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Surface-functionalized nanomaterials can act as theranostic agents that detect disease and track biological processes using hyperpolarized magnetic resonance imaging (MRI). Candidate materials are sparse however, requiring spinful nuclei…

Ultra-low-field (ULF, <0.1 T) magnetic resonance imaging (MRI) systems offer advantages in cost, portability, and accessibility, but their current utility is still limited by low signal-to-noise ratio (SNR). Deep learning (DL)-based…

In Magnetic Resonance Imaging (MRI), to achieve sufficient Signal to Noise Ratio (SNR), the electrical performance of the RF coil is critical. We developed a device (microcoil) based on the original concept of monolithic resonator. This…

High resolution magnetic resonance (MR) images are desired for accurate diagnostics. In practice, image resolution is restricted by factors like hardware, cost and processing constraints. Recently, deep learning methods have been shown to…

Machine Learning · Computer Science 2018-09-11 Venkateswararao Cherukuri , Tiantong Guo , Steven J. Schiff , Vishal Monga

Neural implicit surface reconstruction has achieved remarkable progress recently. Despite resorting to complex radiance modeling, state-of-the-art methods still struggle with textureless and specular surfaces. Different from RGB images,…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Guangcheng Chen , Yicheng He , Li He , Hong Zhang

Portable, low-field Magnetic Resonance Imaging (MRI) scanners are increasingly being deployed in clinical settings. However, key barriers to their widespread use include low signal-to-noise ratio (SNR), generally low image quality, and long…

Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform. Numerical results show that the…

Other Computer Science · Computer Science 2011-03-28 S. Satheesh , KVSVR Prasad

Over the past several decades, many different types of computational imaging approaches have been proposed for improving MRI. In this paper, we provide an overview of methods that assume that MRI Fourier data is linearly predictable. Linear…

Signal Processing · Electrical Eng. & Systems 2020-02-19 Justin P. Haldar , Kawin Setsompop

Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measurements has the potential to reduce medical costs, minimize stress to patients and make MRI possible in applications where it is currently prohibitively slow or expensive.…

During the past ten years nanostructures have been subject of active research. Fabrication of such systems follows well developed methods. The increase in the number of materials available for research and applications requires that the…

Materials Science · Physics 2007-05-23 G. V. Kurlyandskaya , S. M. Bhagat

Imaging with multiple modalities or multiple channels is becoming increasingly important for our modern society. A key tool for understanding and early diagnosis of cancer and dementia is PET-MR, a combined positron emission tomography and…

Image and Video Processing · Electrical Eng. & Systems 2020-07-24 Matthias J. Ehrhardt

Quantitative MRI is highly desirable in terms of intrinsic tissue parameters such as T1, T2 and proton density. This approach promises to minimize diagnostic variability and differentiate normal and pathological tissues by comparing tissue…

Medical Physics · Physics 2018-06-21 Qing Lyu , Ge Wang

Magnetic Resonance Imaging (MRI) is a valuable clinical diagnostic modality for spine pathologies with excellent characterization for infection, tumor, degenerations, fractures and herniations. However in surgery, image-guided spinal…

Image and Video Processing · Electrical Eng. & Systems 2021-02-11 Madhu Mithra K K , Sriprabha Ramanarayanan , Keerthi Ram , Mohanasankar Sivaprakasam

Determining the brain perfusion is an important task for the diagnosis and treatment of vascular diseases such as occlusions and intracerebral haemorrhage. Even after successful diagnosis and treatment, there is a high risk of restenosis or…

Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique offering high-resolution 3D images and valuable insights into human tissue conditions. Even at present, the refinement of denoising methods for MRI remains a…

Image and Video Processing · Electrical Eng. & Systems 2023-08-29 Shiao Li

Wide-field imaging Mueller polarimetry is a revolutionary, label-free, and non-invasive modality for computer-aided intervention: in neurosurgery it aims to provide visual feedback of white matter fibre bundle orientation from derived…

Magnetic resonance imaging (MRI) is a common and life-saving medical imaging technique. However, acquiring high signal-to-noise ratio MRI scans requires long scan times, resulting in increased costs and patient discomfort, and decreased…

Image and Video Processing · Electrical Eng. & Systems 2023-02-07 Tiange Xiang , Mahmut Yurt , Ali B Syed , Kawin Setsompop , Akshay Chaudhari

The inherently low signal-to-noise ratio of NMR and MRI is now being addressed by hyperpolarization methods. For example, iridium-based catalysts that reversibly bind both parahydrogen and ligands in solution can hyperpolarize protons…

Presently, Magnetic Resonance Imaging (MRI) magnets must deliver excellent magnetic field (B0) uniformity to achieve optimum image quality. Long magnets can satisfy the homogeneity requirements but require considerable superconducting…

Medical Physics · Physics 2024-02-15 Marina Manso Jimeno , John Thomas Vaughan , Sairam Geethanath

Magnetic resonance imaging (MRI) is central to the diagnosis of multiple sclerosis, where the identification of biomarkers such as the central vein sign benefits from high-resolution images. However, most clinical brain MRI scans are…

Optimization and Control · Mathematics 2026-03-05 Matteo Cannas , Alice Mariottini , Luca Massacesi , Federica Porta , Simone Rebegoldi , Andrea Sebastiani
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