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05/04/2026 [07:52:00]
Results 75 to 77 of 77
Absstract of: CN121616633A
本发明公开了基于几何模糊的自适应细化医学图像配准方法，属于医学图像处理与医学人工智能技术领域，包括以下步骤：1、输入固定图像和移动图像，并提取医学图像的多尺度几何特征；2、将多尺度几何特征进行特征变换与融合，得到联合特征；3、通过模糊加权模块对联合特征进行加权调整；4、将联合特征输入形变估计模块，并通过逐尺度自适应细化模块细化联合特征的尺度，之后将此时的形变场返回2进行迭代操作，直到完成最细尺度的形变估计，得到高分辨率形变场；5、使用高分辨率形变场对原始输入的移动图像进行处理，得到形变图像，并与原始固定图像进行精确配准；本发明采用上述方法，多模块依次连接，从而实现由粗到细的精确医学图像配准。
Nº publicación: CN121616074A 06/03/2026
Applicant:
中国船舶集团有限公司综合技术经济研究院北京航空航天大学
Absstract of: CN121616074A
本申请实施例提供一种基于任务网络特征的协同任务复杂度分析方法及系统，方法包括：通过将指控任务按照四个维度层次化分解为原子任务后，构建任务网络模型，遍历任务网络模型，提取网络规模特征、结构关系特征以及不确定性特征，分别对所述网络规模特征、所述结构关系特征以及所述不确定性特征进行复杂度计算，确定对应的复杂度量化结果，根据所述复杂度量化结果对所述任务网络模型进行优化调整，以使所述任务网络模型的任务网络复杂度降低，本申请能够提高指控任务复杂度度量的准确性和效率。
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