公开(公告)号：US20160317118A1

公开(公告)日：2016-11-03

申请号：US15105037

申请日：2014-11-28

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： Vijay Parthasarathy ,  Gary Cheng-How Ng ,  Charles Ray Hatt

IPC: A61B8/08 ,  G06K9/66 ,  G06K9/62 ,  A61B8/00 ,  G06T7/00

Abstract: A classification-based medical image segmentation apparatus includes an ultrasound image acquisition device configured for acquiring, from ultrasound, an image depicting a medical instrument such as needle; and machine-learning-based-classification circuitry configured for using machine-learning-based-classification to, dynamically responsive to the acquiring, segment the instrument by operating on information (212) derived from the image. The segmenting can be accomplished via statistical boosting (220) of parameters of wavelet features. Each pixel (216) of the image is identified as “needle” or “background.” The whole process of acquiring an image, segmenting the needle, and displaying an image with a visually enhanced and artifact-free needle-only overlay may be performed automatically and without the need for user intervention.

Abstract translation: 基于分类的医用图像分割装置包括：超声图像获取装置，被配置为从超声波获取描绘诸如针的医疗器械的图像; 以及基于机器学习的分类电路，其被配置为使用基于机器学习的分类，以动态响应于通过操作从所述图像导出的信息（212）来获取所述乐器。 分段可以通过小波特征参数的统计提升（220）来实现。 图像的每个像素（216）被标识为“针”或“背景”。可以执行获取图像，分割针和显示具有视觉增强和无伪影的针对覆盖的图像的整个过程 自动，无需用户干预。