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English(EN) Sharing standardized image-derived data in computational pathology using DICOM

标准化的DICOM格式支持共享病理图像衍生的数据

研究人员开发了一种使用医学影像数字化和通信(DICOM)标准来标准化和共享计算病理学中图像衍生的数据的方法。该方法解决了诸如感兴趣区域划分和分割掩码等数据共享的挑战,而这些数据的共享一直落后于原始病理图像的共享。该团队将五个数据集编码为DICOM格式,并通过美国国家癌症研究所(NCI)影像数据共享中心(IDC)公开发布,展示了这种标准化的好处,并为更广泛的采用贡献了开源工具。 AI

影响 在计算病理学中标准化图像衍生的数据可以加速医学影像中AI模型开发和验证。

排序理由 该项目是一篇学术论文,详细介绍了一种用于计算病理学中数据标准化和共享的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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标准化的DICOM格式支持共享病理图像衍生的数据

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该项目是一篇学术论文,详细介绍了一种用于计算病理学中数据标准化和共享的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Daniela P. Schacherer (Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany), Christopher P. Bridge (Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, USA), David Clunie (PixelMed Publishing, Bangor,… ·

    使用DICOM在计算病理学中共享标准化图像衍生数据

    arXiv:2609.14530v1 Announce Type: cross Abstract: Development and evaluation of computational pathology methods require access to large and diverse datasets. Over the past decade, various initiatives invested significantly into collecting, centralizing, and sharing pathology imag…