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iterative model reconstruction

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https://www.readbyqxmd.com/read/28910696/tissue-microstructure-estimation-using-a-deep-network-inspired-by-a-dictionary-based-framework
#1
Chuyang Ye
Diffusion magnetic resonance imaging (dMRI) captures the anisotropic pattern of water displacement in the neuronal tissue and allows noninvasive investigation of the complex tissue microstructure. A number of biophysical models have been proposed to relate the tissue organization with the observed diffusion signals, so that the tissue microstructure can be inferred. The Neurite Orientation Dispersion and Density Imaging (NODDI) model has been a popular choice and has been widely used for many neuroscientific studies...
September 6, 2017: Medical Image Analysis
https://www.readbyqxmd.com/read/28901614/investigating-simulation-based-metrics-for-characterizing-linear-iterative-reconstruction-in-digital-breast-tomosynthesis
#2
Sean D Rose, Adrian A Sanchez, Emil Y Sidky, Xiaochuan Pan
PURPOSE: Simulation-based image quality metrics are adapted and investigated for characterizing the parameter dependences of linear iterative image reconstruction for DBT. METHODS: Three metrics based on a 2D DBT simulation are investigated: (1) a root-mean-square-error (RMSE) between the test phantom and reconstructed image, (2) a gradient RMSE where the comparison is made after taking a spatial gradient of both image and phantom, and (3) a region-of-interest (ROI) Hotelling observer (HO) for signal-known-exactly/background-known-exactly (SKE/BKE) and signal-known-exactly/background-known-statistically (SKE/BKS) detection tasks...
September 2017: Medical Physics
https://www.readbyqxmd.com/read/28901610/low-dose-dynamic-myocardial-perfusion-ct-imaging-using-a-motion-adaptive-sparsity-prior
#3
Zhaoying Bian, Dong Zeng, Zhang Zhang, Changfei Gong, Xiumei Tian, Gang Yan, Jing Huang, Hong Guo, Bo Chen, Jing Zhang, Qianjin Feng, Wufan Chen, Jianhua Ma
PURPOSE: Dynamic myocardial perfusion computed tomography (DM-PCT) imaging offers benefits over quantitative assessment of myocardial blood flow (MBF) for diagnosis and risk stratification of coronary artery disease. However, one major drawback of DM-PCT imaging is that a high radiation level is imparted by repeated scanning. To address this issue, in this work, we developed a statistical iterative reconstruction algorithm based on the penalized weighted least-squares (PWLS) scheme by incorporating a motion adaptive sparsity prior (MASP) model to achieve high-quality DM-PCT imaging with low tube current dynamic data acquisition...
September 2017: Medical Physics
https://www.readbyqxmd.com/read/28870227/cone-beam-ct-reconstruction-for-non-periodic-organ-motion-using-time-ordered-chain-graph-model
#4
Masahiro Nakano, Akihiro Haga, Jun'ichi Kotoku, Taiki Magome, Yoshitaka Masutani, Shouhei Hanaoka, Satoshi Kida, Keiichi Nakagawa
PURPOSE: The purpose of this study is to introduce the new concept of a four-dimensional (4D) cone-beam computed tomography (CBCT) reconstruction approach for non-periodic organ motion in cooperation with the time-ordered chain graph model (TCGM) and to compare it with previously developed methods such as total variation-based compressed sensing (TVCS) and prior-image constrained compressed sensing (PICCS). MATERIALS AND METHODS: Our proposed reconstruction is based on a model including the constraint originating from the images of neighboring time phases...
September 4, 2017: Radiation Oncology
https://www.readbyqxmd.com/read/28862350/reconstruction-by-calibration-over-tensors-for-multi-coil-multi-acquisition-balanced-ssfp-imaging
#5
Erdem Biyik, Efe Ilicak, Tolga Çukur
PURPOSE: To develop a rapid imaging framework for balanced steady-state free precession (bSSFP) that jointly reconstructs undersampled data (by a factor of R) across multiple coils (D) and multiple acquisitions (N). To devise a multi-acquisition coil compression technique for improved computational efficiency. METHODS: The bSSFP image for a given coil and acquisition is modeled to be modulated by a coil sensitivity and a bSSFP profile. The proposed reconstruction by calibration over tensors (ReCat) recovers missing data by tensor interpolation over the coil and acquisition dimensions...
September 1, 2017: Magnetic Resonance in Medicine: Official Journal of the Society of Magnetic Resonance in Medicine
https://www.readbyqxmd.com/read/28856413/could-new-reconstruction-ct-techniques-challenge-mri-for-the-detection-of-brain-metastases-in-the-context-of-initial-lung-cancer-staging
#6
Domitille Millon, David Byl, Philippe Collard, Samantha E Cambier, Aline G Van Maanen, Alain Vlassenbroek, Emmanuel E Coche
OBJECTIVES: To evaluate the diagnostic performance of brain CT images reconstructed with a model-based iterative algorithm performed at usual and reduced dose. METHODS: 115 patients with histologically proven lung cancer were prospectively included over 15 months. Patients underwent two CT acquisitions at the initial staging, performed on a 256-slice MDCT, at standard (CTDIvol: 41.4 mGy) and half dose (CTDIvol: 20.7 mGy). Both image datasets were reconstructed with filtered back projection (FBP) and iterative model-based reconstruction (IMR) algorithms...
August 30, 2017: European Radiology
https://www.readbyqxmd.com/read/28830200/assessment-of-structural-similarity-in-ct-using-filtered-backprojection-and-iterative-reconstruction-a-phantom-study-with-3d-printed-lung-vessels
#7
Raoul Ms Joemai, Jacob Geleijns
OBJECTIVE: To compare the performance of three generations of CT reconstruction techniques using structural similarity (SSIM) as a measure of image quality for CT scans of a chest phantom with 3D printed lung vessels. METHODS: CT images of the chest phantom were acquired at seven dose levels by changing the tube current while other acquisition parameters were kept constant. Three CT reconstruction techniques were applied on each acquisition. The first technique was Filtered Backprojection (FBP), the second technique was FBP with iterative filtering (AIDR 3D) and the third technique was model-based iterative reconstruction (FIRST)...
August 22, 2017: British Journal of Radiology
https://www.readbyqxmd.com/read/28829308/a-look-up-table-based-ray-integration-framework-for-2d-3d-forward-and-back-projection-in-x-ray-ct
#8
Sungsoo Ha, Klaus Mueller
Iterative algorithms have become increasingly popular in Computed Tomography (CT) image reconstruction since they better deal with the adverse image artifacts arising from low radiation dose image acquisition. But iterative methods remain computationally expensive. The main cost emerges in the projection and backprojection operations where accurate CT system modeling can greatly improve the quality of the reconstructed image. We present a framework that improves upon one particular aspect - the accurate projection of the image basis functions...
August 18, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28829306/physics-model-based-scatter-correction-in-multi-source-interior-computed-tomography
#9
Hao Gong, Bin Li, Xun Jia, Guohua Gao
Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware based scatter correction methods for multi-source interior CT. Here, we propose a software based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework...
August 17, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28826857/3d-reconstruction-of-human-bones-based-on-dictionary-learning
#10
Binkai Zhang, Xiang Wang, Xiao Liang, Jinjin Zheng
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...
August 18, 2017: Medical Engineering & Physics
https://www.readbyqxmd.com/read/28816669/nonlocally-multi-morphological-representation-for-image-reconstruction-from-compressive-measurements
#11
Jiao Wu, Feilong Cao, Juncheng Yin
A novel multi-morphological representation model for solving the nonlocal similarity-based image reconstruction from compressed measurements is introduced in this paper. Under the probabilistic framework, the proposed approach provides the nonlocal similarity clustering for image patches by using the Gaussian mixture models, and endows a multimorphological representation for image patches in each cluster by using the Gaussians that represent the different features to model the morphological components. Using the simple alternating iteration, the developed piecewise morphological diversity estimation (PMDE) algorithm can effectively estimate the MAP of morphological components, thus resulting in the nonlinear estimation for image patches...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28809683/low-rank-latent-pattern-approximation-with-applications-to-robust-image-classification
#12
Shuo Chen, Jian Yang, Lei Luo, Yang Wei, Kaihua Zhang, Ying Tai
This paper develops a novel method to address the structural noise in samples for image classification. Recently, regression related classification methods have shown promising results when facing the pixel-wise noise. However, they become weak in coping with the structural noise due to ignoring of relationships between pixels of noise image. Meanwhile, most of them need to implement the iterative process for computing representation coefficients, which leads to the high time consumption. To overcome these problems, we exploit a latent pattern model called Low-Rank Latent Pattern Approximation (LLPA) to reconstruct the test image having structural noise...
August 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28806318/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
#13
Martin H Goodenberger, Nicolaus A Wagner-Bartak, Shiva Gupta, Xinming Liu, Ramon Q Yap, Jia Sun, Eric P Tamm, Corey T Jensen
OBJECTIVE: 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). METHODS AND MATERIALS: 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...
August 12, 2017: Journal of Computer Assisted Tomography
https://www.readbyqxmd.com/read/28774650/rapid-anatomical-brain-imaging-using-spiral-acquisition-and-an-expanded-signal-model
#14
Lars Kasper, Maria Engel, Christoph Barmet, Maximilian Haeberlin, Bertram J Wilm, Benjamin E Dietrich, Thomas Schmid, Simon Gross, David O Brunner, Klaas E Stephan, Klaas P Pruessmann
We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute...
July 31, 2017: NeuroImage
https://www.readbyqxmd.com/read/28770254/3d-correction-of-ais-in-braces-designed-using-cad-cam-and-fem-a-randomized-controlled-trial
#15
Nikita Cobetto, Carl-Éric Aubin, Stefan Parent, Soraya Barchi, Isabelle Turgeon, Hubert Labelle
BACKGROUND: Recent studies showed that finite element model (FEM) combined to CAD/CAM improves the design of braces for the conservative treatment of adolescent idiopathic scoliosis (AIS), using 2D measurements from in-brace radiographs. We aim to assess the immediate effectiveness on curve correction in all three planes of braces designed using CAD/CAM and numerical simulation compared to braces designed with CAD/CAM only. METHODS: SRS standardized criteria for bracing were followed to recruit 48 AIS patients who were randomized into two groups...
2017: Scoliosis and Spinal Disorders
https://www.readbyqxmd.com/read/28767366/detector-blur-and-correlated-noise-modeling-for-digital-breast-tomosynthesis-reconstruction
#16
Jiabei Zheng, Jeffrey A Fessler, Heang-Ping Chan
This paper describes a new image reconstruction method for digital breast tomosynthesis (DBT). The new method incorporates detector blur into the forward model. The detector blur in DBT causes correlation in the measurement noise. By making a few approximations that are reasonable for breast imaging, we formulated a regularized quadratic optimization problem with a data-fit term that incorporates models for detector blur and correlated noise (DBCN). We derived a computationally efficient separable quadratic surrogate (SQS) algorithm to solve the optimization problem that has a non-diagonal noise covariance matrix...
July 27, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28766981/image-quality-and-radiation-dose-of-ct-venography-with-double-dose-reduction-using-model-based-iterative-reconstruction-comparison-with-conventional-ct-venography-using-filtered-back-projection
#17
Yeo-Jin Jeong, Ki Seok Choo, Kyung Jin Nam, Ji Won Lee, Jin You Kim, Hyuk Jae Jung, Soo Jin Lim
Background Computed tomography venography (CTV) at low kVp using model-based iterative reconstruction (MBIR) can enhance vascular enhancement with noise reduction. Purpose To evaluate image qualities and radiation doses of CTV at 80 kVp using MBIR and a small iodine contrast media (CM) dose and to compare these with those of CTV performed using a conventional protocol. Material and Methods Sixty-five patients (mean age = 58.1 ± 7.2 years) that underwent CTV for the evaluation of deep vein thrombosis (DVT) and varicose veins were enrolled in this study...
January 1, 2017: Acta Radiologica
https://www.readbyqxmd.com/read/28764856/image-quality-of-ct-angiography-in-young-children-with-congenital-heart-disease-a%C3%A2-comparison-between-the-sinogram-affirmed-iterative-reconstruction-safire-and-advanced-modelled-iterative-reconstruction-admire-algorithms
#18
S B Nam, D W Jeong, K S Choo, K J Nam, J-Y Hwang, J W Lee, J Y Kim, S J Lim
AIM: To compare the image quality of computed tomography angiography (CTA) reconstructed by sinogram-affirmed iterative reconstruction (SAFIRE) with that of advanced modelled iterative reconstruction (ADMIRE) in children with congenital heart disease (CHD). MATERIAL AND METHODS: Thirty-one children (8.23±13.92 months) with CHD who underwent CTA were enrolled. Images were reconstructed using SAFIRE (strength 5) and ADMIRE (strength 5). Objective image qualities (attenuation, noise) were measured in the great vessels and heart chambers...
July 29, 2017: Clinical Radiology
https://www.readbyqxmd.com/read/28762337/superiorized-algorithm-for-reconstruction-of-ct-images-from-sparse-view-and-limited-angle-polyenergetic-data
#19
T Humphries, J Winn, A Faridani
Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed heuristic which provides an automatic procedure to 'superiorize' an iterative image reconstruction algorithm with respect to a chosen objective function, such as TV. Under certain conditions, the superiorized algorithm is guaranteed to find a solution that is as satisfactory as any found by the original algorithm with respect to satisfying the constraints of the problem; this solution is also expected to be superior with respect to the chosen objective...
August 1, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28759633/dictionary-learning-based-noisy-image-super-resolution-via-distance-penalty-weight-model
#20
Yulan Han, Yongping Zhao, Qisong Wang
In this study, we address the problem of noisy image super-resolution. Noisy low resolution (LR) image is always obtained in applications, while most of the existing algorithms assume that the LR image is noise-free. As to this situation, we present an algorithm for noisy image super-resolution which can achieve simultaneously image super-resolution and denoising. And in the training stage of our method, LR example images are noise-free. For different input LR images, even if the noise variance varies, the dictionary pair does not need to be retrained...
2017: PloS One
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