The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) - Test2 - elhamkhani - TriplyDB

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

http://www.wikidata.org/entity/Q30356228

about

A structural and functional magnetic resonance imaging dataset of brain tumour patients Multi-atlas segmentation of biomedical images: A survey Virtual Raters for Reproducible and Objective Assessments in Radiology The pediatric template of brain perfusion.Supervised learning technique for the automated identification of white matter hyperintensities in traumatic brain injury.A Generative Probabilistic Model and Discriminative Extensions for Brain Lesion Segmentation--With Application to Tumor and Stroke.Connectivity precedes function in the development of the visual word form area Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images Multi-modal glioblastoma segmentation: man versus machine.Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma.Hippocampal subfield and medial temporal cortical persistent activity during working memory reflects ongoing encoding.Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification.A model evaluation study for treatment planning of laser-induced thermal therapy.Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features A Novel GBM Saliency Detection Model Using Multi-Channel MRI.Semi-automated segmentation of pre-operative low grade gliomas in magnetic resonance imaging.Glioblastoma Segmentation: Comparison of Three Different Software Packages.Fully Automated Enhanced Tumor Compartmentalization: Man vs. Machine Reloaded.Progressive disease in glioblastoma: Benefits and limitations of semi-automated volumetry.Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping Multi-channel MRI segmentation of eye structures and tumors using patient-specific features.Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization Theoretical model for laser ablation outcome predictions in brain: calibration and validation on clinical MR thermometry images.Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions Low-Rank Atlas Image Analyses in the Presence of Pathologies.Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.Multiscale CNNs for Brain Tumor Segmentation and Diagnosis.A robust statistics driven volume-scalable active contour for segmenting anatomical structures in volumetric medical images with complex conditions Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning Brain extraction in pediatric ADC maps, toward characterizing neuro-development in multi-platform and multi-institution clinical images.Automated Segmentation of Hyperintense Regions in FLAIR MRI Using Deep Learning.PItcHPERFeCT: Primary Intracranial Hemorrhage Probability Estimation using Random Forests on CT.A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI.Effective user interaction in online interactive semantic segmentation of glioblastoma magnetic resonance imaging.The successive projection algorithm as an initialization method for brain tumor segmentation using non-negative matrix factorization Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network.Brain tumor segmentation using holistically nested neural networks in MRI images.An automatic glioma grading method based on multi-feature extraction and fusion.Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.ITK-SNAP: An interactive tool for semi-automatic segmentation of multi-modality biomedical images.

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P2860

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

http://www.wikidata.org/entity/Q30356228

description

2014 nî lūn-bûn

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2014 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2014 թվականի դեկտեմբերին 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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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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TMI.2014.2377694

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IEEE Transactions on Medical Imaging

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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Antonio Criminisi

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Binsheng Zhao

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Brian B Avants

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D Louis Collins

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Danial Lashkari

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Darko Zikic

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Doina Precup

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Dong Hye Ye

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Duygu Sarikaya

http://www.w3.org/2001/XMLSchema#string

Elizabeth Gerstner

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P2860

The case for open computer programs

New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1)

Multifractal texture estimation for detection and segmentation of brain tumors

Instrumentation bias in the use and evaluation of scientific software: recommendations for reproducible practices in the computational sciences

An open source multivariate framework for n-tissue segmentation with evaluation on public data.

A reproducible evaluation of ANTs similarity metric performance in brain image registration

Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain

Unified segmentation

N4ITK: improved N3 bias correction

The virtual skeleton database: an open access repository for biomedical research and collaboration.

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1993-2024

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10.1109/TMI.2014.2377694

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34

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Koen Van Leemput

Stephen J. Price

Nicolas Cordier

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2014-12-04T00:00:00Z

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