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Head and neck cancer (HNC) patients who undergo radiotherapy (RT) may experience anatomical changes during treatment, compromising the validity of the initial treatment plan, necessitating replanning. However, replanning disrupts clinical…
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…
Explainability is a highly demanded requirement for applications in high-risk areas such as medicine. Vision Transformers have mainly been limited to attention extraction to provide insight into the model's reasoning. Our approach combines…
How the human brain adjusts fuel handling and its bioenergetic state during changing glucose levels remains difficult to assess noninvasively. In this study, we established an interleaved multinuclear 7 T MR spectroscopy protocol to track a…
The human lung and its functions are extremely sensitive to gravity, however the conventional high-field magnets used for most laser-polarized 3He MRI of the human lung restrict subjects to lying horizontally. Imaging of human lungs using…
MR experiments are essential for studying brain metabolism, yet preclinical 1H-MRSI remains underdeveloped, with significant limitations in SNR, acquisition speed, and automated data processing. Although recent advances-such as accelerated…
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…
Portable medical imaging (PMI) has emerged as an important solution for point-of-care diagnosis in emergency, rural, and resource-limited settings where conventional imaging infrastructure is not readily available. Modalities such as…
Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) suffer from inherently low sensitivity due to the weak thermal polarization of nuclear spins. Parahydrogen-induced polarization (PHIP) offers a powerful route to enhance…
Machine learning (ML) is a subfield of Artificial intelligence (AI), and its applications in radiology are growing at an ever-accelerating rate. The most studied ML application is the automated interpretation of images. However, natural…
This study presents the progress of our recent research regarding wireless measurements of the human body. First, we explain radar imaging algorithms for screening passengers at security checkpoints that can process data faster than…
Current magnetic resonance imaging (MRI) requires the subject to remain stationary to limit motion artifacts and avoid unwanted field-induced brain stimulation. However, imaging during large-scale motion could enable studies in which motion…
Objectives: Analyze the types of studies and algorithms that are most applied, Identify the anatomical regions treated. Determine the application of parallel techniques used in studies carried out between 2010 and 2022 in research on noise…
Electropermeabilization is a clinical technique in cancer treatment to locally stimulate the cell metabolism. It is based on electrical fields that change the properties of the cell membrane. With that, cancer treatment can reach the cell…
Robust generalization beyond training distributions remains a critical challenge for deep neural networks. This is especially pronounced in medical image analysis, where data is often scarce and covariate shifts arise from different…
Histopathology plays a central role in diagnosis of many diseases including solid cancers. Efforts are underway to transform this subjective art form to an objective and quantitative science. Coherent Raman imaging (CRI), a label-free…
Increasing attention is being paid to millimeter-wave (mmWave), 30 GHz to 300 GHz, and terahertz (THz), 300 GHz to 10 THz, sensing applications including security sensing, industrial packaging, medical imaging, and non-destructive testing.…
A novel method for fast and high-resolution metabolic imaging, called ECcentric Circle ENcoding TRajectorIes for Compressed sensing (ECCENTRIC), has been developed and implemented at 7 Tesla MRI. ECCENTRIC is a non-Cartesian…
Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related…
There is a growing interest in portable MRI (pMRI) systems for point-of-care imaging, particularly in remote or resource-constrained environments. However, the computational complexity of pMRI, especially in image reconstruction and machine…