发明名称 SYSTEM AND METHOD FOR DETECTION OF LESIONS
摘要 A method for detecting a lesion in an anatomical region of interest is presented. The method includes identifying one or more candidate mass regions in each of a plurality of 3D ultrasound images acquired at different view angles from the anatomical region of interest. Single-view features corresponding to each candidate mass region are identified. For a candidate mass region, a similarity metric between the single-view features corresponding to the candidate mass region and the single-view features corresponding to the other candidate mass regions is determined. The candidate mass region is classified based at least on the similarity metric. A system for imaging and a non-transitory computer readable media for detection of the lesion are also presented.
申请公布号 US2015282782(A1) 申请公布日期 2015.10.08
申请号 US201414247265 申请日期 2014.04.08
申请人 General Electric Company 发明人 Zhao Fei;Vaidya Vivek Prabhakar;Mullick Rakesh;Biswas Soma;Ye Chuyang
分类号 A61B8/08 主分类号 A61B8/08
代理机构 代理人
主权项 1. A method for detecting a lesion in an anatomical region of interest, the method comprising: receiving a plurality of three-dimensional ultrasound images corresponding to the anatomical region of interest, wherein each of the plurality of three-dimensional ultrasound images represents the anatomical region of interest from a different view angle; identifying one or more candidate mass regions in each of the plurality of three-dimensional ultrasound images; determining one or more single-view features corresponding to each of the one or more candidate mass regions in each of the plurality of three-dimensional ultrasound images; determining, for a candidate mass region of the one or more candidate mass regions in a three-dimensional ultrasound image of the plurality of three-dimensional ultrasound images, a similarity metric between the one or more single-view features corresponding to the candidate mass region and the one or more single-view features corresponding to the one or more candidate mass regions in the other three-dimensional ultrasound images of the plurality of three-dimensional ultrasound images; and classifying the candidate mass region based at least on the similarity metric.
地址 Schenectady NY US