公开(公告)号：US11875257B2

公开(公告)日：2024-01-16

申请号：US17320424

申请日：2021-05-14

Applicant: Lunit Inc.

Inventor： Jae Hwan Lee

IPC: G06N3/08 ,  G06F18/10 ,  G06F18/213 ,  G06V10/77 ,  G06V10/82

CPC classification number: G06N3/08 ,  G06F18/10 ,  G06F18/213 ,  G06V10/7715 ,  G06V10/82

Abstract: A normalization method for machine learning and an apparatus thereof are provided. The normalization method according to some embodiments of the present disclosure may calculate a value of a normalization parameter for an input image through a normalization model before inputting the input image to a target model and normalize the input image using the calculated value of the normalization parameter. Because the normalization model is updated based on a prediction loss of the target model, the input image can be normalized to an image suitable for a target task, so that stability of the learning and performance of the target model can be improved.

公开(公告)号：US20230335259A1

公开(公告)日：2023-10-19

申请号：US17720549

申请日：2022-04-14

Applicant: Lunit Inc.

Inventor： Kyoung Won LEE ,  Kyung Hyun PAENG

IPC: G16H30/40 ,  G16H30/20 ,  G06V10/774 ,  G06T7/00

CPC classification number: G16H30/40 ,  G16H30/20 ,  G06V10/7753 ,  G06T7/0012 ,  G06T2207/30024 ,  G06V2201/03

Abstract: A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.

公开(公告)号：US20230253098A1

公开(公告)日：2023-08-10

申请号：US18105312

申请日：2023-02-03

Applicant: Lunit Inc.

Inventor： Donggeun YOO

IPC: G16H30/40 ,  G16H50/70

CPC classification number: G16H30/40 ,  G16H50/70

Abstract: An operating method of a medical data selecting apparatus operated by at least one processor includes generating training data including partial medical data sampled from mass medical data and annotated data of the partial medical data, extracting candidate data for annotation from the mass medical data, the candidate data being at least a portion of the mass medical data, acquiring inference results that are inferred from the candidate data by an artificial intelligence (AI) model trained based on the training data and selecting target data for annotation to be used in next training of the AI model, from among the candidate data based on the inference results.

公开(公告)号：US20230252626A1

公开(公告)日：2023-08-10

申请号：US18128492

申请日：2023-03-30

Applicant: Lunit Inc.

Inventor： Hyo-Eun KIM ,  Hyeonseob Nam

IPC: G06T7/00 ,  G06N3/08 ,  G06V10/40 ,  G06V10/764

CPC classification number: G06T7/0012 ,  G06N3/08 ,  G06V10/40 ,  G06V10/764 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30068 ,  G06T2207/30096

Abstract: A method for interpreting an input image by a computing device operated by at least one processor is provided. The method for interpreting an input image comprises storing an artificial intelligent (AI) model that is trained to classify a lesion detected in the input image as suspicious or non-suspicious and, under a condition of being suspicious, to classify the lesion detected in the input image as malignant or benign-hard representing that the lesion is suspicious but determined to be benign, receiving an analysis target image, by using the AI model, obtaining a classification class of a target lesion detected in the analysis target image and, when the classification class is the suspicious, obtaining at least one of a probability of being suspicious, a probability of being benign-hard, and a probability of malignant for the target lesion, and outputting an interpretation result including at least one probability obtained for the target lesion.

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：US11630985B2

公开(公告)日：2023-04-18

申请号：US16694843

申请日：2019-11-25

Applicant: Lunit Inc.

Inventor： Minje Jang

IPC: G06T7/00 ,  G06N3/04 ,  G06N3/08 ,  G06V10/774 ,  G06V10/82 ,  G06N3/045 ,  G06V30/19

Abstract: An image analysis method and an image analysis system are disclosed. The method may include extracting training graphic data including at least one first node corresponding to a plurality of histological features of a training tissue slide image, and at least one first edge defined by a relationship between the histological features The method may also include determining a parameter of a readout function by training a graph neural network (GNN) using the training graphic data and training output data corresponding to the training graphic data. The method may also include extracting inference graphic data including at least one second node corresponding to a plurality of histological features of an inference tissue slide image, and at least one second edge decided by a relationship between the histological features, The method may further include deriving inference output data by the readout function after inputting the inference graphic data to the GNN.

公开(公告)号：US20220415013A1

公开(公告)日：2022-12-29

申请号：US17895315

申请日：2022-08-25

Applicant: LUNIT INC.

Inventor： Dong Geun YOO ,  Min Chul KIM ,  Hyo Eun KIM ,  Hyun Jae LEE ,  Jae Hwan LEE ,  Hae Joon KIM

IPC: G06V10/46 ,  G06V10/25 ,  G06V10/44 ,  G06V10/74 ,  G06T7/70 ,  G06T11/20

Abstract: A method for operating a medical imaging device includes obtaining lesion information on at least one lesion detected from a medical image, determining a shape and a position of at least one contour corresponding to the at least one lesion based on the obtained lesion information, determining a position of at least one text region that includes a text indicating the lesion information on the at least one lesion in the medical image, and displaying the at least one contour and the text included in the at least one text region on the medical image, based on the determined shape and position of the at least one contour and the determined position of the at least one text region.

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：US20220037024A1

公开(公告)日：2022-02-03

申请号：US17502304

申请日：2021-10-15

Applicant: LUNIT INC.

Inventor： Donggeun YOO ,  Jeong Hoon LEE ,  Kyunghyun PAENG

IPC: G16H50/20 ,  G16H50/70 ,  G16H10/60 ,  G06T7/00

Abstract: A method for generating a medical prediction related to a biomarker from medical data is provided, which includes obtaining medical data associated with a patient, determining a region of interest in the medical data, extracting one or more features associated with the medical data based on the region of interest, and generating a medical prediction for the patient based on the extracted one or more features.

公开(公告)号：US11042789B2

公开(公告)日：2021-06-22

申请号：US16535314

申请日：2019-08-08

Applicant: Lunit Inc.

Inventor： Jae Hwan Lee

IPC: G06K9/62 ,  G06K9/66 ,  G06N3/08

Abstract: A normalization method for machine learning and an apparatus thereof are provided. The normalization method according to some embodiments of the present disclosure may calculate a value of a normalization parameter for an input image through a normalization model before inputting the input image to a target model and normalize the input image using the calculated value of the normalization parameter. Because the normalization model is updated based on a prediction loss of the target model, the input image can be normalized to an image suitable for a target task, so that stability of the learning and performance of the target model can be improved.