公开(公告)号：US20230128769A1

公开(公告)日：2023-04-27

申请号：US18086962

申请日：2022-12-22

Applicant: Lunit Inc.

Inventor： Jongchan PARK

IPC: G06T7/00 ,  G16H50/20 ,  G16H30/40

Abstract: A method of reading a medical image by a computing device operated by at least one processor is provided. The method includes obtaining an abnormality score of the input image using an abnormality prediction model, filtering the input image so as not to be subsequently analyzed when the abnormality score is less than or equal to a cut-off score based on the cut-off score which makes a specific reading sensitivity; and obtaining an analysis result of the input image using a classification model that distinguishes the input image into classification classes when the abnormality score is greater than the cut-off score.

公开(公告)号：US20220199258A1

公开(公告)日：2022-06-23

申请号：US17689196

申请日：2022-03-08

Applicant: Lunit Inc.

Inventor： Donggeun YOO ,  Seungwook PAEK ,  Minchul KIM ,  Jongchan PARK

IPC: G16H50/20 ,  G16H50/70 ,  G16H15/00

Abstract: A training method for specializing an artificial intelligence model in an institution for deployment and an apparatus for performing training the artificial intelligence model are provided. A method for operating a training apparatus operated by at least one processor includes extracting a dataset to be used for specialized training from data retained by a certain institution, selecting an annotation target for which annotation is required from the dataset by using a pre-trained artificial intelligence (AI) model, and performing supervised training of the pre-trained AI model by using data annotated with a label for the annotation target.

公开(公告)号：US20220269905A1

公开(公告)日：2022-08-25

申请号：US17685740

申请日：2022-03-03

Applicant: Lunit Inc.

Inventor： Jongchan PARK ,  Donggeun YOO

IPC: G06K9/62 ,  G06T7/70 ,  G16H30/20 ,  G06T7/00 ,  G16H30/40 ,  G06N20/00 ,  G06V30/166

Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.

公开(公告)号：US20200372299A1

公开(公告)日：2020-11-26

申请号：US16708205

申请日：2019-12-09

Applicant: Lunit Inc.

Inventor： Jongchan PARK ,  Donggeun YOO

IPC: G06K9/62 ,  G06T7/00 ,  G06T7/70

Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.

公开(公告)号：US20210391059A1

公开(公告)日：2021-12-16

申请号：US17077142

申请日：2020-10-22

Applicant: Lunit Inc.

Inventor： Jongchan PARK

IPC: G16H30/40 ,  G16H50/20 ,  G06T7/00

Abstract: A method of reading a medical image by a computing device operated by at least one processor is provided. The method includes obtaining an abnormality score of the input image using an abnormality prediction model, filtering the input image so as not to be subsequently analyzed when the abnormality score is less than or equal to a cut-off score based on the cut-off score which makes a specific reading sensitivity; and obtaining an analysis result of the input image using a classification model that distinguishes the input image into classification classes when the abnormality score is greater than the cut-off score.

公开(公告)号：US20210012160A1

公开(公告)日：2021-01-14

申请号：US17035401

申请日：2020-09-28

Applicant: Lunit Inc.

Inventor： Jongchan PARK ,  Donggeun YOO

IPC: G06K9/62 ,  G16H30/20 ,  G06T7/70 ,  G06T7/00

Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.