Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation. - Test2 - elhamkhani - TriplyDB

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

http://www.wikidata.org/entity/Q34794564

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Multi-atlas segmentation of biomedical images: A survey Improved Automatic Optic Nerve Radius Estimation from High Resolution MRI Structural-Functional Relationships Between Eye Orbital Imaging Biomarkers and Clinical Visual Assessments.Constructing a statistical atlas of the radii of the optic nerve and cerebrospinal fluid sheath in young healthy adults.Disambiguating the optic nerve from the surrounding cerebrospinal fluid: Application to MS-related atrophy Multi-Scale Hippocampal Parcellation Improves Atlas-Based Segmentation Accuracy.

P2860

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P2860

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

http://www.wikidata.org/entity/Q34794564

description

2014 nî lūn-bûn

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2014 թուականի Յուլիսին հրատարակուած գիտական յօդուած

@hyw

2014 թվականի հուլիսին հրատարակված գիտական հոդված

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2014年の論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年论文

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name

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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type

label

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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prefLabel

Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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1.JMI.1.2.024002

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Journal of Medical Imaging

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Evaluation of Multi-Atlas Label Fusion for In Vivo MRI Orbital Segmentation.

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Andrew J Asman

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Bennett A Landman

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Lindsey Thompson

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Louise A Mawn

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Seth A Smith

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Shweta P Khare

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Swetasudha Panda

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P2860

A generative model for image segmentation based on label fusion

Combination strategies in multi-atlas image segmentation: application to brain MR data.

The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.

Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation.

A learning-based wrapper method to correct systematic errors in automatic image segmentation: consistently improved performance in hippocampus, cortex and brain segmentation.

Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain

An atlas-navigated optimal medial axis and deformable model algorithm (NOMAD) for the segmentation of the optic nerves and chiasm in MR and CT images

Evaluation of multiple-atlas-based strategies for segmentation of the thyroid gland in head and neck CT images for IMRT

Radiologic measurement of extraocular muscle volumes in patients with Graves' orbitopathy: a review and guideline.

LoAd: a locally adaptive cortical segmentation algorithm.

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scholarly article

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10.1117/1.JMI.1.2.024002

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4280790

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