Korea Advanced Institute of Science and Technology

Yoseob Han

JongChul Ye

Eunju Cha

A method for processing a sparse-view computed tomography (CT) image using a neural network and an apparatus therefor are provided. The method includes receiving a sparse-view CT data and reconstructing an image for the sparse-view CT data using a neural network of a learning model satisfying a predetermined frame condition.

Method for processing sparse-view computed tomography image using neural network and apparatus therefor

A method for processing a multi-directional X-ray computed tomography (CT) image using a neural network and an apparatus therefor are provided. The method includes receiving a predetermined number of multi-directional X-ray CT data and reconstructing an image for the multi-directional X-ray CT data using a neural network learned in each of an image domain and a sinogram domain.

Method for processing multi-directional X-ray computed tomography image using artificial neural network and apparatus therefor

A method and apparatus for reconstructing an image using an extended neural network is provided. The method includes receiving an input image and reconstructing an output image from the input image using a neural network meeting a predetermined frame constraint. The reconstructing includes transforming the input image into signals corresponding to different frequencies, adjusting coefficients of the transformed signals using a nonlinear function, reconstructing the adjusted coefficients, and inversely transforming all coefficients determined using the reconstructed coefficients into the output image.

Growing community of inventors

Daejeon, South Korea

Yoseob Han