GPU-based iterative transmission reconstruction in 3D ultrasound computer tomography

Birk, Matthias; Dapp, R.; Ruiter, Nicole V.; Becker, J.

doi:10.1016/j.jpdc.2013.09.007

Cited by 43 publications

(32 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, recent publications have shown that GPU-based programming can significantly improve the CS based reconstruction speed from a few tens of seconds to less than one second. 69,70 In addition, during the ℓ 1 minimization computation time of a certain slice, partial data can be acquired from other 2D slices in the image to avoid "dead" time periods. Examining new approaches for ℓ 1 minimization, algorithmic simplifications, combined with massively parallel digital computation and GPU programming could allow our framework to be used for real time MRI scanning.…”

Section: C Computational Complexitymentioning

confidence: 99%

Compressed sensing for longitudinal MRI: An adaptive‐weighted approach

2015

View full text Add to dashboard Cite

Purpose: Repeated brain MRI scans are performed in many clinical scenarios, such as follow up of patients with tumors and therapy response assessment. In this paper, the authors show an approach to utilize former scans of the patient for the acceleration of repeated MRI scans.Methods: The proposed approach utilizes the possible similarity of the repeated scans in longitudinal MRI studies. Since similarity is not guaranteed, sampling and reconstruction are adjusted during acquisition to match the actual similarity between the scans. The baseline MR scan is utilized both in the sampling stage, via adaptive sampling, and in the reconstruction stage, with weighted reconstruction. In adaptive sampling, k -space sampling locations are optimized during acquisition. Weighted reconstruction uses the locations of the nonzero coefficients in the sparse domains as a prior in the recovery process. The approach was tested on 2D and 3D MRI scans of patients with brain tumors.Results: The longitudinal adaptive CS MRI (LACS-MRI) scheme provides reconstruction quality which outperforms other CS-based approaches for rapid MRI. Examples are shown on patients with brain tumors and demonstrate improved spatial resolution. Compared with data sampled at Nyquist rate, LACS-MRI exhibits Signal-to-Error Ratio (SER) of 24.8dB with undersampling factor of 16.6 in 3D MRI.Conclusions reconstruction utilizing similarity of scans in longitudinal MRI studies, where possible. The proposed approach can play a major part and significantly reduce scanning time in many applications that consist of disease follow-up and monitoring of longitudinal changes in brain MRI.

show abstract

Section: C Computational Complexitymentioning

confidence: 99%

Compressed sensing for longitudinal MRI: An adaptive‐weighted approach

2015

View full text Add to dashboard Cite

show abstract

“…In addition, these experimental studies used simple two-dimensional porous media. To overcome the above limitations, Ju et al (2014a) incorporated several advanced technologies, such as CT scan, three-dimensional (3D) reconstruction (Gomi et al 2007;Geiger et al 2009;Hajizadeh et al 2011;Zhang et al 2013;Birk et al 2014;Ju et al 2014b), and 3D printing, to produce a physical model representing the natural rock. A 3D digital image can be obtained to represent the real rock structure based on the high-resolution X-ray CT imaging and the reconstruction, and then its three-dimensional micromodel using transparent material can be generated using a 3D printer.…”

Section: Fabricated Micromodelsmentioning

confidence: 99%

Simulation and visualization of the displacement between CO2 and formation fluids at pore-scale levels and its application to the recovery of shale gas

Hou

Gao

et al. 2016

Int J Coal Sci Technol

View full text Add to dashboard Cite

This article reports recent developments and advances in the simulation of the CO 2 -formation fluid displacement behaviour at the pore scale of subsurface porous media. Roughly, there are three effective visualization approaches to detect and observe the CO 2 -formation fluid displacement mechanism at the micro-scale, namely, magnetic resonance imaging, X-ray computed tomography and fabricated micromodels, but they are not capable of investigating the displacement process at the nano-scale. Though a lab-on-chip approach for the direct visualization of the fluid flow behaviour in nanoscale channels has been developed using an advanced epi-fluorescence microscopy method combined with a nanofluidic chip, it is still a qualitative analysis method. The lattice Boltzmann method (LBM) can simulate the CO 2 displacement processes in a two-dimensional or three-dimensional (3D) pore structure, but until now, the CO 2 displacement mechanisms had not been thoroughly investigated and the 3D pore structure of real rock had not been directly taken into account in the simulation of the CO 2 displacement process. The status of research on the applications of CO 2 displacement to enhance shale gas recovery is also analyzed in this paper. The coupling of molecular dynamics and LBM in tandem is proposed to simulate the CO 2 -shale gas displacement process based on the 3D digital model of shale obtained from focused ion beams and scanning electron microscopy.

show abstract

“…The area of medical image processing and analysis has contributed to significant medical advances [7,23,50,81,83,88,101] by integrating systems and techniques that support more efficient clinical diagnosis. These systems and techniques are based on images acquired by different imaging modalities such as, endoscopy [52], X-ray [88], microscopy [47,68], computed tomography (CT) [26,57], optical coherence tomography (OCT) [67], magnetic resonance (MR) [2,15], functional magnetic resonance (fMR) [3,97], magnetic resonance elastography (MRE) [20], positron emission tomography (PET) [17,42,43], single photon emission computed tomography (SPECT) [28], and 3D ultrasound computer tomography (USCT) [7].…”

Section: Introductionmentioning

confidence: 99%

“…Such extraction of relevant clinical information is a complex task requiring advanced computational systems able to process and obtain image-based features accurately and consistently within the shortest possible runtime. As a result, a new research area has emerged that combines computational techniques used for medical image processing and analysis [23,81,88] and high-performance computing solutions [7,50,83,101]. These two components can be briefly described as follows:…”

Section: Introductionmentioning

confidence: 99%

“…• High-performance computing-The main goal of this area is to optimize computational methods to achieve greater robustness, effectiveness, efficiency, and faster execution. To accomplish these objectives, parallel computing techniques are usually exploited to use the maximum available performance in the computational architecture adopted [7,50,83,101].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Techniques of medical image processing and analysis accelerated by high-performance computing: a systematic literature review

Gulo

Sementille

Tavares

2017

J Real-Time Image Proc

View full text Add to dashboard Cite

Techniques of medical image processing and analysis play a crucial role in many clinical scenarios, including in diagnosis and treatment planning. However, immense quantities of data and high complexity of the algorithms often used are computationally demanding. As a result, there now exists a wide range of techniques of medical image processing and analysis that require the application of high-performance computing solutions in order to reduce the required runtime. The main purpose of this review is to provide a comprehensive reference source of techniques of medical image processing and analysis that have been accelerated by high-performance computing solutions. With this in mind, the articles available in the Scopus and Web of Science electronic repositories were searched. Subsequently, the most relevant articles found were individually analyzed in order to identify: (a) the metrics used to evaluate computing performance, (b) the high-performance computing solution used, (c) the parallel design adopted, and (d) the task of medical image processing and analysis involved. Hence, the techniques of medical image processing and analysis found were identified, reviewed, and discussed, particularly in terms of computational performance. Consequently, the techniques reviewed herein present the progress made so far in reducing the computational runtime involved, and the difficulties and challenges that remain to be overcome.

show abstract

GPU-based iterative transmission reconstruction in 3D ultrasound computer tomography

Cited by 43 publications

References 14 publications

Compressed sensing for longitudinal MRI: An adaptive‐weighted approach

Compressed sensing for longitudinal MRI: An adaptive‐weighted approach

Simulation and visualization of the displacement between CO2 and formation fluids at pore-scale levels and its application to the recovery of shale gas

Techniques of medical image processing and analysis accelerated by high-performance computing: a systematic literature review

Contact Info

Product

Resources

About