Susceptibility weighted imaging (SWI)

By E. Haacke, Yingbiao Xu, Y. Cheng, Jürgen Rainer Reichenbach. Magnetic Resonance in Medicine, 2004

1,633 citations recorded by the source corpus.

Subfields: Radiation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/567557ae0be85763a9d1b3c999daa09f395cd54e

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Citations in the corpus

Quantitative imaging of intrinsic magnetic tissue properties using MRI signal phase: An approach to in vivo brain iron metabolism? (2011, background): “, due to regional differences in the deoxygenated blood volume or in the oxygen extraction fraction (Haacke et al., 2004; Petridou et al., 2010).”
Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition (2011, background): “…in MRI images are typically discarded except in a limited number of cases such as the measuring of flow in angiography, enhancing image contrast in susceptibility weighted images and temperature mapping (Gatehouse et al., 2005; Haacke et al., 2009, 2004; Mittal et al., 2009; Ishihara et al., 1995).”
Susceptibility-Weighted Imaging: Technical Aspects and Clinical Applications, Part 2 (2008, neutral): “53,54 CCMs. CCMs compose 10%–20% of all CNS vascular malformations and consist of abnormally enlarged capillary cavities surrounded by a single layer of endothelium without intervening brain parenchyma.”
Overview of quantitative susceptibility mapping (2017, neutral): “Δφ r → 1⁄4 arctan ∑ Nc l1⁄41 Sn;lS m;l : [13] A.”
Susceptibility Contrast in High Field MRI of Human Brain as a Function of Tissue Iron Content (2008, background): “MRI techniques that are sensitive to the magnetic susceptibility effects induced by iron (Haacke et al., 2004; Ogg et al., 1999) are potentially valuable for the study of diseases with abnormal iron distributions, such as Huntington's disease (HD), Parkinson's disease (PD), Alzheimer's disease…”
Imaging the deep cerebellar nuclei: A probabilistic atlas and normalization procedure (2011, positive): “A phase mask is then multiplied with the magnitude images to create SWI images (Haacke et al., 2009; Haacke et al., 2004).”
MRI Estimates of Brain Iron Concentration in Normal Aging Using Quantitative Susceptibility Mapping (2011, methodology): “Dipole fitting contains no parameters that need tuning and preserves the phase variations caused by internal susceptibility effects more faithfully than high-pass filtering, as employed in susceptibility-weighted imaging (SWI) (Haacke et al., 2005a; Haacke et al., 2004).”
Quantitative Susceptibility Mapping (QSM): Decoding MRI Data for a Tissue Magnetic Biomarker (2014, background): “[3] can be Fourier transformed into B k ð Þ 1⁄4 m0 M=3 k k M ð Þ=k(2) ð Þ.”
Multimodal population brain imaging in the UK Biobank prospective epidemiological study (2016, neutral): “While this might not provide statistical certainty for a diagnosis or interventional recommendation, it should allow for single-patient imaging to be used in a similar way to current state-of-the-art patient-tuned genetic testing.”
Susceptibility-Weighted Imaging: Technical Aspects and Clinical Applications, Part 1 (2008, methodology): “Susceptibility-weighted imaging (SWI) is a new means to enhance contrast in MR imaging.(1-56) Until recently, with the exception of phase being used for large-vessel flow quantification or for use in inversion recovery sequences, most diagnostic MR imaging relied only on the reading of magnitude inf”
Principles, techniques, and applications of T2*-based MR imaging and its special applications. (2009, background): “Phase itself can be a superb source of contrast, with or without T2* effects (18).”
Toward in vivo histology: A comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2⁎-imaging at ultra-high magnetic field strength (2013, neutral): “The laminas of the basal ganglia have recently been visualized using high-resolution SWI, albeit, with dramatically low SNR, in the globus pallidus (Abosch et al., 2010; Nölte et al., 2012).”
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank (2017, methodology): “Venograms were calculated using an established reconstruction (Haacke et al., 2004), in which magnitude images are multiplied by a further filtering of the phase data to enhance the appearance of veins.”
Morphology Enabled Dipole Inversion for Quantitative Susceptibility Mapping Using Structural Consistency Between the Magnitude Image and the Susceptibility Map (2011, neutral): “Because MEDI QSM is a postprocessing method for gradient echo MRI, upon further refinement and stabilization, the MEDI algorithm should be compared with other processing methods such as R2⁎ mapping and SWI (Haacke et al., 2004) and evaluated in pertinent applications to establish its clinical and sc”
DeepQSM - Using Deep Learning to Solve the Dipole Inversion for MRI Susceptibility Mapping (2018, methodology): “F In order to obtain a quantitative susceptibility map, an image is acquired using an MRI sequence where the signal phase is sensitive to local magnetic ﬁeld changes, such as a gradient-recalled echo sequence (23–25).”