公开(公告)号：US12141897B2

公开(公告)日：2024-11-12

申请号：US17753452

申请日：2021-01-06

Applicant: TOMOCUBE, INC.

Inventor： YongKeun Park ,  Donghun Ryu ,  HyunSeok Min ,  Dongmin Ryu

IPC: G06T11/00 ,  G06V10/82

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.

公开(公告)号：US11410304B2

公开(公告)日：2022-08-09

申请号：US16900364

申请日：2020-06-12

Applicant: TOMOCUBE, INC.

Inventor： YongKeun Park ,  Donghun Ryu ,  Young Seo Kim ,  Kihyun Hong ,  Hyun-Seok Min

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/73 ,  G01B9/021 ,  G01N21/45

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.