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Image modification and detection using massive training artificial neural networks (MTANN)

机译:使用大规模训练人工神经网络(MTANN)进行图像修改和检测

摘要

A method, system, and computer program product for modifying an appearance of an anatomical structure in a medical image, e.g., rib suppression in a chest radiograph. The method includes: acquiring, using a first imaging modality, a first medical image that includes the anatomical structure; applying the first medical image to a trained image processing device to obtain a second medical image, corresponding to the first medical image, in which the appearance of the anatomical structure is modified; and outputting the second medical image. Further, the image processing device is trained using plural teacher images obtained from a second imaging modality that is different from the first imaging modality. In one embodiment, the method also includes processing the first medical image to obtain plural processed images, wherein each of the plural processed images has a corresponding image resolution; applying the plural processed images to respective multi-training artificial neural networks (MTANNs) to obtain plural output images, wherein each MTANN is trained to detect the anatomical structure at one of the corresponding image resolutions; and combining the plural output images to obtain a second medical image in which the appearance of the anatomical structure is enhanced.
机译:一种用于修改医学图像中的解剖结构的外观的方法,系统和计算机程序产品,例如,胸部X光照片中的肋骨抑制。该方法包括:使用第一成像模态获取包括解剖结构的第一医学图像;以及将所述第一医学图像应用于训练后的图像处理设备,以获得与所述第一医学图像相对应的第二医学图像,所述第二医学图像中所述解剖结构的外观被修改;输出第二医学图像。此外,使用从不同于第一成像模态的第二成像模态获得的多个教师图像来训练图像处理装置。在一个实施例中,该方法还包括处理第一医学图像以获得多个处理后的图像,其中多个处理后的图像中的每个具有对应的图像分辨率;将多个处理后的图像应用于各自的多训练人工神经网络(MTANN)以获得多个输出图像,其中训练每个MTANN以在对应的图像分辨率之一下检测解剖结构;组合多个输出图像以获得第二医学图像,其中所述第二医学图像增强了所述解剖结构的外观。

著录项

  • 公开/公告号US2005100208A1

    专利类型

  • 公开/公告日2005-05-12

    原文格式PDF

  • 申请/专利权人 KENJI SUZUKI;KUNIO DOI;

    申请/专利号US20030703617

  • 发明设计人 KENJI SUZUKI;KUNIO DOI;

    申请日2003-11-10

  • 分类号G06K9/62;G06K9/00;

  • 国家 US

  • 入库时间 2022-08-21 22:26:06

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