scholarly journals Model‐based reconstruction for simultaneous multi‐slice mapping using single‐shot inversion‐recovery radial FLASH

2020 ◽  
Vol 85 (3) ◽  
pp. 1258-1271
Author(s):  
Xiaoqing Wang ◽  
Sebastian Rosenzweig ◽  
Nick Scholand ◽  
H. Christian M. Holme ◽  
Martin Uecker
Keyword(s):  
Inversion Recovery ◽  
Single Shot ◽  
Model Based

Model-based reconstruction for T1 mapping using single-shot inversion-recovery radial FLASH

2016 ◽  
Vol 26 (4) ◽  
pp. 254-263 ◽  
Author(s):  
Volkert Roeloffs ◽  
Xiaoqing Wang ◽  
Tilman J. Sumpf ◽  
Markus Untenberger ◽  
Dirk Voit ◽  
...  
Keyword(s):  
T1 Mapping ◽  
Inversion Recovery ◽  
Single Shot ◽  
Model Based

scholarly journals Fast Interleaved Multislice T1 Mapping: Model-Based Reconstruction of Single-Shot Inversion-Recovery Radial FLASH

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoqing Wang ◽  
Dirk Voit ◽  
Volkert Roeloffs ◽  
Martin Uecker ◽  
Jens Frahm
Keyword(s):  
High Speed ◽  
T1 Mapping ◽  
Inversion Recovery ◽  
Inversion Pulse ◽  
Breath Hold ◽  
Single Shot ◽  
Radial Sampling ◽  
Model Based ◽  
Inverse Reconstruction ◽  
Space Data

Purpose. To develop a high-speed multislice T1 mapping method based on a single-shot inversion-recovery (IR) radial FLASH acquisition and a regularized model-based reconstruction. Methods. Multislice radial k-space data are continuously acquired after a single nonselective inversion pulse using a golden-angle sampling scheme in a spoke-interleaved manner with optimized flip angles. Parameter maps and coil sensitivities of each slice are estimated directly from highly undersampled radial k-space data using a model-based nonlinear inverse reconstruction in conjunction with joint sparsity constraints. The performance of the method has been validated using a numerical and experimental T1 phantom as well as demonstrated for studies of the human brain and liver at 3T. Results. The proposed method allows for 7 simultaneous T1 maps of the brain at 0.5 × 0.5 × 4 mm3 resolution within a single IR experiment of 4 s duration. Phantom studies confirm similar accuracy and precision as obtained for a single-slice acquisition. For abdominal applications, the proposed method yields three simultaneous T1 maps at 1.25 × 1.25 × 6 mm3 resolution within a 4 s breath hold. Conclusion. Rapid, robust, accurate, and precise multislice T1 mapping may be achieved by combining the advantages of a model-based nonlinear inverse reconstruction, radial sampling, parallel imaging, and compressed sensing.

scholarly journals Model-based T1mapping with sparsity constraints using single-shot inversion-recovery radial FLASH

2017 ◽  
Vol 79 (2) ◽  
pp. 730-740 ◽  
Author(s):  
Xiaoqing Wang ◽  
Volkert Roeloffs ◽  
Jakob Klosowski ◽  
Zhengguo Tan ◽  
Dirk Voit ◽  
...  
Keyword(s):  
Inversion Recovery ◽  
Single Shot ◽  
Model Based ◽  
Sparsity Constraints

Most commonly used sequences and clinical protocols for brain and spine magnetic resonance imaging allowing better identification of pathological changes in dogs

2013 ◽  
Vol 16 (1) ◽  
pp. 157-163 ◽  
Author(s):  
Y. Zhalniarovich ◽  
Z. Adamiak ◽  
A. Pomianowski ◽  
M. Jaskólska
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Imaging Modality ◽  
Spin Echo ◽  
Inversion Recovery ◽  
Fast Spin Echo ◽  
Single Shot ◽  
Turbo Spin Echo ◽  
Resonance Imaging ◽  
Turbo Spin

Abstract Magnetic resonance imaging is the best imaging modality for the brain and spine. Quality of the received images depends on many technical factors. The most significant factors are: positioning the patient, proper coil selection, selection of appropriate sequences and image planes. The present contrast between different tissues provides an opportunity to diagnose various lesions. In many clinics magnetic resonance imaging has replaced myelography because of its noninvasive modality and because it provides excellent anatomic detail. There are many different combinations of sequences possible for spinal and brain MR imaging. Most frequently used are: T2-weighted fast spin echo (FSE), T1- and T2-weighted turbo spin echo, Fluid Attenuation Inversion Recovery (FLAIR), T1-weighted gradient echo (GE) and spin echo (SE), high-resolution three-dimensional (3D) sequences, fat-suppressing short tau inversion recovery (STIR) and half-Fourier acquisition single-shot turbo spin echo (HASTE). Magnetic resonance imaging reveals neurologic lesions which were previously hard to diagnose antemortem.

scholarly journals The Assisted Positioning Technology for High Speed Train Based on Deep Learning

2020 ◽  
Vol 10 (23) ◽  
pp. 8625
Author(s):  
Yali Song ◽  
Yinghong Wen
Keyword(s):  
Deep Learning ◽  
High Speed ◽  
Detection Method ◽  
Generative Adversarial Networks ◽  
Single Shot ◽  
High Speed Train ◽  
Data Set ◽  
Detection Model ◽  
Model Based ◽  
Cumulative Error

In the positioning process of a high-speed train, cumulative error may result in a reduction in the positioning accuracy. The assisted positioning technology based on kilometer posts can be used as an effective method to correct the cumulative error. However, the traditional detection method of kilometer posts is time-consuming and complex, which greatly affects the correction efficiency. Therefore, in this paper, a kilometer post detection model based on deep learning is proposed. Firstly, the Deep Convolutional Generative Adversarial Networks (DCGAN) algorithm is introduced to construct an effective kilometer post data set. This greatly reduces the cost of real data acquisition and provides a prerequisite for the construction of the detection model. Then, by using the existing optimization as a reference and further simplifying the design of the Single Shot multibox Detector (SSD) model according to the specific application scenario of this paper, the kilometer post detection model based on an improved SSD algorithm is established. Finally, from the analysis of the experimental results, we know that the detection model established in this paper ensures both detection accuracy and efficiency. The accuracy of our model reached 98.92%, while the detection time was only 35.43 ms. Thus, our model realizes the rapid and accurate detection of kilometer posts and improves the assisted positioning technology based on kilometer posts by optimizing the detection method.

Real‐time Triggered RAdial Single‐Shot Inversion recovery for arrhythmia‐insensitive myocardial T1 mapping: motion phantom validation and in vivo comparison

2018 ◽  
Vol 81 (3) ◽  
pp. 1714-1725 ◽  
Author(s):  
Daniel Gensler ◽  
Tim Salinger ◽  
Markus Düring ◽  
Kristina Lorenz ◽  
Roland Jahns ◽  
...  
Keyword(s):  
Real Time ◽  
T1 Mapping ◽  
Inversion Recovery ◽  
Single Shot ◽  
Myocardial T1 ◽  
Motion Phantom ◽  
Phantom Validation

scholarly journals 2110 Single shot inversion recovery gradient-echo MRI at 3 T for diagnosis of venous thrombosis

2008 ◽  
Vol 10 (S1) ◽  
Author(s):  
Farhood Saremi ◽  
Stephanie Channual ◽  
Mahammad Helmy ◽  
Kevin Chang ◽  
Imelda Ho
Keyword(s):  
Venous Thrombosis ◽  
Inversion Recovery ◽  
Single Shot ◽  
Gradient Echo

scholarly journals Whole-Brain Imaging of Subvoxel T1-Diffusion Correlation Spectra in Human Subjects

2021 ◽  
Vol 15 ◽  
Author(s):  
Alexandru V. Avram ◽  
Joelle E. Sarlls ◽  
Peter J. Basser
Keyword(s):  
Pulse Sequence ◽  
Mean Diffusivity ◽  
Inversion Recovery ◽  
Quantitative Mri ◽  
Single Shot ◽  
Myelinated Fiber ◽  
Whole Brain ◽  
Model Free ◽  
Wide Range ◽  
Biological Specificity

T1 relaxation and water mobility generate eloquent MRI tissue contrasts with great diagnostic value in many neuroradiological applications. However, conventional methods do not adequately quantify the microscopic heterogeneity of these important biophysical properties within a voxel, and therefore have limited biological specificity. We describe a new correlation spectroscopic (CS) MRI method for measuring how T1 and mean diffusivity (MD) co-vary in microscopic tissue environments. We develop a clinical pulse sequence that combines inversion recovery (IR) with single-shot isotropic diffusion encoding (IDE) to efficiently acquire whole-brain MRIs with a wide range of joint T1-MD weightings. Unlike conventional diffusion encoding, the IDE preparation ensures that all subvoxel water pools are weighted by their MDs regardless of the sizes, shapes, and orientations of their corresponding microscopic diffusion tensors. Accordingly, IR-IDE measurements are well-suited for model-free, quantitative spectroscopic analysis of microscopic water pools. Using numerical simulations, phantom experiments, and data from healthy volunteers we demonstrate how IR-IDE MRIs can be processed to reconstruct maps of two-dimensional joint probability density functions, i.e., correlation spectra, of subvoxel T1-MD values. In vivo T1-MD spectra show distinct cerebrospinal fluid and parenchymal tissue components specific to white matter, cortical gray matter, basal ganglia, and myelinated fiber pathways, suggesting the potential for improved biological specificity. The one-dimensional marginal distributions derived from the T1-MD correlation spectra agree well with results from other relaxation spectroscopic and quantitative MRI studies, validating the T1-MD contrast encoding and the spectral reconstruction. Mapping subvoxel T1-diffusion correlations in patient populations may provide a more nuanced, comprehensive, sensitive, and specific neuroradiological assessment of the non-specific changes seen on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MRIs (DWIs) in cancer, ischemic stroke, or brain injury.

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