Airs Medical Inc.

Jeewook Kim

Sunwoo Kim

Jingu Lee

Jaeyeon Yoon

Keunwoo Jeong

According to an embodiment of the present invention, there is provided a magnetic resonance image processing method that is performed by a magnetic resonance image processing apparatus, the magnetic resonance image processing method including: acquiring first k-space data calculated based on a sub-sampled magnetic resonance signal; acquiring second k-space data from the first k-space data by using a first artificial neural network model; and acquiring a first magnetic resonance image from the second k-space data by using an inverse Fourier operation.

Magnetic resonance image processing apparatus and method using artificial neural network in k-space domain

According to an embodiment of the present invention, there is provided a magnetic resonance image processing method, the magnetic resonance image processing method being performed by a magnetic resonance image processing apparatus, the magnetic resonance image processing method including: inputting an input image having a slice resolution higher than 0 and lower than 1 to an artificial neural network model; and outputting an output image having a slice resolution of 1 from the artificial neural network model.

Magnetic resonance image processing apparatus and method to which improvement in slice resolution is applied

According to an embodiment of the present invention, there is provided a magnetic resonance image processing method including: acquiring a low-quality training image, a first parameter group including at least one scan parameter applied when the training image is acquired, a high-quality label image, and a second parameter group including at least one scan parameter applied when the label image is acquired; and training an artificial neural network model by using the training image, the first parameter group, the label image, and the second parameter group.

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Seoul, South Korea

Jeewook Kim