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Showing 1-25 of 30,859 resultsfor "Index Terms":Image Reconstruction Algorithm
"Index Terms":Image Reconstruction Algorithm
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Ultra Fast Symmetry and SIMD-Based Projection-Backprojection (SSP) Algorithm for 3-D PET Image Reconstruction
I. K. Hong;S. T. Chung;H. K. Kim;Y. B. Kim;Y. D. Son;Z. H. Cho
Remarkable progress in positron emission tomography (PET) development has occurred in recent years, in hardware, software, and computer implementation of image reconstruction. Recent development in PET scanners such as the high-resolution research tomograph (HRRT) developed by CTI (now Siemens) represents such a case and is capable of greatly enhanced resolution as well as sensitivity. In these PE...Show More
Real-Time Reconstruction of Sensitivity Encoded Radial Magnetic Resonance Imaging Using a Graphics Processing Unit
Thomas Sangild Sorensen;David Atkinson;Tobias Schaeffter;Michael Schacht Hansen
A barrier to the adoption of non-Cartesian parallel magnetic resonance imaging for real-time applications has been the times required for the image reconstructions. These times have exceeded the underlying acquisition time thus preventing real-time display of the acquired images. We present a reconstruction algorithm for commodity graphics hardware (GPUs) to enable real time reconstruction of sens...Show More
A Fast Fully 4-D Incremental Gradient Reconstruction Algorithm for List Mode PET Data
We describe a fast and globally convergent fully four-dimensional incremental gradient (4DIG) algorithm to estimate the continuous-time tracer density from list mode positron emission tomography (PET) data. Detection of 511-keV photon pairs produced by positron-electron annihilation is modeled as an inhomogeneous Poisson process whose rate function is parameterized using cubic B-splines. The ra...Show More
Improvement of 3-D Ultrasound Spine Imaging Technique Using Fast Reconstruction Algorithm
Hong-Bo Chen;Rui Zheng;Li-Yue Qian;Feng-Yu Liu;Sheng Song;Hong-Ye Zeng
Three-dimensional (3-D) freehand ultrasound (US) imaging has been applied to the investigation of spine deformity. However, it is a challenge for the current 3-D imaging reconstruction algorithms to achieve a balance between image quality and computation time. The objectives of this article are to implement a new fast reconstruction algorithm that can fulfill the request of immediate demonstration...Show More
Sparse Gradient Image Reconstruction Done Faster
2007 IEEE International Conference on Image Processing
Year: 2007 | Conference Paper |
In a wide variety of imaging applications (especially medical imaging), we obtain a partial set or subset of the Fourier transform of an image. From these Fourier measurements, we want to reconstruct the entire original image. Convex optimization is a powerful, recent solution to this problem. Unfortunately, convex optimization in its myriad of implementations is computationally expensive and may ...Show More
2.5-D simultaneous multislice reconstruction by series expansion methods from Fourier-rebinned PET data
True three dimensional (3-D) volume reconstruction from fully 3-D data in positron emission tomography (PET) has only a limited clinical use because of its large computational burden. Fourier rebinning (FORE) of the fully 3-D data into a set of 2-D sinogram data decomposes the 3-D reconstruction process into multiple 2-D reconstructions of decoupled 2-D image slices, thus substantially decreasing ...Show More
Pinhole SPECT With Different Data Acquisition Geometries: Usefulness of Unified Projection Operators in Homogeneous Coordinates
To further improve pinhole single photon emission computed tomography (SPECT) imaging, there have been increasing interests in the use of nonstandard collimator designs and/or acquisition geometries. Homogeneous coordinates provide a compact and convenient framework to unify the geometric descriptions of the projection operators for these different imaging geometries, which may facilitate the impl...Show More
Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints
Yuping Duan;Dalel Bouslimi;Guanyu Yang;Huazhong Shu;Gouenou Coatrieux
In this paper, we focus on the “blind” identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is i...Show More
Image Reconstruction and Multidimensional Field Estimation From Randomly Scattered Sensors
Many important problems in statistical signal processing can be formulated as function estimation from randomly scattered sensors in a multidimensional space, e.g., image reconstruction from photon-limited images and field estimation from scattered sensors. We present a novel approach to the study of signal reconstruction from random samples in a multidimensional space. In particular, we study a c...Show More
Suppression of Metal Artifacts in CT Using a Reconstruction Procedure That Combines MAP and Projection Completion
Metal implants such as hip prostheses and dental fillings produce streak and star artifacts in the reconstructed computed tomography (CT) images. Due to these artifacts, the CT image may not be diagnostically usable. A new reconstruction procedure is proposed that reduces the streak artifacts and that might improve the diagnostic value of the CT images. The procedure starts with a maximum a poster...Show More
A Multiresolution Approach to Iterative Reconstruction Algorithms in X-Ray Computed Tomography
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...Show More
Fast Joint Reconstruction of Dynamic R_2^* and Field Maps in Functional MRI
Blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) is conventionally done by reconstructing T2 * -weighted images. However, since the images are unitless they are nonquantifiable in terms of important physiological parameters. An alternative approach is to reconstruct R2 * maps which are quantifiable and have comparable BOLD contrast as T2* -weighted images. However, ...Show More
TRIO a Technique for Reconstruction Using Intensity Order: Application to Undersampled MRI
Leonardo Ramirez;Claudia Prieto;Carlos Sing-Long;Sergio Uribe;Philip Batchelor;Cristian Tejos;Pablo Irarrazaval
Long acquisition times are still a limitation for many applications of magnetic resonance imaging (MRI), specially in 3-D and dynamic imaging. Several undersampling reconstruction techniques have been proposed to overcome this problem. These techniques are based on acquiring less samples than specified by the Nyquist criterion and estimating the nonacquired data by using some sort of prior informa...Show More
Comparison and analysis of nonlinear algorithms for compressed sensing in MRI
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology
Year: 2010 | Conference Paper |
Cited by: Papers (1)
Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A ...Show More
Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography
Thermoacoustic tomography (TAT) is an emerging imaging technique with potential for a wide range of biomedical imaging applications. In this correspondence, we propose an infinite family of weighted expectation maximization (EM) algorithms for reconstruction of images from temporally truncated TAT measurement data. The weighted EM algorithms are equivalent mathematically to the conventional EM alg...Show More
Research on Computed Tomography Image Reconstruction Algorithm Based on Optical Flow Equation and Target Matching
2022 International Conference on Information System, Computing and Educational Technology (ICISCET)
Year: 2022 | Conference Paper |
Image is the main source of human access to information. Due to the development needs of aerospace, biomedical engineering, industrial detection, culture and art, pattern recognition and military, image processing has attracted more and more attention, and has gradually developed into a promising new discipline. For different processing purposes, digital image processing can be divided into geomet...Show More
Fast algorithms for GS-model-based image reconstruction in data-sharing Fourier imaging
Many imaging experiments involve acquiring a time series of images. To improve imaging speed, several "data-sharing" methods have been proposed, which collect one (or a few) high-resolution reference(s) and a sequence of reduced data sets. In image reconstruction, two methods, known as "Keyhole" and reduced-encoding imaging by generalized-series reconstruction (RIGR), have been used. Keyhole fills...Show More
Field Inhomogeneity Correction Based on Gridding Reconstruction for Magnetic Resonance Imaging
Spatial variations of the main field give rise to artifacts in magnetic resonance images if disregarded in reconstruction. With non-Cartesian k-space sampling, they often lead to unacceptable blurring. Data from such acquisitions are usually reconstructed with gridding methods and optionally restored with various correction methods. Both types of methods essentially face the same basic problem of ...Show More
A Survey On Recent Approaches In Image Reconstruction
2020 International Conference on Power, Instrumentation, Control and Computing (PICC)
Year: 2020 | Conference Paper |
Image reconstruction is an ongoing research in medical image processing. It is a continuously developing field. The aim is to reconstruct the images from some noise or something else without loss of image quality and accuracy of the reconstructed images. Medical image processing is one of the most trending research area. Medical images are widely used in various applications like medical segmentat...Show More
Conjugate phase MRI reconstruction with spatially variant sample density correction
A new image reconstruction method to correct for the effects of magnetic field inhomogeneity in non-Cartesian sampled magnetic resonance imaging (MRI) is proposed. The conjugate phase reconstruction method, which corrects for phase accumulation due to applied gradients and magnetic field inhomogeneity, has been commonly used for this case. This can lead to incomplete correction, in part, due to th...Show More
Investigation of THz image reconstruction by transposed convolution algorithm
2017 10th UK-Europe-China Workshop on Millimetre Waves and Terahertz Technologies (UCMMT)
Year: 2017 | Conference Paper |
This paper presents our study on image reconstruction algorithms for THz near field scanning systems. Based on the principle of Physical Optics (PO) algorithm, we have proposed and investigated a novel transposed convolution image reconstruction algorithm (TC), in comparison with the back propagation algorithm (BP) in simulation and experiment.Show More
On the efficiency of OSEM algorithm for tomographic lung CT images reconstruction
2016 International Image Processing, Applications and Systems (IPAS)
Year: 2016 | Conference Paper |
Cited by: Papers (1)
Sometimes, computed tomography (CT) examinations need to be repeated. This may generate adverse effects on patients. To avoid it, an efficient reconstruction technique should be applied. This paper presents a qualitative and quantitative comparative study of four iterative algorithms (Algebraic Reconstruction Technique (ART), Maximum Likelihood Expectation Maximization (MLEM), Ordered-subsets expe...Show More
Nonseparable wavelet-based cone-beam reconstruction in 3-D rotational angiography
We propose a new wavelet-based reconstruction method suited to three-dimensional (3-D) cone-beam (CB) tomography. It is derived from the Feldkamp algorithm and is valid for the same geometrical conditions. The demonstration is done in the framework of nonseparable wavelets and requires ideally radial wavelets. The proposed inversion formula yields to a filtered backprojection algorithm but the fil...Show More
Radial Imaging With Multipolar Magnetic Encoding Fields
Gerrit Schultz;Hans Weber;Daniel Gallichan;Walter R. T. Witschey;Anna M. Welz;Chris A. Cocosco;Jürgen Hennig;Maxim Zaitsev
We present reconstruction methods for radial magnetic resonance imaging (MRI) data which were spatially encoded using a pair of orthogonal multipolar magnetic fields for in-plane encoding and parallel imaging. It is shown that a direct method exists in addition to iterative reconstruction. Standard direct projection reconstruction algorithms can be combined with a previously developed direct recon...Show More
Backprojection Filtration Image Reconstruction Approach for Reducing High-Density Object Artifacts in Digital Breast Tomosynthesis
Hyeongseok Kim;Jongha Lee;Jeongtae Soh;Jonghwan Min;Young Wook Choi;Seungryong Cho
While an accurate image reconstruction of digital breast tomosynthesis (DBT) is fundamentally impossible due to its limited data, the DBT is increasingly used in clinics for its rich image information at a relatively low dose. One of the dominant image artifacts in DBT that hinders a faithful diagnosis is high-density object artifact in conjunction with a limited angle problem. In this paper, we d...Show More
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