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View article: Pre‐atrophic Neurodegeneration: A Novel MRI‐Based Biomarker for Early Neuronal Injury Coincident with Early Amyloid Accumulation
Pre‐atrophic Neurodegeneration: A Novel MRI‐Based Biomarker for Early Neuronal Injury Coincident with Early Amyloid Accumulation Open
Background Early identification of neuropathological changes in Alzheimer's disease (AD) is essential for the development and application of disease‐modifying therapies. Currently, brain accumulation of β‐amyloid (Aβ) and/or CSF amyloid le…
View article: Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements
Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements Open
Background The 18F‐AV‐1451 radioligand enables in‐vivo identification of tau neurofibrillary tangles that are considered as biomarkers of neurodegeneration in Alzheimer Disease (AD). However, off‐target radioligand binding is also observed…
View article: Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements
Relationship Between 18F‐AV‐1451 Binding in Human Brain and Tissue Alterations Defined by Quantitative Gradient Recalled Echo (qGRE) MRI Measurements Open
Background The 18F‐AV‐1451 radioligand enables in‐vivo identification of tau neurofibrillary tangles that are considered as biomarkers of neurodegeneration in Alzheimer Disease (AD). However, off‐target radioligand binding is also observed…
View article: Quantification of myocardial oxygen extraction fraction on noncontrast MRI enabled by deep learning
Quantification of myocardial oxygen extraction fraction on noncontrast MRI enabled by deep learning Open
Purpose To develop a new deep learning enabled cardiovascular magnetic resonance (CMR) approach for noncontrast quantification of myocardial oxygen extraction fraction (mOEF) and myocardial blood volume (MBV) in vivo. Materials and Methods…
View article: MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images
MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images Open
Our early results show that automated motion-corrected and deep learning-generated pseudo-CT images of the pediatric skull have potential for clinical use and offer a high level of diagnostic accuracy when compared with standard CT scans.
View article: SPICER: Self‐supervised learning for MRI with automatic coil sensitivity estimation and reconstruction
SPICER: Self‐supervised learning for MRI with automatic coil sensitivity estimation and reconstruction Open
Purpose To introduce a novel deep model‐based architecture (DMBA), SPICER, that uses pairs of noisy and undersampled k‐space measurements of the same object to jointly train a model for MRI reconstruction and automatic coil sensitivity est…
View article: Resting-state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats
Resting-state MRI reveals spontaneous physiological fluctuations in the kidney and tracks diabetic nephropathy in rats Open
This work demonstrates the development and use of resting-state MRI to detect low-frequency, spontaneous physiological fluctuations in the kidney consistent with previously observed fluctuations in perfusion and potentially due to autoregu…
View article: Comparison of cerebral oxygen extraction fraction using ASE and TRUST methods in patients with sickle cell disease and healthy controls
Comparison of cerebral oxygen extraction fraction using ASE and TRUST methods in patients with sickle cell disease and healthy controls Open
Abnormal oxygen extraction fraction (OEF), a putative biomarker of cerebral metabolic stress, may indicate compromised oxygen delivery and ischemic vulnerability in patients with sickle cell disease (SCD). Elevated OEF was observed at the …
View article: Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees
Self-Supervised Deep Equilibrium Models for Inverse Problems with Theoretical Guarantees Open
Deep equilibrium models (DEQ) have emerged as a powerful alternative to deep unfolding (DU) for image reconstruction. DEQ models-implicit neural networks with effectively infinite number of layers-were shown to achieve state-of-the-art ima…
View article: SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction
SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction Open
Deep model-based architectures (DMBAs) integrating physical measurement models and learned image regularizers are widely used in parallel magnetic resonance imaging (PMRI). Traditional DMBAs for PMRI rely on pre-estimated coil sensitivity …
View article: Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease
Normalization of cerebral hemodynamics after hematopoietic stem cell transplant in children with sickle cell disease Open
Children with sickle cell disease (SCD) demonstrate cerebral hemodynamic stress and are at high risk of strokes. We hypothesized that curative hematopoietic stem cell transplant (HSCT) normalizes cerebral hemodynamics in children with SCD …
View article: Deep‐learning synthesized pseudo‐<scp>CT</scp> for <scp>MR</scp> high‐resolution pediatric cranial bone imaging (<scp>MR‐HiPCB</scp>)
Deep‐learning synthesized pseudo‐<span>CT</span> for <span>MR</span> high‐resolution pediatric cranial bone imaging (<span>MR‐HiPCB</span>) Open
Purpose CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo‐CT (pCT) images for MR high‐resolution pediatr…
View article: Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth
Image Reconstruction for MRI using Deep CNN Priors Trained without Groundtruth Open
We propose a new plug-and-play priors (PnP) based MR image reconstruction method that systematically enforces data consistency while also exploiting deep-learning priors. Our prior is specified through a convolutional neural network (CNN) …
View article: Deformation-Compensated Learning for Image Reconstruction Without Ground Truth
Deformation-Compensated Learning for Image Reconstruction Without Ground Truth Open
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has shown the potential of using multiple noisy measurements of th…
View article: <scp>MR‐assisted PET</scp> respiratory motion correction using <scp>deep‐learning</scp> based <scp>short‐scan</scp> motion fields
<span>MR‐assisted PET</span> respiratory motion correction using <span>deep‐learning</span> based <span>short‐scan</span> motion fields Open
Purpose We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep‐learning reconstructed short MRI sc…
View article: MoDIR: Motion-Compensated Training for Deep Image Reconstruction without Ground Truth
MoDIR: Motion-Compensated Training for Deep Image Reconstruction without Ground Truth Open
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work onNoise2Noise (N2N) has shown the potential of using multiple noisy measurements of the…
View article: Deformation-Compensated Learning for Image Reconstruction without Ground Truth
Deformation-Compensated Learning for Image Reconstruction without Ground Truth Open
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has shown the potential of using multiple noisy measurements of th…
View article: Spatiotemporal Uptake Characteristics of [18]F-2-Fluoro-2-Deoxy-D-Glucose in a Rat Middle Cerebral Artery Occlusion Model
Spatiotemporal Uptake Characteristics of [18]F-2-Fluoro-2-Deoxy-D-Glucose in a Rat Middle Cerebral Artery Occlusion Model Open
Alterations of cerebral glucose metabolism are well anticipated during cerebral ischemia. However, detailed spatiotemporal characteristics of disturbed cerebral glucose metabolism during acute ischemia remain largely elusive. This study ai…
View article: Cerebral Oxygen Metabolic Stress, Microstructural Injury, and Infarction in Adults With Sickle Cell Disease
Cerebral Oxygen Metabolic Stress, Microstructural Injury, and Infarction in Adults With Sickle Cell Disease Open
Elevated OEF, a putative index of cerebral oxygen metabolic stress, may provide a metric of ischemic vulnerability that could enable individualization of therapeutic strategies in SCD. The patient- and tissue-based relationships between el…
View article: Quantification of myocardial oxygen extraction fraction: A proof‐of‐concept study
Quantification of myocardial oxygen extraction fraction: A proof‐of‐concept study Open
Purpose To demonstrate a proof of concept for the measurement of myocardial oxygen extraction fraction (mOEF) by a cardiovascular magnetic resonance technique. Methods The mOEF measurement was performed using an electrocardiogram‐triggered…
View article: Bulk volume susceptibility difference between deoxyhemoglobin and oxyhemoglobin for HbA and HbS: A comparative study
Bulk volume susceptibility difference between deoxyhemoglobin and oxyhemoglobin for HbA and HbS: A comparative study Open
Purpose Sickle cell anemia is a blood disorder that alters the morphology and the oxygen affinity of the red blood cells. Cerebral oxygen extraction fraction measurements using quantitative BOLD contrast have been used for assessing inadeq…
View article: Deep Image Reconstruction using Unregistered Measurements without Groundtruth
Deep Image Reconstruction using Unregistered Measurements without Groundtruth Open
One of the key limitations in conventional deep learning based image reconstruction is the need for registered pairs of training images containing a set of high-quality groundtruth images. This paper addresses this limitation by proposing …
View article: Functional Connectivity Decreases with Metabolic Stress in Sickle Cell Disease
Functional Connectivity Decreases with Metabolic Stress in Sickle Cell Disease Open
Objective Children with sickle cell disease (SCD) experience cognitive deficits even when unaffected by stroke. Using functional connectivity magnetic resonance imaging (MRI) as a potential biomarker of cognitive function, we tested our hy…
View article: Magnetic resonance safety assessment of a new trend: magnetic eyelashes
Magnetic resonance safety assessment of a new trend: magnetic eyelashes Open
One type of cosmetic that has gained recent popularity is the magnetic false eyelash. Some of these magnetic eyelashes are placed onto magnetic eyeliner applied to eye lids, while others come in pairs and clamp around the natural eyelashes…
View article: 3D pediatric cranial bone imaging using high-resolution MRI for visualizing cranial sutures: a pilot study
3D pediatric cranial bone imaging using high-resolution MRI for visualizing cranial sutures: a pilot study Open
OBJECTIVE There is an unmet need to perform imaging in young children and obtain CT-equivalent cranial bone images without subjecting the patients to radiation. In this study, the authors propose using a high-resolution fast low-angle shot…
View article: Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge
Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge Open
We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging …
View article: RARE: Image Reconstruction Using Deep Priors Learned Without Groundtruth
RARE: Image Reconstruction Using Deep Priors Learned Without Groundtruth Open
Regularization by denoising (RED) is an image reconstruction framework that uses an image denoiser as a prior. Recent work has shown the state-of-the-art performance of RED with learned denoisers corresponding to pre-trained convolutional …
View article: Reperfusion Beyond 6 Hours Reduces Infarct Probability in Moderately Ischemic Brain Tissue
Reperfusion Beyond 6 Hours Reduces Infarct Probability in Moderately Ischemic Brain Tissue Open
We aimed to examine perfusion changes between 3 and 6, and 6 and 24 hours after stroke onset and their impact on tissue outcome.