公开(公告)号：US11823056B2

公开(公告)日：2023-11-21

申请号：US16842435

申请日：2020-04-07

Applicant: Lunit Inc.

Inventor： HyunJae Lee ,  Hyo-Eun Kim ,  Weonsuk Lee

IPC: G06N3/084 ,  G06N20/20 ,  G06T5/50 ,  G06V10/82 ,  G06N3/045 ,  G06V10/774 ,  G06V10/44 ,  G06V20/64

CPC classification number: G06N3/084 ,  G06N3/045 ,  G06N20/20 ,  G06T5/50 ,  G06V10/44 ,  G06V10/7747 ,  G06V10/82 ,  G06V20/647 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20212 ,  G06T2207/30068

Abstract: Provided is a method for training a neural network and a device thereof. The method may train a neural network with three-dimensional (3D) training image data including a plurality of two-dimensional (2D) training image data. The method may include training, at a processor, a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers. The method may further include training, at the processor, a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.

公开(公告)号：US11830227B2

公开(公告)日：2023-11-28

申请号：US17097036

申请日：2020-11-13

Applicant: Lunit Inc.

Inventor： HyunJae Lee

IPC: G16H30/40 ,  G06N3/08 ,  G06F18/214 ,  G06F18/22 ,  G06V20/64 ,  G06N3/00 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V20/64 ,  G06F18/2148 ,  G06F18/22 ,  G06N3/00 ,  G06V10/764 ,  G06V10/82 ,  G16H30/40 ,  G06V2201/03

Abstract: A 3D image sliced into a plurality of slices including the first slice on which a label is annotated and a plurality of second slices on which the label is not annotated is provided as a training sample. A computing device trains a neural network based on the first slice, determines an expandable second slice which is expandable from the first slice from among the plurality of second slices based on the trained neural network; and trains the neural network based on expanded slices including the expandable second slice.