Daniel Hägg and Emil Styrke

Image Processing
Imaging vendors have options for image processing hardware
When developing new imaging systems, OEMs can choose from many types of computer hardware platforms. Platform selection in turn affects the type of image processing to be used, which then influences the radiologist's work when viewing medical images. Software architects from advanced visualization developer ContextVision offer some guidance.
March 26, 2015
2014 01 23 14 51 33 773 Data Stream 200
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A lollipop plots showing the most important nodes by RF-MLA selected by Mean decrease in Gini for a 7 tesla fMRI dataset, with longer sticks meaning greater importance. Each group of networks’ nodes has its own color matching the same network’s color in the brain map. Nodes' names preceded by a red asterisk are repeated among different networks, matching the red nodes in the brain map, which appear in multiple networks.
ISMRM 2025
ISMRM: fMRI identifies key brain regions in superagers
Functional MRI (fMRI) has shed new light on brain areas that differentiate superagers from cognitively average older adults.
Computer Brain Hemisphere
ISMRM 2025
ISMRM: Deep-learning tool shows promise in diagnosing frontotemporal dementia
Honolulu
ISMRM 2025
ISMRM: Novel MRI technique identifies changes in brain entropy
Hawaii Honolulu
ISMRM 2025
ISMRM: Diffusion MRI predicts progression to Alzheimer's
Hawaii Honolulu
ISMRM 2025
ISMRM: Exercise may reduce structural brain changes
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ISMRM: fMRI identifies key brain regions in superagers
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Functional MRI (fMRI) has shed new light on brain areas that differentiate superagers from cognitively average older adults.
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A lollipop plots showing the most important nodes by RF-MLA selected by Mean decrease in Gini for a 7 tesla fMRI dataset, with longer sticks meaning greater importance. Each group of networks’ nodes has its own color matching the same network’s color in the brain map. Nodes' names preceded by a red asterisk are repeated among different networks, matching the red nodes in the brain map, which appear in multiple networks.
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An automated brain volumetry model for MRI shows promising accuracy in diagnosing FTD, according to research presented at ISMRM 2025.
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Computer Brain Hemisphere
ISMRM: Novel MRI technique identifies changes in brain entropy
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A novel MRI technique called quantitative magnetization transfer (qMT) identifies changes in brain entropy due to normal aging.
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ISMRM: Diffusion MRI predicts progression to Alzheimer's
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A presentation at ISMRM 2025 suggests diffusion MRI could predict progression from mild cognitive impairment to Alzheimer's.
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ISMRM: Exercise may reduce structural brain changes
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Researchers examine the relationship between exercise intensity, brain volume changes, and depression.
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ISMRM: Contrast-free MR angiography comparable to CT for PE detection
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University of Michigan researchers investigate detectability of pulmonary embolism by noncontrast MR angiography at 0.55 tesla.
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Axial (A) and Coronal (B) CTPA show multiple partial intraluminal filling defects along the course of the right middle lobar segmental branches (medial segment) (yellow arrow) and lower lobar and postero-medial segmental branches (green arrow). Note the low-signal filling defects on the axial and coronal 0.55T MRI sequence.
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ISMRM research indicates that higher insulin resistance is associated with less myelin in women.
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Associations between insulin resistance and MWF. (A) Distribution of insulin resistance, stratified by sex. (B) Regression analysis of whole-brain MWF vs. log (HOMA-IR), adjusted for age and age². Shaded regions indicate 95% confidence intervals. (C) Regression analysis of whole-brain MWF vs. log (HOMA-IR), adjusted for age, age², sex, and log (HOMA-IR) sex. Graphics and caption courtesy of Nathan Zhang, PhD, and the ISMRM.
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Representative T2-FLAIR, CBF maps, choroid plexus segment, free-water maps, ALPS ROI, and 3D T1BRAVO from a stroke patient, and a healthy control. Both individuals are 64 years old in chronological age. The patient displays an evident ischemic lesion in the basal ganglia region on T2-FLAIR imaging. The distinctions between the patient and the healthy control are as follows: CBF (32.22 ml/100g/min vs. 47.70 ml/100g/min), CPVF (1.47 vs. 0.84), VCSFVF (32.50 vs. 11.00), MSFW (0.0455 vs. 0.0313), ALPS (1.04 vs. 1.54), and BPAD (13.21 vs. -1.60).
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Researchers at ISMRM highlighted the success of a trimodal MR-PET-FUS system built around a low-field MRI scanner. MR (top) and PET (bottom) images were acquired simultaneously before and after FUS heating.
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Protocol time and recall bounds as a function of AI specificity and sensitivity. On the top, the bounds are shown as a function of the specificity of the AI algorithm, for a fixed value of the sensitivity of that same AI model. On the bottom, the bounds are shown as a function of the sensitivity, for a fixed specificity. Graphics and caption courtesy of the ISMRM.
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PET/MRI scans have revealed the mechanism underlying a brain stimulation technique for treating neurological and psychiatric conditions.
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