Automatic human knee cartilage segmentation from 3D magnetic resonance images.
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Registration of Magnetic Resonance Image Series for Knee Articular Cartilage Analysis: Data from the Osteoarthritis Initiative.First-line analysis of the effects of treatment on progression of structural changes in knee osteoarthritis over 24 months: data from the osteoarthritis initiative progression cohort.Long-Term Effects of Glucosamine and Chondroitin Sulfate on the Progression of Structural Changes in Knee Osteoarthritis: Six-Year Followup Data From the Osteoarthritis Initiative.Fully automated, level set-based segmentation for knee MRIs using an adaptive force function and template: data from the osteoarthritis initiative.Three-dimensional double-echo steady-state (3D-DESS) magnetic resonance imaging of the knee: establishment of flip angles for evaluation of cartilage at 1.5 T and 3.0 T.The presence of meniscal lesions is a strong predictor of neuropathic pain in symptomatic knee osteoarthritis: a cross-sectional pilot study.Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision makingFully automatic analysis of the knee articular cartilage T1ρ relaxation time using voxel-based relaxometry.What is the predictive value of MRI for the occurrence of knee replacement surgery in knee osteoarthritis?New and emerging treatments for osteoarthritis management: will the dream come true with personalized medicine?Fully automated segmentation of cartilage from the MR images of knee using a multi-atlas and local structural analysis methodAutomatic segmentation of the glenohumeral cartilages from magnetic resonance images.Structure-enhanced local phase filtering using L0 gradient minimization for efficient semiautomated knee magnetic resonance imaging segmentation.Automatic atlas-based three-label cartilage segmentation from MR knee images.Automated analysis of hip joint cartilage combining MR T2 and three-dimensional fast-spin-echo images.Application of a semi-automatic cartilage segmentation method for biomechanical modeling of the knee joint.Knee cartilage segmentation and thickness computation from ultrasound images.EM segmentation of the distal femur and proximal tibia: a high-throughput approach to anatomic surface generation.Exploring determinants predicting response to intra-articular hyaluronic acid treatment in symptomatic knee osteoarthritis: 9-year follow-up data from the Osteoarthritis Initiative.Impact of oral osteoarthritis therapy usage among other risk factors on knee replacement: a nested case-control study using the Osteoarthritis Initiative cohort
P2860
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P2860
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
@zh-hant
name
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@en
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@nl
type
label
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@en
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@nl
prefLabel
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@en
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@nl
P50
P1476
Automatic human knee cartilage segmentation from 3D magnetic resonance images.
@en
P2093
Pierre Dodin
P356
10.1109/TBME.2010.2058112
P577
2010-07-15T00:00:00Z