Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
about
Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosisPrinciples of T2 *-weighted dynamic susceptibility contrast MRI technique in brain tumor imaging.Biomarkers and surrogate outcomes in neurodegenerative disease: lessons from multiple sclerosis.Segmentation of electron tomographic data sets using fuzzy set theory principlesDiminished visibility of cerebral venous vasculature in multiple sclerosis by susceptibility-weighted imaging at 3.0 Tesla.Reproducible segmentation of white matter hyperintensities using a new statistical definitionNuclear magnetic resonance monitoring of treatment and prediction of outcome in multiple sclerosisSegmentation of multiple sclerosis lesions in MR images: a review.Automated detection of multiple sclerosis lesions in serial brain MRI.Clinical applications of imaging disease burden in multiple sclerosis: MRI and advanced imaging techniques.Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates.Unified approach for multiple sclerosis lesion segmentation on brain MRI.Quantitative assessment of iron accumulation in the deep gray matter of multiple sclerosis by magnetic field correlation imaging.Improved operator agreement and efficiency using the minimum area contour change method for delineation of hyperintense multiple sclerosis lesions on FLAIR MRIParallel fuzzy connected image segmentation on GPU.A fully automated method for quantifying and localizing white matter hyperintensities on MR images.A reference-free method for brightness compensation and contrast enhancement of micrographs of serial sectionsSegmentation and quantification of black holes in multiple sclerosis.Reduced binding of Pittsburgh Compound-B in areas of white matter hyperintensitiesMenopausal hot flashes and white matter hyperintensitiesGPU-based relative fuzzy connectedness image segmentation.Quantitative MRI assessment of leukoencephalopathyfMRI correlates of white matter hyperintensities in late-life depression.Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine.Reliability of tumor volume estimation from MR images in patients with malignant glioma. Results from the American College of Radiology Imaging Network (ACRIN) 6662 Trial.A comprehensive approach to the segmentation of multichannel three-dimensional MR brain images in multiple sclerosis.Regional cortical thickness in relapsing remitting multiple sclerosis: A multi-center study.Parallel Fuzzy Segmentation of Multiple Objects.Age-related changes in conventional and magnetization transfer MR imaging in elderly people: comparison with neurocognitive performance.FLAIR histogram segmentation for measurement of leukoaraiosis volume.Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.MRI FLAIR lesion segmentation in multiple sclerosis: Does automated segmentation hold up with manual annotation?Refinement-cut: user-guided segmentation algorithm for translational science.A Model of Population and Subject (MOPS) Intensities With Application to Multiple Sclerosis Lesion Segmentation.Intensity Standardization Simplifies Brain MR Image Segmentation.Trimmed-likelihood estimation for focal lesions and tissue segmentation in multisequence MRI for multiple sclerosisReal-time segmentation by Active Geometric Functions.Automatic segmentation of white matter hyperintensities by an extended FitzHugh & Nagumo reaction diffusion model.Immunological biomarkers associated with brain structure and executive function in late-life depression: exploratory pilot study.Segmentation with gray-scale connectedness can separate arteries and veins in MRA.
P2860
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P2860
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
description
1997 nî lūn-bûn
@nan
1997年の論文
@ja
1997年学术文章
@wuu
1997年学术文章
@zh
1997年学术文章
@zh-cn
1997年学术文章
@zh-hans
1997年学术文章
@zh-my
1997年学术文章
@zh-sg
1997年學術文章
@yue
1997年學術文章
@zh-hant
name
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@en
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@nl
type
label
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@en
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@nl
prefLabel
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@en
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@nl
P2093
P356
P1476
Multiple sclerosis lesion quantification using fuzzy-connectedness principles.
@en
P2093
P304
P356
10.1109/42.640750
P577
1997-10-01T00:00:00Z