公开(公告)号：US10089747B2

公开(公告)日：2018-10-02

申请号：US15381510

申请日：2016-12-16

Applicant: General Electric Company

Inventor： Dejun Wang ,  Yanling Qu

IPC: G06T7/35 ,  G06T7/70 ,  G06K9/62 ,  G06K9/66

Abstract: This disclosure presents an image processing method and related X-ray imaging device The method comprises: calculating a relative displacement between two first images that are already in auto registration as a first displacement vector; calculating a difference between position information fed back by a position sensor on the X-ray imaging device when imaging exposure is performed on the two first images respectively as a second displacement vector; calculating a first error of the first displacement vector relative to the second displacement vector; calculating a registration level corresponding to the first error in accordance with a pre-stored training model which is a mathematical distribution model of second errors between a plurality of third displacement vectors and a plurality of corresponding fourth displacement vectors; and labeling the registration level on the two first images that are already in auto registration.

公开(公告)号：US20180061067A1

公开(公告)日：2018-03-01

申请号：US15381510

申请日：2016-12-16

Applicant: General Electric Company

Inventor： Dejun Wang ,  Yanling Qu

IPC: G06T7/35 ,  G06T7/70 ,  G06K9/62 ,  G06K9/66

CPC classification number: G06T7/35 ,  G06K9/6269 ,  G06K9/66 ,  G06T7/344 ,  G06T7/70 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/30008

Abstract: This disclosure presents an image processing method and related X-ray imaging device The method comprises: calculating a relative displacement between two first images that are already in auto registration as a first displacement vector; calculating a difference between position information fed back by a position sensor on the X-ray imaging device when imaging exposure is performed on the two first images respectively as a second displacement vector; calculating a first error of the first displacement vector relative to the second displacement vector; calculating a registration level corresponding to the first error in accordance with a pre-stored training model which is a mathematical distribution model of second errors between a plurality of third displacement vectors and a plurality of corresponding fourth displacement vectors; and labeling the registration level on the two first images that are already in auto registration.