Invention Grant
- Patent Title: Deep-learning-based scatter estimation and correction for X-ray projection data and computer tomography (CT)
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Application No.: US16252392Application Date: 2019-01-18
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Publication No.: US10937206B2Publication Date: 2021-03-02
- Inventor: Yujie Lu , Zhou Yu , Jian Zhou , Tzu-Cheng Lee , Richard Thompson
- Applicant: Canon Medical Systems Corporation
- Applicant Address: JP Tochigi
- Assignee: Canon Medical Systems Corporation
- Current Assignee: Canon Medical Systems Corporation
- Current Assignee Address: JP Tochigi
- Agency: Oblon, McClelland, Maier & Neustadt, L.L.P.
- Main IPC: G06T11/00
- IPC: G06T11/00 ; G06T7/11

Abstract:
A method and apparatus are provided for using a neural network to estimate scatter in X-ray projection images and then correct for the X-ray scatter. For example, the neural network is a three-dimensional convolutional neural network 3D-CNN to which are applied projection images, at a given view, for respective energy bins and/or material components. The projection images can be obtained by material decomposing spectral projection data, or by segmenting a reconstructed CT image into material-component images, which are then forward projected to generate energy-resolved material-component projections. The result generated by the 3D-CNN is an estimated scatter flux. To train the 3D-CNN, the target scatter flux in the training data can be simulated using a radiative transfer equation method.
Public/Granted literature
Information query
IPC分类:
G | 物理 |
G06 | 计算;推算或计数 |
G06T | 一般的图像数据处理或产生 |
G06T11/00 | 2D〔二维〕图像的生成 |