Tomocube, Inc.

Dongmin Ryu

Hyunseok Min

YongKeun Park

Donghun Ryu

Woonsoo Lee

Hansol Yoon

The present disclosure provides a system and method for improving image resolution of a three-dimensional (3-D) refractive index microscope based on an artificial intelligence (AI) technology. The present disclosure provides a technology for converting a low-resolution 3-D refractive index microscope image into a high-resolution 3-D refractive index image without physical machine conversion and re-photographing based on AI. That is, the present disclosure applies an AI technology, such as deep learning, in order to train an AI model with a physical correlation between a low-resolution 3-D refractive index microscope image and a high-resolution 3-D refractive index image of various samples, such as a cell and a tissue, and convert a low resolution image into a high resolution image without a change in a physical microscope based on the training. Furthermore, for the training of the AI model, the present disclosure uses physical characteristics of a refractive index image.

System and method for improving image resolution of 3-D refractive index microscope based on AI technology

Proposed are a method and device for regularizing rapid three-dimensional tomographic imaging using a machine-learning algorithm. A method for regularizing three-dimensional tomographic imaging using a machine-learning algorithm according to an embodiment comprises the steps of: measuring a three-dimensional tomogram of a cell to acquire a raw tomogram of the cell; acquiring a regularized tomogram by using a regularization algorithm; and learning the relationship between the raw tomogram and the regularized tomogram through machine-learning.

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Daejeon, South Korea

Dongmin Ryu