18777615. METHOD FOR COMPUTED TOMOGRAPHY IMAGING AND RECONSTRUCTION BASED ON LEARNING (ZHEJIANG UNIVERSITY)
METHOD FOR COMPUTED TOMOGRAPHY IMAGING AND RECONSTRUCTION BASED ON LEARNING
Organization Name
Inventor(s)
Kaizhang Kang of Hangzhou (CN)
METHOD FOR COMPUTED TOMOGRAPHY IMAGING AND RECONSTRUCTION BASED ON LEARNING
This abstract first appeared for US patent application 18777615 titled 'METHOD FOR COMPUTED TOMOGRAPHY IMAGING AND RECONSTRUCTION BASED ON LEARNING
Original Abstract Submitted
A method for computed tomography imaging and reconstruction based on learning, which measures the scene density distribution in an illumination multiplexing manner. The light source(s) for imaging emit(s) light according to the intensity obtained by pre-learning, and the light from different directions is absorbed and attenuated by the scene and reaches a sensor. The measured values are calculated and reconstructed to obtain the density information of the scene. The illumination intensity and reconstruction algorithm are learned by a neural network. In this method, the CT imaging process is modeled as a linear fully connected layer, and the weight corresponds to the illumination intensity of the light source for imaging; the reconstruction algorithm is modeled as a nonlinear neural network, which can be optimized according to the characteristics of scanning geometry.