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Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from…

医学物理 · 物理学 2023-02-13 Jessie Mosso , Dunja Simicic , Cristina Cudalbu , Ileana O. Jelescu

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to infer estimates of local tissue magnetism (magnetic susceptibility), which has been shown useful to provide novel image contrast and as biomarkers of abnormal tissue.…

医学物理 · 物理学 2019-04-16 Juan Liu , Kevin M. Koch

The signal to noise ratio (SNR) fundamentally limits the information accessible by magnetic resonance imaging (MRI). This limitation has been addressed by a host of denoising techniques, recently including so-called MPPCA: Principal…

医学物理 · 物理学 2022-10-18 Jonas L. Olesen , Andrada Ianus , Leif Østergaard , Noam Shemesh , Sune N. Jespersen

PURPOSE: Multi-exponential relaxometry is a powerful tool for characterizing tissue, but generally requires high image signal-to-noise ratio (SNR). This work evaluates the use of principal-component-analysis (PCA) denoising to mitigate…

In the human brain, essential iron molecules for proper neurological functioning exist in transferrin (tf) and ferritin (Fe3) forms. However, its unusual increment manifests iron overload, which reacts with hydrogen peroxide. This reaction…

神经元与认知 · 定量生物学 2022-11-10 Shradha Verma , Tripti Goel , M Tanveer

Diffusion-weighted MRI (DWI) at high b-values often suffers from low signal-to-noise ratio (SNR), making image quality poor. Marchenko-Pastur PCA (MPPCA) is a popular method to reduce noise, but it uses a fixed patch size across the whole…

图像与视频处理 · 电气工程与系统科学 2025-12-05 Ananya Singhal , Dattesh Dayanand Shanbhag , Sudhanya Chatterjee

MP-PCA denoising has become the method of choice for denoising in MRI since it provides an objective threshold to separate the desired signal from unwanted thermal noise components. In rodents, thermal noise in the coils is an important…

医学物理 · 物理学 2022-11-29 Francisca F. Fernandes , Jonas L. Olesen , Sune N. Jespersen , Noam Shemesh

Quantitative susceptibility mapping (QSM) is an MRI phase-based post-processing technique to extract the distribution of tissue susceptibilities, demonstrating significant potential in studying neurological diseases. However, the…

图像与视频处理 · 电气工程与系统科学 2024-06-19 Min Li , Chen Chen , Zhuang Xiong , Ying Liu , Pengfei Rong , Shanshan Shan , Feng Liu , Hongfu Sun , Yang Gao

Quantitative susceptibility mapping (QSM) has been increasingly applied in longitudinal studies of neurodegenerative diseases and aging to assess temporal alterations in brain iron and myelin. The accuracy of such investigations depends on…

定量方法 · 定量生物学 2026-05-05 Jiye Kim , Hwihun Jeong , Taechang Kim , Eunseon Jeong , Jinhee Jang , Yangsean Choi , Jongho Lee

Purpose: To introduce, develop, and evaluate a novel denoising technique for diffusion MRI that leverages non-linear redundancy in the data to boost the SNR while preserving signal information. Methods: We exploit non-linear redundancy of…

Quantitative susceptibility mapping (QSM) is a valuable magnetic resonance imaging (MRI) contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed…

图像与视频处理 · 电气工程与系统科学 2021-01-29 Yang Gao , Xuanyu Zhu , Bradford A. Moffat , Rebecca Glarin , Alan H. Wilman , G. Bruce Pike , Stuart Crozier , Feng Liu , Hongfu Sun

New multinuclear MRI techniques, such as sodium MRI, generally suffer from low image quality due to an inherently low signal. Postprocessing methods, such as image denoising, have been developed for image enhancement. However, the…

Quantitative MRI (qMRI) offers significant advantages over weighted images by providing objective parameters related to tissue properties. Deep learning-based methods have demonstrated effectiveness in estimating quantitative maps from…

计算机视觉与模式识别 · 计算机科学 2024-10-15 Shishuai Wang , Hua Ma , Juan A. Hernandez-Tamames , Stefan Klein , Dirk H. J. Poot

Quantitative susceptibility mapping (QSM) has gained broad interests in the field by extracting biological tissue properties, predominantly myelin, iron and calcium from magnetic resonance imaging (MRI) phase measurements in vivo. Thereby,…

图像与视频处理 · 电气工程与系统科学 2019-12-12 Woojin Jung , Steffen Bollmann , Jongho Lee

Quantitative magnetic resonance imaging (qMRI) allows images to be compared across sites and time points, which is particularly important for assessing long-term conditions or for longitudinal studies. The multiparametric mapping (MPM)…

信号处理 · 电气工程与系统科学 2024-10-24 Klara Baś , Christian Lambert , John Ashburner

Quantitative susceptibility mapping (QSM) utilizes MRI signal phase to estimate local tissue susceptibility, which has been shown useful to provide novel image contrast and as biomarkers of abnormal tissue. QSM requires addressing a…

医学物理 · 物理学 2019-06-03 Juan Liu , Kevin M. Koch

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high-resolution over the entire brain. The constant demand for higher…

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that estimates magnetic susceptibility of tissue from Larmor frequency offset measurements. The generation of QSM requires solving a challenging…

医学物理 · 物理学 2020-08-18 Juan Liu , Kevin M. Koch

Motivation - The test-retest reliability of quantitative susceptibility mapping (QSM) is affected by parameters of the acquisition protocol such as the angulation of acquisition plane with respect to the B0 field direction and spatial…

图像与视频处理 · 电气工程与系统科学 2024-11-26 Shuai Huang , Thomas Denney , Deqiang Qiu

Quantitative Susceptibility Mapping (QSM) can estimate the underlying tissue magnetic susceptibility and reveal pathology. Current deep-learning-based approaches to solve the QSM inverse problem are restricted on fixed image resolution.…

医学物理 · 物理学 2019-08-02 Juan Liu , Kevin M. Koch
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