59 Result(s)
within
Simon K. Warfield
Computer Science
Pattern Recognition
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Chapter and Conference Paper
MRI Super-Resolution Through Generative Degradation Learning
Spatial resolution plays a critically important role in MRI for the precise delineation of the imaged tissues. Unfortunately, acquisitions with high spatial resolution require increased imaging time, which inc...
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Chapter and Conference Paper
Learning a Gradient Guidance for Spatially Isotropic MRI Super-Resolution Reconstruction
In MRI practice, it is inevitable to appropriately balance between image resolution, signal-to-noise ratio (SNR), and scan time. It has been shown that super-resolution reconstruction (SRR) is effective to ach...
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Chapter and Conference Paper
Isotropic MRI Super-Resolution Reconstruction with Multi-scale Gradient Field Prior
In this work, we proposed a novel image-based MRI super-resolution reconstruction (SRR) approach based on anisotropic acquisition schemes. We achieved superior reconstruction to state-of-the-art work by intro...
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Chapter and Conference Paper
A Bayes Hilbert Space for Compartment Model Computing in Diffusion MRI
The single diffusion tensor model for map** the brain white matter microstructure has long been criticized as providing sensitive yet non-specific clinical biomarkers for neurodegenerative diseases because (...
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Chapter and Conference Paper
Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging
Diffusion tensor imaging (DTI) based group analysis has helped uncover the impact of white matter injuries in a wide range of studies involving subjects from preterm neonates to adults. The application of thes...
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Chapter and Conference Paper
Identification of Gadolinium Contrast Enhanced Regions in MS Lesions Using Brain Tissue Microstructure Information Obtained from Diffusion and T2 Relaxometry MRI
A multiple sclerosis (MS) lesion at an early stage undergoes active blood brain barrier (BBB) breakdown. Identifying MS lesions in a patient which are undergoing active BBB breakdown is of critical importance ...
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Chapter and Conference Paper
Motion-Robust Spatially Constrained Parameter Estimation in Renal Diffusion-Weighted MRI by 3D Motion Tracking and Correction of Sequential Slices
In this work, we introduce a novel motion-robust spatially constrained parameter estimation (MOSCOPE) technique for kidney diffusion-weighted MRI. The proposed motion compensation technique does not require a ...
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Chapter and Conference Paper
Decoupling Axial and Radial Tissue Heterogeneity in Diffusion Compartment Imaging
Diffusion compartment imaging (DCI) characterizes tissues in vivo by separately modeling the diffusion signal arising from a finite number of large scale microstructural environments in each voxel, also referr...
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Chapter and Conference Paper
Comprehensive Maximum Likelihood Estimation of Diffusion Compartment Models Towards Reliable Map** of Brain Microstructure
Diffusion MRI is a key in-vivo non invasive imaging capability that can probe the microstructure of the brain. However, its limited resolution requires complex voxelwise generative models of the diffusion. Dif...
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Chapter and Conference Paper
Motion-Robust Reconstruction Based on Simultaneous Multi-slice Registration for Diffusion-Weighted MRI of Moving Subjects
Simultaneous multi-slice (SMS) echo-planar imaging has had a huge impact on the acceleration and routine use of diffusion-weighted MRI (DWI) in neuroimaging studies in particular the human connectome project; ...
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Chapter and Conference Paper
Motion Compensated Abdominal Diffusion Weighted MRI by Simultaneous Image Registration and Model Estimation (SIR-ME)
Non-invasive characterization of water molecule’s mobility variations by quantitative analysis of diffusion-weighted MRI (DW-MRI) signal decay in the abdomen has the potential to serve as a biomarker in gastro...
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Chapter and Conference Paper
Analytic Quantification of Bias and Variance of Coil Sensitivity Profile Estimators for Improved Image Reconstruction in MRI
Magnetic resonance (MR) imaging provides a unique in-vivo capability of visualizing tissue in the human brain non-invasively, which has tremendously improved patient care over the past decades. However, there ...
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Chapter and Conference Paper
Accelerated High Spatial Resolution Diffusion-Weighted Imaging
Acquisition of a series of anisotropically oversampled acquisitions (so-called anisotropic “snapshots”) and reconstruction in the image space has recently been proposed to increase the spatial resolution in di...
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Chapter and Conference Paper
A Fully Bayesian Inference Framework for Population Studies of the Brain Microstructure
Models of the diffusion-weighted signal are of strong interest for population studies of the brain microstructure. These studies are typically conducted by extracting a scalar property from the model and subje...
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Chapter and Conference Paper
Construction of a Deformable Spatiotemporal MRI Atlas of the Fetal Brain: Evaluation of Similarity Metrics and Deformation Models
The development and identification of best methods in fetal brain MRI analysis is crucial as we expect an outburst of studies on groupwise and longitudinal analysis of early brain development in the upcoming y...
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Chapter and Conference Paper
Spatially-Constrained Probability Distribution Model of Incoherent Motion (SPIM) in Diffusion Weighted MRI Signals of Crohn’s Disease
Diffusion Weighted imaging (DWI) of the body provides important information about the physiological and microstructural properties of tissues and has great potential for imaging inflammatory activity and impro...
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Chapter and Conference Paper
T 2-Relaxometry for Myelin Water Fraction Extraction Using Wald Distribution and Extended Phase Graph
Quantitative assessment of myelin density in the white matter is an emerging tool for neurodegenerative disease related studies such as multiple sclerosis and Schizophrenia. For the last two decades, T ...
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Chapter and Conference Paper
Optimal MAP Parameters Estimation in STAPLE - Learning from Performance Parameters versus Image Similarity Information
In many medical imaging applications, merging segmentations obtained from multiple reference images (i.e., templates) has become a standard practice for improving the accuracy as well as reliability. Simultane...
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Chapter and Conference Paper
Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can)
Null Hypothesis Significance Testing (NHST) is used pervasively in neuroimaging studies, despite its known limitations. Recent critiques to these tests have mostly focused on technical issues with multiple com...
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Chapter and Conference Paper
Estimation of a Multi-fascicle Model from Single B-Value Data with a Population-Informed Prior
Diffusion tensor imaging cannot represent heterogeneous fascicle orientations in one voxel. Various models propose to overcome this limitation. Among them, multi-fascicle models are of great interest to charac...
