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Medical imaging equipment, medical image processing equipment, medical image processing programs, and machine learning models

机译:医学成像设备,医学图像处理设备,医学图像处理程序和机器学习模型

摘要

PROBLEM TO BE SOLVED: To provide a medical imaging device for improving image quality by accurately reducing noise while preventing inappropriate image processing by enabling analysis of image processing contents in image processing using a machine learning model. SOLUTION: The medical image acquisition unit for acquiring a medical image, the noise evaluation unit 211 for determining whether or not the noise in the medical image exceeds a predetermined reference value, and the noise evaluation unit have noise exceeding the reference value. The noise reduction unit 212 is provided with a noise reduction unit 212 for reducing the noise of the medical image determined to be so, and the noise reduction unit collects a plurality of training data sets consisting of an image containing noise as input data and an image not containing noise as output data. It has a plurality of layers that fold the input image, and one of the multiple layers incorporates a plurality of linear or non-linear filters having a predetermined fold coefficient. A machine learning model that includes a filter layer is used to reduce noise in medical images. [Selection diagram] Fig. 2
机译:解决的问题:提供一种医学成像装置,其通过在机器学习模型中进行图像处理中的图像处理内容的分析,从而通过准确地减少噪声,同时防止不适当的图像处理来改善图像质量。解决方案:用于获取医学图像的医学图像获取单元,用于确定医学图像中的噪声是否超过预定参考值的噪声评估单元211,以及噪声评估单元具有超过参考值的噪声。降噪单元212设置有降噪单元212,用于降低确定为如此的医学图像的噪声,并且降噪单元收集多个训练数据集,该训练数据集包括包含噪声的图像作为输入数据和图像。不包含噪声作为输出数据。它具有折叠输入图像的多个层,并且多个层之一并入了具有预定折叠系数的多个线性或非线性滤波器。包含滤镜层的机器学习模型用于减少医学图像中的噪声。 [选择图]图2

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