, the LM-OSEM-SV-PSF algorithm improved the quality of the reconstructed PG images and the estimation of PG falloff positions. In addition, the 4.44 and 5.25 MeV PG emissions can be accurately reconstructed using the LM-OSEM-SV-PSF algorithm. However, for the 2.31 and 6.13 MeV PG emissions, the LM-OSEM-SV-PSF reconstruction provides limited improvement. We also found that the LM-OSEM algorithm followed by a shift-variant Richardson-Lucy deconvolution could reconstruct images with quality visually similar to the LM-OSEM-SV-PSF-reconstructed images, while requiring shorter computation time.

Three-dimensional shape measurement system applied to superficial inspection of non-metallic pipes for the hydrocarbons transport

NASA Astrophysics Data System (ADS)

Arciniegas, Javier R.; González, Andrés. L.; Quintero, L. A.; Contreras, Carlos R.; Meneses, Jaime E.

2014-05-01

Three-dimensional shape measurement is a subject that consistently produces high scientific interest and provides information for medical, industrial and investigative applications, among others. In this paper, it is proposed to implement a three-dimensional (3D) reconstruction system for applications in superficial inspection of non-metallic pipes for the hydrocarbons transport. The system is formed by a CCD camera, a video-projector and a laptop and it is based on fringe projection technique. System functionality is evidenced by evaluating the quality of three-dimensional reconstructions obtained, which allow observing the failures and defects on the study object surface.

Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pino, Francisco; Roé, Nuria; Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es

2015-02-15

Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Threemore » methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery coefficients in the reconstructed images. To avoid the appearance of ring-type artifacts, the number of iterations should be limited. In low magnification systems, the intrinsic detector PSF plays a major role in improvement of the image-quality parameters.« less

Color quality improvement of reconstructed images in color digital holography using speckle method and spectral estimation

NASA Astrophysics Data System (ADS)

Funamizu, Hideki; Onodera, Yusei; Aizu, Yoshihisa

2018-05-01

In this study, we report color quality improvement of reconstructed images in color digital holography using the speckle method and the spectral estimation. In this technique, an object is illuminated by a speckle field and then an object wave is produced, while a plane wave is used as a reference wave. For three wavelengths, the interference patterns of two coherent waves are recorded as digital holograms on an image sensor. Speckle fields are changed by moving a ground glass plate in an in-plane direction, and a number of holograms are acquired to average the reconstructed images. After the averaging process of images reconstructed from multiple holograms, we use the Wiener estimation method for obtaining spectral transmittance curves in reconstructed images. The color reproducibility in this method is demonstrated and evaluated using a Macbeth color chart film and staining cells of onion.

Measuring and managing patient expectations for breast reconstruction: impact on quality of life and patient satisfaction

PubMed Central

Pusic, Andrea L; Klassen, Anne F; Snell, Laura; Cano, Stefan J; McCarthy, Colleen; Scott, Amie; Cemal, Yeliz; Rubin, Lisa R; Cordeiro, Peter G

2014-01-01

The goal of postmastectomy breast reconstruction is to restore a woman’s body image and to satisfy her personal expectations regarding the results of surgery. Studies in other surgical areas have shown that unrecognized or unfulfilled expectations may predict dissatisfaction more strongly than even the technical success of the surgery. Patient expectations play an especially critical role in elective procedures, such as cancer reconstruction, where the patient’s primary motivation is improved health-related quality of life. In breast reconstruction, assessment of patient expectations is therefore vital to optimal patient care. This report summarizes the existing literature on patient expectations regarding breast reconstruction, and provides a viewpoint on how this field can evolve. Specifically, we consider how systematic measurement and management of patient expectations may improve patient education, shared medical decision-making and patient perception of outcomes. PMID:22458616

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Heteroepitaxial Growth of Ferromagnetic MnSb(0001) Films on Ge/Si(111) Virtual Substrates.

PubMed

Burrows, Christopher W; Dobbie, Andrew; Myronov, Maksym; Hase, Thomas P A; Wilkins, Stuart B; Walker, Marc; Mudd, James J; Maskery, Ian; Lees, Martin R; McConville, Christopher F; Leadley, David R; Bell, Gavin R

2013-11-06

Molecular beam epitaxial growth of ferromagnetic MnSb(0001) has been achieved on high quality, fully relaxed Ge(111)/Si(111) virtual substrates grown by reduced pressure chemical vapor deposition. The epilayers were characterized using reflection high energy electron diffraction, synchrotron hard X-ray diffraction, X-ray photoemission spectroscopy, and magnetometry. The surface reconstructions, magnetic properties, crystalline quality, and strain relaxation behavior of the MnSb films are similar to those of MnSb grown on GaAs(111). In contrast to GaAs substrates, segregation of substrate atoms through the MnSb film does not occur, and alternative polymorphs of MnSb are absent.

Quality of life in women following various surgeries of body manipulation: organ transplantation, mastectomy, and breast reconstruction.

PubMed

Pérez-San-Gregorio, M Angeles; Fernández-Jiménez, Eduardo; Martín-Rodríguez, Agustín; Borda-Más, Mercedes; Rincón-Fernández, M Esther

2013-09-01

This study aimed to determine biopsychosocial differences (anxious-depressive symptomatology and quality of life) among three groups of patients who underwent surgical interventions related to body manipulation, as well as to assess the clinical significance of these results versus reference values. Four groups were compared: women who underwent organ transplant (n = 26), mastectomy for breast cancer (n = 36), breast reconstruction (n = 36), and general population (n = 608). The Hospital Anxiety and Depression Scale and the EORTC QLQ-C30 were used. Women who underwent mastectomy showed the highest anxious-depressive symptomatology and quality-of-life impairment in comparison to the remaining groups, and they also displayed the most clinically significant deterioration in the majority of dimensions (large effect sizes). In contrast, the group with implantation of a healthy organ (transplantation) only showed higher biopsychosocial impairment than the group with reconstruction of an organ (breast reconstruction) in gastrointestinal dysfunctions and in the global self-perception of health.

Computed Tomography Imaging of a Hip Prosthesis Using Iterative Model-Based Reconstruction and Orthopaedic Metal Artefact Reduction: A Quantitative Analysis.

PubMed

Wellenberg, Ruud H H; Boomsma, Martijn F; van Osch, Jochen A C; Vlassenbroek, Alain; Milles, Julien; Edens, Mireille A; Streekstra, Geert J; Slump, Cornelis H; Maas, Mario

To quantify the combined use of iterative model-based reconstruction (IMR) and orthopaedic metal artefact reduction (O-MAR) in reducing metal artefacts and improving image quality in a total hip arthroplasty phantom. Scans acquired at several dose levels and kVps were reconstructed with filtered back-projection (FBP), iterative reconstruction (iDose) and IMR, with and without O-MAR. Computed tomography (CT) numbers, noise levels, signal-to-noise-ratios and contrast-to-noise-ratios were analysed. Iterative model-based reconstruction results in overall improved image quality compared to iDose and FBP (P < 0.001). Orthopaedic metal artefact reduction is most effective in reducing severe metal artefacts improving CT number accuracy by 50%, 60%, and 63% (P < 0.05) and reducing noise by 1%, 62%, and 85% (P < 0.001) whereas improving signal-to-noise-ratios by 27%, 47%, and 46% (P < 0.001) and contrast-to-noise-ratios by 16%, 25%, and 19% (P < 0.001) with FBP, iDose, and IMR, respectively. The combined use of IMR and O-MAR strongly improves overall image quality and strongly reduces metal artefacts in the CT imaging of a total hip arthroplasty phantom.

Improved Compressive Sensing of Natural Scenes Using Localized Random Sampling

PubMed Central

Barranca, Victor J.; Kovačič, Gregor; Zhou, Douglas; Cai, David

2016-01-01

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, localized random sampling, which yields significantly improved CS image reconstructions. For each set of localized image measurements, our sampling method first randomly selects an image pixel and then measures its nearby pixels with probability depending on their distance from the initially selected pixel. We compare the uniformly-random and localized random sampling methods over a large space of sampling parameters, and show that, for the optimal parameter choices, higher quality image reconstructions can be consistently obtained by using localized random sampling. In addition, we argue that the localized random CS optimal parameter choice is stable with respect to diverse natural images, and scales with the number of samples used for reconstruction. We expect that the localized random sampling protocol helps to explain the evolutionarily advantageous nature of receptive field structure in visual systems and suggests several future research areas in CS theory and its application to brain imaging. PMID:27555464

Dietary quality and encephalization in platyrrhine primates.

PubMed

Allen, Kari L; Kay, Richard F

2012-02-22

The high energetic costs of building and maintaining large brains are thought to constrain encephalization. The 'expensive-tissue hypothesis' (ETH) proposes that primates (especially humans) overcame this constraint through reduction of another metabolically expensive tissue, the gastrointestinal tract. Small guts characterize animals specializing on easily digestible diets. Thus, the hypothesis may be tested via the relationship between brain size and diet quality. Platyrrhine primates present an interesting test case, as they are more variably encephalized than other extant primate clades (excluding Hominoidea). We find a high degree of phylogenetic signal in the data for diet quality, endocranial volume and body size. Controlling for phylogenetic effects, we find no significant correlation between relative diet quality and relative endocranial volume. Thus, diet quality fails to account for differences in platyrrhine encephalization. One taxon, in particular, Brachyteles, violates predictions made by ETH in having a large brain and low-quality diet. Dietary reconstructions of stem platyrrhines further indicate that a relatively high-quality diet was probably in place prior to increases in encephalization. Therefore, it is unlikely that a shift in diet quality was a primary constraint release for encephalization in platyrrhines and, by extrapolation, humans.

ECG-triggered high-pitch CT for simultaneous assessment of the aorta and coronary arteries.

PubMed

Hachulla, Anne-Lise; Ronot, Maxime; Noble, Stéphane; Becker, Christoph D; Montet, Xavier; Vallée, Jean-Paul

2016-01-01

To study the image quality of ECG-gated-computed tomography (CT) acquisition with a high-pitch CT imaging for the exploration of both the aorta and coronary arteries. Eighty-four patients underwent high-pitch ECG-gated aortic CT without β-blockers with iterative reconstruction algorithms. Contrast-to-noise ratio (CNR) between vessels and adjacent perivascular fat tissue were calculated on the aorta and the coronary arteries. Dose-length-products (DLP) were recorded. Two blinded readers graded image quality of the aorta and the coronary arteries on a 3-point scale. Coronary artery stenoses were compared with coronary angiograms in 24 patients. Kappa values were calculated. High-pitch acquisition resulted in a mean DLP of 234 ± 93 mGy cm(4.2 mSv) for an acquisition of the entire aorta, (mean 73 ± 16 bpm). CNR for ascending aorta was 10.6 ± 4 and CNR for coronary arteries was 9.85 ± 4.1. Image quality was excellent in 79/84 patients (94%), and excellent or moderate but diagnostic in 1087/1127 coronary artery segments (96%). 74 significant stenoses were observed, and 38/40 significant stenoses were confirmed by coronary angiography (K = 0.91, Sensitivity = 0.97, Specificity = 0.98). High-pitch ECG-gated aortic CT with iterative reconstructions allows an accurate exploration of both aorta and coronary arteries during the same acquisition, with limited dose deposition, despite the lack of β-blockers and relatively high heart rate. Radiologists need to be aware of the necessity to analyze and report coronary artery disease in aortic examination. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Quality of life among patients after bilateral prophylactic mastectomy: A systematic review of patient reported outcomes

PubMed Central

Razdan, Shantanu N.; Patel, Vishal; Jewell, Sarah; McCarthy, Colleen M.

2016-01-01

Purpose Bilateral prophylactic mastectomy (BPM) is effective in reducing the risk of breast cancer in women with a well-defined family history of breast cancer or in women with BRCA 1 or 2 mutations. Evaluating patient-reported outcomes following BPM are thus essential for evaluating success of BPM from patient’s perspective. Our systematic review aimed to: (1) identify studies describing health-related quality of life (HRQOL) in patients following BPM with or without reconstruction; (2) assess the effect of BPM with or without reconstruction on HRQOL; and, (3) identify predictors of HRQOL post BPM. Methods We performed a systematic review of literature using the PRISMA guidelines. PubMed, Embase, PsycINFO, Web of Science, Scopus and Cochrane databases were searched. Results The initial search resulted in 1082 studies; 22 of these studies fulfilled our inclusion criteria. Post BPM, patients are satisfied with the outcomes and report high psychosocial well-being and positive body image. Sexual well-being and somatosensory function are most negatively affected. Vulnerability, psychological distress and preoperative cancer distress are significant negative predictors of quality of life and body image post BPM. Conclusion There is a paucity of high quality data on outcomes of different HRQOL domains post BPM. Future studies should strive to use validated and breast-specific PRO instruments for measuring HRQOL. This will facilitate shared decision-making by enabling surgeons to provide evidence-based answers to women contemplating BPM. PMID:26577764

INFLUENCE OF DIFFERENT LEVELS OF SPORTS ACTIVITIES ON THE QUALITY OF LIFE AFTER THE RECONSTRUCTION OF ANTERIOR CRUCIATE LIGAMENT.

PubMed

Ninković, Srđan; Avramov, Snežana; Harhaji, Vladimir; Obradović, Mirko; Vranješ, Miodrag; Milankov, Miroslav

2015-01-01

The goal of this study was to examine the nature and presence of influence of different levels of sports activity on the life quality of the patients a year after the reconstruction of anterior cruciate ligament. The study included 185 patients operated at the Department of Orthopedic Surgery and Traumatology of the Clinical Centre of Vojvodina, who were followed for twelve months. Data were collected using the modified Knee Injury and Osteoarthritis Outcome Score questionnaire which included the Lysholm scale. This study included 146 male and 39 female subjects. The reconstruction of anterior cruciate ligament was equally successful in both gender groups. In relation to different types of sports activity, there were no differences in the overall life quality measured by the questionnaire and its subscales, regardless of the level (professional or recreational). However, regarding the level of sports activities, there were differences among the subjects engaged in sports activities at the national level as compared with those going in for sports activities at the recreational level, and particularly in comparison with physically inactive population. A significant correlation was not found by examining the aforementioned relationship between sports activities. This study has shown that the overall life quality a year after the reconstruction of the anterior cruciate ligament does not differ in relation to either the gender of the subjects or the type of sports activity, while the level of sports activity does have some influence on the quality of life. Professional athletes have proved to train significantly more intensively after this reconstruction than those going in for sports recreationally.

Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

NASA Astrophysics Data System (ADS)

Dong, Jian; Kudo, Hiroyuki

2017-03-01

Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

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.

PubMed

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

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 < 0.05). Adaptive statistical iterative reconstruction-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 <0.0001). Veo 3.0 and ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-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.

Efficacy and safety profile of antibiotic prophylaxis usage in clean and clean-contaminated plastic and reconstructive surgery: a meta-analysis of randomized controlled trials.

PubMed

Zhang, Yi; Dong, Jiasheng; Qiao, Yufei; He, Jinguang; Wang, Tao; Ma, Sunxiang

2014-01-01

There is no consensus with regard to antibiotic prophylaxis usage in clean and clean-contaminated plastic and reconstructive surgery. This meta-analysis sought to assess the efficacy and safety of antibiotic prophylaxis and to determine appropriate duration of prophylaxis. An English language literature search was conducted using PubMed and the Cochrane Collaboration for randomized controlled trials (RCTs) that evaluate the use of antibiotic prophylaxis to prevent postoperative surgical site infection (SSI) in patients undergoing clean and clean-contaminated plastic and reconstructive surgery. Data from intention-to-treat analyses were used where available. For the dichotomous data, results for each study were odds ratio (OR) with 95% confidence interval (CI) and combined for meta-analysis using the Mantel-Haenszel method or the DerSimonian and Laird method. Study quality was critically appraised by 2 reviewers using established criteria. STATA version 12 was used for meta-analyses. Twelve RCTs involving 2395 patients were included, of which 8 trials were considered to be of high methodological quality. Effect of antibiotic prophylaxis in plastic and reconstructive surgery was found favorable over placebo in SSI prevention (13 studies; 2449 participants; OR, 0.53; 95% CI, 0.4-0.7; P < 0.01) and the other wound complication (OWC) prevention (9 studies; 1843 participants; OR, 0.36; 95% CI, 0.15-0.84; P < 0.02). Subgroup analysis performed according to surgical wound type or the duration of prophylaxis did not modify the results except for the OWC with short-term antibiotic treatment. Compared with short-term antibiotic prophylaxis, long-term administration showed no evidence of a difference in risk of SSI (7 studies; 1012 participants; OR, 0.99; 95% CI, 0.63-1.55; P < 0.95), OWC (5 studies; 824 participants; OR, 0.92; 95% CI, 0.46-1.86; P < 0.82), and adverse event relative to antibiotic administration (3 studies; 653 participants; OR, 0.23; 95% CI, 0.01-4.92; P < 0.35). This meta-analysis of RCTs provides evidence supporting that antibiotic prophylaxis reduced postoperative SSI in clean plastic surgeries with high-risk factors and clean-contaminated plastic surgeries. Besides, a short-course administration regimen seemed to be of adequate efficacy and safety. High-quality prospective trials on larger scale are needed to further confirm these findings.

Influence of photon energy cuts on PET Monte Carlo simulation results.

PubMed

Mitev, Krasimir; Gerganov, Georgi; Kirov, Assen S; Schmidtlein, C Ross; Madzhunkov, Yordan; Kawrakow, Iwan

2012-07-01

The purpose of this work is to study the influence of photon energy cuts on the results of positron emission tomography (PET) Monte Carlo (MC) simulations. MC simulations of PET scans of a box phantom and the NEMA image quality phantom are performed for 32 photon energy cut values in the interval 0.3-350 keV using a well-validated numerical model of a PET scanner. The simulations are performed with two MC codes, egs_pet and GEANT4 Application for Tomographic Emission (GATE). The effect of photon energy cuts on the recorded number of singles, primary, scattered, random, and total coincidences as well as on the simulation time and noise-equivalent count rate is evaluated by comparing the results for higher cuts to those for 1 keV cut. To evaluate the effect of cuts on the quality of reconstructed images, MC generated sinograms of PET scans of the NEMA image quality phantom are reconstructed with iterative statistical reconstruction. The effects of photon cuts on the contrast recovery coefficients and on the comparison of images by means of commonly used similarity measures are studied. For the scanner investigated in this study, which uses bismuth germanate crystals, the transport of Bi X(K) rays must be simulated in order to obtain unbiased estimates for the number of singles, true, scattered, and random coincidences as well as for an unbiased estimate of the noise-equivalent count rate. Photon energy cuts higher than 170 keV lead to absorption of Compton scattered photons and strongly increase the number of recorded coincidences of all types and the noise-equivalent count rate. The effect of photon cuts on the reconstructed images and the similarity measures used for their comparison is statistically significant for very high cuts (e.g., 350 keV). The simulation time decreases slowly with the increase of the photon cut. The simulation of the transport of characteristic x rays plays an important role, if an accurate modeling of a PET scanner system is to be achieved. The simulation time decreases slowly with the increase of the cut which, combined with the accuracy loss at high cuts, means that the usage of high photon energy cuts is not recommended for the acceleration of MC simulations.

An image quality comparison study between XVI and OBI CBCT systems.

PubMed

Kamath, Srijit; Song, William; Chvetsov, Alexei; Ozawa, Shuichi; Lu, Haibin; Samant, Sanjiv; Liu, Chihray; Li, Jonathan G; Palta, Jatinder R

2011-02-04

The purpose of this study is to evaluate and compare image quality characteristics for two commonly used and commercially available CBCT systems: the X-ray Volumetric Imager and the On-Board Imager. A commonly used CATPHAN image quality phantom was used to measure various image quality parameters, namely, pixel value stability and accuracy, noise, contrast to noise ratio (CNR), high-contrast resolution, low contrast resolution and image uniformity. For the XVI unit, we evaluated the image quality for four manufacturer-supplied protocols as a function of mAs. For the OBI unit, we did the same for the full-fan and half-fan scanning modes, which were respectively used with the full bow-tie and half bow-tie filters. For XVI, the mean pixel values of regions of interest were found to generally decrease with increasing mAs for all protocols, while they were relatively stable with mAs for OBI. Noise was slightly lower on XVI and was seen to decrease with increasing mAs, while CNR increased with mAs for both systems. For XVI and OBI, the high-contrast resolution was approximately limited by the pixel resolution of the reconstructed image. On OBI images, up to 6 and 5 discs of 1% and 0.5% contrast, respectively, were visible for a high mAs setting using the full-fan mode, while none of the discs were clearly visible on the XVI images for various mAs settings when the medium resolution reconstruction was used. In conclusion, image quality parameters for XVI and OBI have been quantified and compared for clinical protocols under various mAs settings. These results need to be viewed in the context of a recent study that reported the dose-mAs relationship for the two systems and found that OBI generally delivered higher imaging doses than XVI.

Quality of Life in Symptomatic Individuals After Anterior Cruciate Ligament Reconstruction, With and Without Radiographic Knee Osteoarthritis.

PubMed

Filbay, Stephanie R; Ackerman, Ilana N; Dhupelia, Sanjay; Arden, Nigel K; Crossley, Kay M

2018-05-01

Study Design Clinical measurement, cross-sectional. Background Individuals who have undergone anterior cruciate ligament (ACL) reconstruction commonly experience long-term impairments in quality of life (QoL), which may be related to persistent knee symptoms or radiographic osteoarthritis (ROA). Understanding the impact of knee symptoms and ROA on QoL after ACL reconstruction may assist in the development of appropriate management strategies. Objectives To (1) compare QoL between groups of individuals after ACL reconstruction (including those who are symptomatic with ROA, symptomatic without ROA, and asymptomatic [unknown ROA status]), and (2) identify specific aspects of QoL impairment in symptomatic individuals with and without ROA post ACL reconstruction. Methods One hundred thirteen participants completed QoL measures (Knee injury and Osteoarthritis Outcome Score QoL subscale [KOOS-QoL], Anterior Cruciate Ligament Quality of Life [ACL-QoL], Assessment of Quality of Life-8 Dimensions [AQoL-8D]) 5 to 20 years after ACL reconstruction. Eighty-one symptomatic individuals underwent radiographs, and 32 asymptomatic individuals formed a comparison group. Radiographic osteoarthritis was defined as a Kellgren-Lawrence grade of 2 or greater for the tibiofemoral and/or patellofemoral joints. Mann-Whitney U tests compared outcomes between groups. Individual ACL-QoL items were used to explore specific aspects of QoL. Results In symptomatic individuals after ACL reconstruction, ROA was related to worse knee-related outcomes on the KOOS-QoL (median, 50; interquartile range [IQR], 38-69 versus median, 69; IQR, 56-81; P<.001) and the ACL-QoL (median, 51; IQR, 38-71 versus median, 66; IQR, 50-82; P = .04). The AQoL-8D scores showed that health-related QoL was impaired in both symptomatic groups compared to the asymptomatic group. The ACL-QoL item scores revealed greater limitations and concern surrounding sport and exercise and social/emotional difficulties in the symptomatic group with ROA. Conclusion Osteoarthritis is associated with worse knee-related QoL in symptomatic individuals after ACL reconstruction. Diagnosing ROA in symptomatic individuals after ACL reconstruction may be valuable, because these individuals may require unique management. Targeted strategies to facilitate participation in satisfying activities have potential to improve QoL in symptomatic people with ROA after ACL reconstruction. J Orthop Sports Phys Ther 2018;48(5):398-408. doi:10.2519/jospt.2018.7830.

Single-shot spiral imaging at 7 T.

PubMed

Engel, Maria; Kasper, Lars; Barmet, Christoph; Schmid, Thomas; Vionnet, Laetitia; Wilm, Bertram; Pruessmann, Klaas P

2018-03-25

The purpose of this work is to explore the feasibility and performance of single-shot spiral MRI at 7 T, using an expanded signal model for reconstruction. Gradient-echo brain imaging is performed on a 7 T system using high-resolution single-shot spiral readouts and half-shot spirals that perform dual-image acquisition after a single excitation. Image reconstruction is based on an expanded signal model including the encoding effects of coil sensitivity, static off-resonance, and magnetic field dynamics. The latter are recorded concurrently with image acquisition, using NMR field probes. The resulting image resolution is assessed by point spread function analysis. Single-shot spiral imaging is achieved at a nominal resolution of 0.8 mm, using spiral-out readouts of 53-ms duration. High depiction fidelity is achieved without conspicuous blurring or distortion. Effective resolutions are assessed as 0.8, 0.94, and 0.98 mm in CSF, gray matter and white matter, respectively. High image quality is also achieved with half-shot acquisition yielding image pairs at 1.5-mm resolution. Use of an expanded signal model enables single-shot spiral imaging at 7 T with unprecedented image quality. Single-shot and half-shot spiral readouts deploy the sensitivity benefit of high field for rapid high-resolution imaging, particularly for functional MRI and arterial spin labeling. © 2018 International Society for Magnetic Resonance in Medicine.

Application of EARL (ResEARch 4 Life®) protocols for [18F]FDG-PET/CT clinical and research studies. A roadmap towards exact recovery coefficient

NASA Astrophysics Data System (ADS)

Balcerzyk, Marcin; Fernández-López, Rosa; Parrado-Gallego, Ángel; Pachón-Garrudo, Víctor Manuel; Chavero-Royan, José; Hevilla, Juan; Jiménez-Ortega, Elisa; Leal, Antonio

2017-11-01

Tumour uptake value is a critical result in [18F]FDG-PET/CT ([18F]fluorodeoxyglucose) quantitative scans such as the dose prescription for radiotherapy and oncology. The quantification is highly dependent on the protocol of acquisition and reconstruction of the image, especially in low activity tumours. During adjusting acquisition and reconstruction protocols available in our Siemens Biograph mCT scanner for EARL (ResEARch 4 Life®) [18F]FDG-PET/CT accreditation requirements, we developed reconstruction protocols which will be used in PET based radiotherapy planning able to reduce inter-/intra-institute variability in Standard Uptake Value (SUV) results, and to bring Recovery Coefficient to 1 as close as possible for Image Quality NEMA 2007 phantom. Primary and secondary tumours from two patients were assessed by four independent evaluators. The influence of reconstruction protocols on tumour clinical assessment was presented. We proposed the improvement route for EARL accredited protocols so that they may be developed in classes to take advantage of scanner possibilities. The application of optimized reconstruction protocol eliminates the need of partial volume corrections.

Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

NASA Astrophysics Data System (ADS)

Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

2018-06-01

Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.