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This paper presents the design and experimental characterization of a 1 T electromagnet tailored to meet the demands of a Magnetic Resonance Imaging (MRI) system conceived for spatial resolutions at the level of tens of microns. For high…
Purpose: To develop a self-supervised scan-specific deep learning framework for reconstructing accelerated multiparametric quantitative MRI (qMRI). Methods: We propose REFINE-MORE (REference-Free Implicit NEural representation with MOdel…
Purpose: Low-field MRI systems operate at single MHz-range frequencies, where signal losses are primarily dominated by thermal noise from the radio-frequency (RF) receive coils. Achieving operation close to this limit is essential for…
Real-time magnetic resonance imaging (MRI) poses unique challenges related to the speed of data acquisition and to the degree of undersampling necessary to achieve this speed. This Master's thesis introduces and evaluates two pre-processing…
Sodium magnetic resonance imaging (MRI) is sensitive and specific to ionic balance of cells owing to 10 fold difference in sodium concentration across membrane actively maintained by sodium potassium (Na+ K+) pump. Disruption of the pump…
The hybrid light-matter character of exciton-polaritons gives rise to distinct polariton parametric scattering (PPS) process, which holds promise for frontier applications in polaritonic quantum devices. However, the stable excitation and…
The advanced magnetic resonance (MR) image reconstructions such as the compressed sensing and subspace-based imaging are considered as large-scale, iterative, optimization problems. Given the large number of reconstructions required by the…
Recently, interest in programmable photonics integrated circuits has grown as a potential hardware framework for deep neural networks, quantum computing, and field programmable arrays (FPGAs). However, these circuits are constrained by the…
Detailed understanding of spin dynamics in magnetic nanomaterials is necessary for developing ultrafast, low-energy and high-density spintronic logic and memory. Here, we develop micromagnetic models and analytical solutions to elucidate…
Magnetic resonance imaging (MRI) reconstruction is a fundamental task aimed at recovering high-quality images from undersampled or low-quality MRI data. This process enhances diagnostic accuracy and optimizes clinical applications. In…
Magnetic particle imaging (MPI) is an imaging method that can visualize magnetic nanoparticles in positive contrast, without radiation exposure. Recently, we proposed an image reconstruction method for projection-based MPI (pMPI), in which…
Neuromorphic photonics relies on efficiently emulating analog neural networks at high speeds. Prior work showed that transducing signals from the optical to the electrical domain and back with transimpedance gain was an efficient approach…
By decoupling motion and spatial encoding, magnitude contrast MR Elastography could be performed for the first time at ultrashort echo times (12 $\mu$s). On the basis of a motion-sensitizing magnetization preparation, the available total…
High-resolution magnetic resonance imaging (MRI) is essential in clinical diagnosis. However, its long acquisition time remains a critical issue. Parallel imaging (PI) is a common approach to reduce acquisition time by periodically skipping…
Polarization splitter-rotators (PSRs) are the key elements to realize on-chip polarization manipulation. Current PSRs on thin film lithium niobate (TFLN) rely on sub-micron gaps to realize modes separation, which increase the difficulties…
We propose a unified deep meta-learning framework for accelerated magnetic resonance imaging (MRI) that jointly addresses multi-coil reconstruction and cross-modality synthesis. Motivated by the limitations of conventional methods in…
Magnetic resonance imaging (MRI) is the gold standard imaging modality for numerous diagnostic tasks, yet its usefulness is tempered due to its high cost and infrastructural requirements. Low-cost very-low-field portable scanners offer new…
Portable low-cost MRI systems have the potential to enable point-of-care and timely MRI diagnosis, and to make this imaging modality available to routine scans and to underdeveloped areas. With simplicity, no maintenance, no power…
Functional Magnetic Resonance Imaging (fMRI) data is a widely used kind of four-dimensional biomedical data, which requires effective compression. However, fMRI compressing poses unique challenges due to its intricate temporal dynamics, low…
Electromagnetic induction imaging with atomic magnetometers has disclosed unprecedented domains for imaging, from security screening to material characterization. However, applications to low-conductivity specimens -- most notably for…