Measuring signal-to-noise ratio (SNR) for parallel MRI reconstructions is difficult due to spatially dependent noise amplification. Existing approaches for measuring parallel MRI SNR are limited because they are not applicable to all reconstructions, require significant computation time, or rely on repeated image acquisitions. A new SNR estimation approach is proposed, a hybrid of the repeated image acquisitions method detailed in the National Electrical Manufacturers Association (NEMA) standard and the Monte Carlo based pseudo-multiple replica method, in which the difference between images reconstructed from the unaltered acquired data and that same data reconstructed after the addition of calibrated pseudo-noise is used to estimate the noise in the parallel MRI image reconstruction. This new noise estimation method can be used to rapidly compute the pixel-wise SNR of the image generated from any parallel MRI reconstruction of a single acquisition. SNR maps calculated with the new method are validated against existing SNR calculation techniques.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/mrm.22893 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Patient perspective: Is intensive screening of women at high risk of breast cancer evidence-based medicine or ?
Womens Health (Lond)
January 2025
Department of Pharmacy Practice, Midwestern University College of Pharmacy, Glendale Campus, Glendale, AZ, USA.
In 2023, a breast cancer risk assessment and a subsequent positive test for the BRCA-2 genetic mutation brought me to the uncomfortable intersection of a longstanding career as an advocate for high-quality medical evidence to support shared patient-provider decision making and a new role as a high-risk patient. My search for studies of available risk-management options revealed that the most commonly recommended approach for women with a ⩾20% lifetime breast cancer risk, intensive screening including annual mammography and/or magnetic resonance imaging beginning at age 25-40 years, was supported only by cancer-detection statistics, with almost no evidence on patient-centered outcomes-mortality, physical and psychological morbidity, or quality of life-compared with standard screening or a surgical alternative, bilateral risk-reducing mastectomy. In this commentary, I explore parallels between the use of the intensive screening protocol and another longstanding women's health recommendation based on limited evidence, the use of hormone therapy (HT) for postmenopausal chronic disease prevention, which was sharply curtailed after the publication of the groundbreaking Women's Health Initiative trial in 2002.
View Article and Find Full Text PDF3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data.
Cogn Neurodyn
December 2025
Department of Computational Intelligence, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Tamilnadu India.
Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment.
View Article and Find Full Text PDFMediterranean diet and dementia: MRI marker evidence from meta-analysis.
Eur J Med Res
January 2025
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, 74 Zhongshan Road 2, Guangzhou, 510080, Guangdong, China.
Background: Dementia is a growing public health concern with limited effective treatments. Diet may be a modifiable factor that significantly impacts brain health. Mediterranean diet (MeDi) has been suggested to be associated with brain Magnetic Resonance Imaging (MRI) markers related to dementia, but the existing evidence is inconsistent.
View Article and Find Full Text PDFExplaining cognitive function in multiple sclerosis through networks of grey and white matter features: a joint independent component analysis.
J Neurol
January 2025
NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Faculty of Brain Sciences, UCL Queen Square Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK.
Cognitive impairment (CI) in multiple sclerosis (MS) is only partially explained by whole-brain volume measures, but independent component analysis (ICA) can extract regional patterns of damage in grey matter (GM) or white matter (WM) that have proven more closely associated with CI. Pathology in GM and WM occurs in parallel, and so patterns can span both. This study assessed whether joint-ICA of GM and WM features better explained cognitive function compared to single-tissue ICA.
View Article and Find Full Text PDFAttention incorporated network for sharing low-rank, image and k-space information during MR image reconstruction to achieve single breath-hold cardiac Cine imaging.
Comput Med Imaging Graph
December 2024
Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University of Tuebingen, Tuebingen, Germany.
Cardiac Cine Magnetic Resonance Imaging (MRI) provides an accurate assessment of heart morphology and function in clinical practice. However, MRI requires long acquisition times, with recent deep learning-based methods showing great promise to accelerate imaging and enhance reconstruction quality. Existing networks exhibit some common limitations that constrain further acceleration possibilities, including single-domain learning, reliance on a single regularization term, and equal feature contribution.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!