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标题:Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks.
时间:2020-01-15 10:11:15
DOI:10.1038/s41591-019-0715-9
PMID:31907460
大小:20827 kb
页数:25 PAGES
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目录:
  • Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks
    • Online content
    • Fig. 1 Intraoperative diagnostic pipeline using SRH and deep learning.
    • Fig. 2 Prospective clinical trial of SRH plus CNN versus conventional H&E histology.
    • Fig. 3 Activation maximization reveals a hierarchy of learned SRH feature representations.
    • Fig. 4 Semantic segmentation of SRH images identifies tumor-infiltrated and diagnostic regions.
    • Extended Data Fig. 1 SRH image dataset and CNN training.
    • Extended Data Fig. 2 A taxonomy of intraoperative SRH diagnostic classes to inform intraoperative decision-making.
    • Extended Data Fig. 3 Inference algorithm for patient-level brain tumor diagnosis.
    • Extended Data Fig. 4 Prospective clinical trial design and recruitment.
    • Extended Data Fig. 5 Mahalanobis distance-based confidence score.
    • Extended Data Fig. 6 Error analysis of pathologist-based classification of brain tumors.
    • Extended Data Fig. 7 Activation maximization to elucidate SRH feature extraction using Inception-ResNet-v2.
    • Extended Data Fig. 8 t-SNE plot of internal CNN feature representations for clinical trial patients.
    • Extended Data Fig. 9 Methods and results of SRH segmentation.
    • Extended Data Fig. 10 Localization of metastatic brain tumor infiltration in SRH images.
  • SpringerNature_NatMed_715_ESM2.pdf
    • nr-reporting-summary_Page_1
    • nr-reporting-summary_Page_2
    • nr-reporting-summary_Page_3

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