Abstract: 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.

Abstract: A method and apparatus for measuring a 3-D refractive index tensor are presented. The method for measuring a 3-D refractive index tensor according to an embodiment comprises the steps of: controlling incident light of a plane wave with respect to at least one angle and polarization; and measuring, in a polarization-dependent manner, the 2-D diffracted light of a specimen with respect to the incident light incident at the at least one angle and polarization, wherein the birefringence value and the 3-D structure of an alignment direction of molecules in the specimen having birefringence may be measured.

Abstract: A non-label diagnosis apparatus for a hematologic malignancy may include a 3-D refractive index cell imaging unit configured to generate a 3-D refractive index slide image of a blood smear specimen by capturing a 3-D refractive index image in the form of the blood smear specimen in which blood (including a bone-marrow or other body fluids) of a patient has been smeared on a slide glass, an ROI detection unit configured to sample a suspected cell segment in the blood smear specimen based on the 3-D refractive index slide image and to determine, as ROI patches, cells determined as abnormal cells, and a diagnosis unit configured to determine a sub-classification of a cancer cell corresponding to each of the ROI patches using a cancer cell sub-classification determination model constructed based on a deep learning algorithm and to generate hematologic malignancy diagnosis results by gathering sub-classification results of the ROI patches.

Abstract: A non-label diagnosis apparatus for a hematologic malignancy may include a 3-D refractive index cell imaging unit configured to generate a 3-D refractive index slide image of a blood smear specimen by capturing a 3-D refractive index image in the form of the blood smear specimen in which blood (including a bone-marrow or other body fluids) of a patent has been smeared on a slide glass, an ROI detection unit configured to sample a suspected cell segment in the blood smear specimen based on the 3-D refractive index slide image and to determine, as ROI patches, cells determined as abnormal cells, and a diagnosis unit configured to determine a sub-classification of a cancer cell corresponding to each of the ROI patches using a cancer cell sub-classification determination model constructed based on a deep learning algorithm and to generate hematologic malignancy diagnosis results by gathering sub-classification results of the ROI patches.

Abstract: A method and apparatus for measuring 3D refractive-index tomograms using a wavefront shaper in ultra-high speed and high precision is provided. The method includes the steps of modifying at least one of an illumination angle and a wavefront pattern of an incident ray through the wavefront shaper and leading the modified incident ray to a sample, measuring a 2D optical field, which passes through the sample, through an interferometry along at least one or more of the incident rays, and obtaining 3D refractive-index tomograms through measured information of the 2D optical field.

Abstract: An ultra-high-speed 3D refractive index tomography and structured illumination microscopy system using a wavefront shaper and a method using the same are provided. A method of using an ultra-high-speed 3D refractive index tomography and structured illumination microscopy system that utilizes a wavefront shaper includes adjusting an irradiation angle of a plane wave incident on a sample by using the wavefront shaper, measuring a 2D optical field, which passes through the sample, based on the irradiation angle of the plane wave, and obtaining a 3D refractive index image from information of the measured 2D optical field by using an optical diffraction tomography or a filtered back projection algorithm.