A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans.
about
Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI imagesAutomatic Echographic Detection of Halloysite Clay Nanotubes in a Low Concentration Range.Theranostic applications: Non-ionizing cellular and molecular imaging through innovative nanosystems for early diagnosis and therapy.Usefulness of two-point Dixon fat-water separation technique in gadoxetic acid-enhanced liver magnetic resonance imagingTumor growth prediction with reaction-diffusion and hyperelastic biomechanical model by physiological data fusion.Automated segmentation and quantification of liver and spleen from CT images using normalized probabilistic atlases and enhancement estimationA low-interaction automatic 3D liver segmentation method using computed tomography for selective internal radiation therapy.Automated liver sampling using a gradient dual-echo Dixon-based technique.Use of the Resection Map system as guidance during hepatectomy.Magnifying endoscopy of gastric epithelial dysplasia based on the morphologic characteristics.Automated noninvasive classification of renal cancer on multiphase CT.Semantic representation of reported measurements in radiology.Quantitative measurement of contrast enhancement of esophageal squamous cell carcinoma on clinical MDCT.Comparison of two-dimensional and three-dimensional iterative watershed segmentation methods in hepatic tumor volumetricsTumor burden analysis on computed tomography by automated liver and tumor segmentation.Preoperative assessment of postoperative liver function: the importance of residual liver volume.Patient-specific quantification of image quality: An automated technique for measuring the distribution of organ Hounsfield units in clinical chest CT images.Automated liver lesion detection in CT images based on multi-level geometric features.Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets.3D Liver Tumor Segmentation in CT Images Using Improved Fuzzy C-Means and Graph Cuts.A non-parametric permutation method for assessing agreement for distance matrix observations.Adaptive fast marching method for automatic liver segmentation from CT images.Comparison of MRI- and CT-based semiautomated liver segmentation: a validation study.Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT.Object-based analysis of CT images for automatic detection and segmentation of hypodense liver lesions.Simultaneous assessment of liver volume and whole liver fat content: a step towards one-stop shop preoperative MRI protocol.Three-dimensional (3D) printing and its applications for aortic diseases.
P2860
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P2860
A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans.
description
2008 nî lūn-bûn
@nan
2008年の論文
@ja
2008年学术文章
@wuu
2008年学术文章
@zh
2008年学术文章
@zh-cn
2008年学术文章
@zh-hans
2008年学术文章
@zh-my
2008年学术文章
@zh-sg
2008年學術文章
@yue
2008年學術文章
@zh-hant
name
A new fully automatic and robu ...... ssue and tumors from CT scans.
@en
A new fully automatic and robu ...... ssue and tumors from CT scans.
@nl
type
label
A new fully automatic and robu ...... ssue and tumors from CT scans.
@en
A new fully automatic and robu ...... ssue and tumors from CT scans.
@nl
prefLabel
A new fully automatic and robu ...... ssue and tumors from CT scans.
@en
A new fully automatic and robu ...... ssue and tumors from CT scans.
@nl
P2860
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A new fully automatic and robu ...... issue and tumors from CT scans
@en
P2093
Laurent Massoptier
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P356
10.1007/S00330-008-0924-Y
P407
P577
2008-03-28T00:00:00Z