公开(公告)号：US20250157100A1

公开(公告)日：2025-05-15

申请号：US18509385

申请日：2023-11-15

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin TANG ,  Jian ZHOU ,  Liang CAI ,  Chih-Chieh LIU

IPC: G06T11/00 ,  G06T5/00 ,  G06T5/20 ,  G06T7/00 ,  G06T7/246

Abstract: A medical image processing method includes obtaining a set of projection data acquired in a computed tomography (CT) scan of a three-dimensional region of an object to be examined; generating for each time point of a plurality of time points of the CT scan based on a part of the obtained set of projection data corresponding to the time point, a pair of feature maps for estimating motion at the time point so as to generate a plurality of pairs of feature maps, each feature map representing a feature of an image reconstructed from the part of the obtained set of projection data; estimating, based on the generated plurality of pairs of feature maps, a four-dimensional motion field; and reconstructing, based on the estimated four-dimensional motion field and the obtained set of projection data, a CT image of the object.

公开(公告)号：US20240062371A1

公开(公告)日：2024-02-22

申请号：US18448773

申请日：2023-08-11

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Chih-Chieh LIU ,  Jian ZHOU ,  Qiulin TANG ,  Liang CAI ,  Zhou YU

IPC: G06T7/00 ,  G06T7/11

CPC classification number: G06T7/0012 ,  G06T7/11 ,  G06T2207/20084 ,  G06T2207/30048 ,  G06T2207/30101 ,  G06T2200/04

Abstract: An apparatus is provided with processing circuitry that receives a phase image acquired at a corresponding cardiac phase, determines, from the received phase image, a mask image of a particular cardiac region, applies both the determined mask image and the phase image to inputs of a trained neural network model to obtain, from outputs of the neural network model, a location probability map. The neural network model is trained with a set of input data and a corresponding set of output data. The input data includes a training mask image and a training phase image, and the output data includes a training location probability map. The processing circuitry calculates, for the cardiac phase, from the determined location probability map output from the trained neural network model, a value of a cardiac motion metric. The determined location probability map specifies a probable location of a cardiac vessel.