Application of fuzzy c-means segmentation technique for tissue differentiation in MR images of a hemorrhagic glioblastoma multiforme.
about
Fuzzy logic: A "simple" solution for complexities in neurosciences?GLISTR: glioma image segmentation and registrationAutomated tumor volumetry using computer-aided image segmentation.A novel, fast entropy-minimization algorithm for bias field correction in MR images.Tumour volume measurement in head and neck cancer.Breast density quantification with cone-beam CT: a post-mortem study.Quantitative tumor segmentation for evaluation of extent of glioblastoma resection to facilitate multisite clinical trials.Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.Post-treatment with cocaine- and amphetamine-regulated transcript enhances infarct resolution, reinnervation, and angiogenesis in stroke rats - an MRI study.Semi-automatic segmentation software for quantitative clinical brain glioblastoma evaluation.Brain tumor detection and segmentation in a CRF (conditional random fields) framework with pixel-pairwise affinity and superpixel-level features.Ensemble segmentation for GBM brain tumors on MR images using confidence-based averaging.MRI internal segmentation of optic pathway gliomas: clinical implementation of a novel algorithm.Tissue segmentation on MR images of the brain by possibilistic clustering on a 3D wavelet representation.Automatic magnetic resonance tissue characterization for three-dimensional magnetic resonance imaging of the brain.Automatic volumetric measurement of lateral ventricles on magnetic resonance images with correction of partial volume effects.Appraisal of the current staging system for residual medulloblastoma by volumetric analysis.An Extension of the Fuzzy Possibilistic Clustering Algorithm Using Type-2 Fuzzy Logic TechniquesInterval Type-2 Fuzzy Possibilistic C-Means Clustering AlgorithmInterval Type-2 Fuzzy System Design Based on the Interval Type-2 Fuzzy C-Means Algorithm
P2860
Q34630475-E23FA503-5647-4CD8-8238-5A44BB831627Q35211472-1E3C8000-9460-48E5-ACCE-D5BCA75516C0Q35395620-D3C94B32-676B-4562-92FB-F12E9F68F9FDQ36672261-EC1EDDF3-7B82-4E1F-9558-A60DA780BA4CQ36963730-066FA8B8-1B49-40E5-909D-27BEAE514BE4Q37524892-070A65EE-9768-413C-99B3-5D46685CF739Q38950093-9E7934AC-F7F7-415D-B1D0-39E8D98ACA80Q39216556-FBD25487-1632-465D-9F0B-C30170EE62BAQ39968198-83333DAA-DB45-4E14-A17D-F8A3301D9F02Q42076427-48B135F4-A0A6-460C-A84B-8AED9B1640BDQ43542440-309101E2-B164-4A14-9BE3-4D36A78707C8Q44316377-E22F6AFE-404E-4235-9494-F51660B6F045Q51583659-D61C18DE-5721-4003-A0B1-CF682F555DEBQ52080446-763FB2A4-55C9-47D5-A9B9-3C5A23A24A15Q52337130-4A5BA8E5-2BC8-4376-BBF6-892DF26DCF94Q53350389-F4F7F4C8-2A64-4D08-9094-C705343F8320Q55462929-B85BDACF-9864-47BD-8835-3F3395533364Q58488140-591FEFE9-137E-4777-9DD1-39CFA9268A07Q58488267-1A11B892-4015-4D82-8488-40338BBF8AF5Q58488270-E25ECD14-7F45-4A02-A69C-865B0331B09D
P2860
Application of fuzzy c-means segmentation technique for tissue differentiation in MR images of a hemorrhagic glioblastoma multiforme.
description
1995 nî lūn-bûn
@nan
1995年の論文
@ja
1995年学术文章
@wuu
1995年学术文章
@zh
1995年学术文章
@zh-cn
1995年学术文章
@zh-hans
1995年学术文章
@zh-my
1995年学术文章
@zh-sg
1995年學術文章
@yue
1995年學術文章
@zh-hant
name
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@en
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@nl
type
label
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@en
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@nl
prefLabel
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@en
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@nl
P2093
P1476
Application of fuzzy c-means s ...... hagic glioblastoma multiforme.
@en
P2093
Phillips WE 2nd
Phuphanich S
Silbiger ML
Velthuizen RP
P304
P356
10.1016/0730-725X(94)00093-I
P577
1995-01-01T00:00:00Z