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AUTOMATED SEGMENTATION OF THREE DIMENSIONAL BONY STRUCTURE IMAGES

机译:三维三维结构图像的自动分段

摘要

A computer-implemented system that includes at least one nontransitory processor-readable storage medium that stores at least one of processor-executable instructions or data and at least one processor communicably coupled to at least one nontransitory processor-readable storage medium. That at least one processor: receives segmentation learning data comprising a plurality of batches of labeled anatomical image sets, each image set comprising image data representative of a bony structure, and each image set including at least one label which identifies the region of a particular part of the bony structure depicted in each image of the image set; trains a fully convolutional neural network model (segmentation CNN) to segment at least one part of the bony structure utilizing the received segmentation learning data; and stores the trained segmentation CNN model in at least one nontransitory processor-readable storage medium of the machine learning system.
机译:一种计算机实现的系统,包括至少一个存储处理器可执行指令或数据中的至少一个的非暂时性处理器可读存储介质,以及至少一个可通信地耦合到至少一个非暂时性处理器可读存储介质的处理器。至少一个处理器:接收包括多个批次的标记解剖图像集的分割学习数据,每个图像集包括表示骨结构的图像数据,并且每个图像集包括至少一个标识特定部位区域的标签在该图像集中的每个图像中描绘的骨结构;利用接收到的分割学习数据训练全卷积神经网络模型(分割CNN)分割骨结构的至少一部分;并将训练后的分割CNN模型存储在机器学习系统的至少一种非暂时性处理器可读存储介质中。

著录项

  • 公开/公告号EP3470006A1

    专利类型

  • 公开/公告日2019-04-17

    原文格式PDF

  • 申请/专利权人 HOLO SURGICAL INC.;

    申请/专利号EP20170195826

  • 申请日2017-10-10

  • 分类号A61B34/20;G02B27/01;A61B90;A61B90/50;A61B34/10;G06K9;G06T7/10;G06T7/11;

  • 国家 EP

  • 入库时间 2022-08-21 12:28:03

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