Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction.

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作者： Mariam,Aboian ^[1] ; Khaled,Bousabarah ^[2] ; Eve,Kazarian ^[1] ; Tal,Zeevi ^[3] ; Wolfgang,Holler ^[2] ; Sara,Merkaj ^[1] ; Gabriel,Cassinelli Petersen ^[1] ; Ryan,Bahar ^[1] ; Harry,Subramanian ^[1] ; Pranay,Sunku ^[1] ; Elizabeth,Schrickel ^[1] ; Jitendra,Bhawnani ^[3] ; Mathew,Zawalich ^[3] ; Amit,Mahajan ^[3] ; Ajay,Malhotra ^[3] ; Sam,Payabvash ^[3] ; Irena,Tocino ^[3] ; MingDe,Lin ^[4] ; Malte,Westerhoff ^[2]

作者单位： Department of Radiology and Biomedical Imaging, Brain Tumor Research Group, Yale School of Medicine, Yale University, New Haven, CT, United States. ^[1] Visage Imaging, GmbH, Berlin, Germany. ^[2] Department of Radiology and Biomedical Imaging, Yale School of Medicine, Yale University, New Haven, CT, United States. ^[3] Department of Radiology, Yale University and Visage Imaging, New Haven, CT, United States. ^[4]

关键词 BraTS PACS (picture archiving and communication system)artificial intelligence (AL)brain tumor feature extraction glioma machine learning (ML)segmentation

DOI 10.3389/fnins.2022.860208

PMID 36312024

发布时间 2022-11-02

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Frontiers in neuroscience

2022年16卷

860208页

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Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction.

Frontiers in neuroscience

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Frontiers in neuroscience

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Clinical implementation of artificial intelligence in neuroradiology with development of a novel workflow-efficient picture archiving and communication system-based automated brain tumor segmentation and radiomic feature extraction.

Frontiers in neuroscience

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Frontiers in neuroscience

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