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Multi modal registration of structural features and mutual information of medical image

机译:结构特征和医学图像互信息的多模式配准

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摘要

Based on automatic matching of medical images synthesized by complementary characteristic, this paper makes full use of SURF algorithm's good scale rotation invariance and HOG algorithm to describe local shape information better, showing good robustness when affected by geometric and optical deformation of graphics. Each performance of algorithm is comprehensively evaluated through the experiment, with accuracy of reaching 98%, meeting the actual application requirements. The algorithm shows good performance and application potential in the field of medical image matching. At the same time, since medical images are affected by lighting, equipment, scene and other factors in the acquisition process, there are large differences, which affect the robustness of the algorithm to a certain extent. Experiments show that this method has high accuracy in digital medical image matching and can be used to construct automatic matching system of medical images. (C) 2018 Elsevier B.V. All rights reserved.
机译:在基于互补特征合成的医学图像自动匹配的基础上,充分利用了SURF算法的良好尺度旋转不变性和HOG算法来更好地描述局部形状信息,在受到图形的几何和光学变形影响时表现出良好的鲁棒性。通过实验对算法的各项性能进行了全面评估,准确率达到98%,可以满足实际应用需求。该算法在医学图像匹配领域具有良好的性能和应用潜力。同时,由于医学图像在采集过程中会受到照明,设备,场景等因素的影响,因此存在较大的差异,在一定程度上影响了算法的鲁棒性。实验表明,该方法在数字医学图像匹配中具有很高的精度,可用于构建医学图像自动匹配系统。 (C)2018 Elsevier B.V.保留所有权利。

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