A5027995660- Advanced MRI Techniques and Applications
- Medical Imaging Techniques and Applications
- Medical Image Segmentation Techniques
- Cardiovascular Function and Risk Factors
- Radiomics and Machine Learning in Medical Imaging
- Cardiac Imaging and Diagnostics
- Cardiovascular Health and Disease Prevention
- Advanced NMR Techniques and Applications
- Atomic and Subatomic Physics Research
- Elasticity and Material Modeling
- Advanced Radiotherapy Techniques
- Gaussian Processes and Bayesian Inference
- Machine Learning in Materials Science
- Image Processing and 3D Reconstruction
- Advanced Vision and Imaging
- Sparse and Compressive Sensing Techniques
- Advanced Neuroimaging Techniques and Applications
- Electron Spin Resonance Studies
Yale University
2024
Harvard University
2020-2024
Massachusetts General Hospital
2019-2024
Gordon Center for Medical Imaging
2020-2022
Laboratoire Traitement et Communication de l’Information
2020-2022
Télécom Paris
2020-2022
Analyse, Géométrie et Modélisation
2020
The spatial resolution and temporal frame-rate of dynamic magnetic resonance imaging (MRI) can be improved by reconstructing images from sparsely sampled <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -space data with mathematical modeling the underlying spatiotemporal signals. These models include sparsity models, linear subspace non-linear manifold models. This work...
Image quality of PET reconstructions is degraded by subject motion occurring during the acquisition. MR-based correction approaches have been studied for PET/MR scanners and successful at capturing regular patterns, when used in conjunction with surrogate signals (e.g. navigators) to detect motion. However, handling irregular respiratory bulk remains challenging. In this work, we propose an method relying on subspace-based real-time MR imaging estimate fields correct reconstructions. We take...
Purpose To develop a cardiac T 1 mapping method for free‐breathing 3D of the whole heart at 3 with transmit B ( ) correction. Methods A free‐breathing, electrocardiogram‐gated inversion‐recovery sequence spoiled gradient‐echo readout was developed and optimized T. High‐frame‐rate dynamic images were reconstructed from sparse (k,t)‐space data acquired along stack‐of‐stars trajectory using subspace‐based accelerated imaging. Joint flip‐angle estimation performed in to improve its robustness...
Purpose To develop a manifold learning‐based method that leverages the intrinsic low‐dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification. Methods A linear tangent space alignment (LTSA) model was proposed to represent MRSI signals. In model, each metabolite were represented using subspace and local coordinates subspaces aligned global underlying via transform. With basis functions predetermined quantum mechanics simulations, matrices...
Positron Emission Tomography (PET) is a valuable imaging method for studying molecular-level processes in the body, such as hyperphosphorylated tau (p-tau) protein aggregates, hallmark of several neurodegenerative diseases including Alzheimer's disease. P-tau density and cerebral perfusion can be quantified from PET data using tracer kinetic modeling techniques. However, noise images leads to uncertainty estimated parameters. This Bayesian framework by posterior distribution parameters given...
$\textbf{Purpose:}$ To develop a new method for free-breathing 3D extracellular volume (ECV) mapping of the whole heart at 3T. $\textbf{Methods:}$ A cardiac ECV was developed T1 performed before and after contrast agent injection using ECG-gated inversion-recovery sequence with spoiled gradient echo readout. linear tangent space alignment (LTSA) model-based used to reconstruct high-frame-rate dynamic images from (k,t)-space data sparsely sampled along random stack-of-stars trajectory. Joint...
Abstract Purpose To develop a new method for free‐breathing 3D extracellular volume (ECV) mapping of the whole heart at 3 T. Methods A cardiac ECV was developed T 1 performed before and after contrast agent injection using electrocardiogram‐gated inversion recovery sequence with spoiled gradient echo readout. linear tangent space alignment model‐based used to reconstruct high‐frame‐rate dynamic images from (k,t)‐space data sparsely sampled along random stack‐of‐stars trajectory. Joint...
Cardiac T1 mapping allows assessment of tissue characteristics and functioning the heart. However, existing methods are limited in terms spatial resolution coverage due to limitations acquisition speed presence cardiac respiratory motion. This work proposes a new reconstruction framework for simultaneous, high-resolution 3D cine imaging heart at 3T from sparsely sampled k-space data.