公开(公告)号：US20240095894A1

公开(公告)日：2024-03-21

申请号：US18223972

申请日：2023-07-19

Applicant: Medicalip Co., Ltd.

Inventor： Sang Joon Park ,  Jong Min Kim ,  Han Jae Chung ,  Seung Min Ham

IPC: G06T5/00 ,  G06T5/50

CPC classification number: G06T5/009 ,  G06T5/50 ,  G06T2207/10081 ,  G06T2207/20081

Abstract: Disclosed is a medical image conversion method and apparatus. The medical image conversion apparatus trains a first artificial intelligence model to output a second contrast-enhanced image, based on first learning data including a pair of a first contrast-enhanced image and a first non-contrast image, and trains a second artificial intelligence model to output a second non-contrast image, based on second learning data including a pair of the first non-contrast image of the first learning data and the second contrast-enhanced image. The disclosure was supported by the “AI Precision Medical Solution (Doctor Answer 2.0) Development” project hosted by Seoul National University Bundang Hospital (Project Serial No.: 1711151151, Project No.: S0252-21-1001).

公开(公告)号：US20240354945A1

公开(公告)日：2024-10-24

申请号：US18640357

申请日：2024-04-19

Applicant: MEDICALIP CO., LTD.

Inventor： Sang Joon Park ,  Jong Min Kim ,  Joseph Nathanael Witanto

IPC: G06T7/00 ,  G06T7/12 ,  G06V10/60 ,  G16H30/40

CPC classification number: G06T7/0012 ,  G06T7/12 ,  G06V10/60 ,  G16H30/40 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061

Abstract: Provided are a medical image translation method and apparatus. The medical image translation apparatus receives a first medical image and translates the first medical image into a second medical image through an image translation model. The first medical image is a two-dimensional (2D) medical image, and the second medical image is a 2D medical image obtained by reconstructing a brightness value of each of pixels of the first medical image while maintaining a structure shown in the first medical image. The image translation model is a model implemented with an artificial neural network that reflects and outputs a feature of a brightness value of each of pixels of a reference image trained in a training process in a 2D medical image.

公开(公告)号：US20240127950A1

公开(公告)日：2024-04-18

申请号：US18224010

申请日：2023-07-19

Applicant: Medicalip Co., Ltd.

Inventor： Sang Joon Park ,  Jong Min Kim ,  Han Jae Chung

IPC: G16H50/20 ,  G06N3/0464 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H50/30

CPC classification number: G16H50/20 ,  G06N3/0464 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H50/30

Abstract: Provided is a disease prediction method and apparatus. The disease prediction apparatus may receive a medical image and clinical information, identify, from the medical image, quantitative data comprising a volume of at least one anatomical structure, and predict a disease occurrence based on the clinical information and the quantitative data. An artificial intelligence model may be used for each of identification of an anatomical structure and prediction of the disease occurrence. The disclosure was supported by the “AI Precision Medical Solution (Doctor Answer 2.0) Development” project hosted by Seoul National University Bundang Hospital (Project Serial No.: 1711151151, Project No.: S0252-21-1001).

公开(公告)号：US20240362753A1

公开(公告)日：2024-10-31

申请号：US18647766

申请日：2024-04-26

Applicant: MEDICALIP CO., LTD.

Inventor： Sang Joon Park ,  Jong Min Kim ,  Da In Lee

IPC: G06T5/50 ,  G06T5/60 ,  G06T7/00 ,  G06T7/49

CPC classification number: G06T5/50 ,  G06T5/60 ,  G06T7/0002 ,  G06T7/49 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004

Abstract: Provided are a method and apparatus for generating an image reconstruction model and an image reconstruction method and apparatus using the image reconstruction model. The image reconstruction apparatus extracts, through an encoder configured to extract a structure and a texture, a structure and a texture of each of a first medical image and a second medical image and generates, through a decoder configured to reconstruct an image based on a structure and a texture, a third medical image in which the texture of the second medical image is combined with the structure of the first medical image.

公开(公告)号：US20240046438A1

公开(公告)日：2024-02-08

申请号：US18229119

申请日：2023-08-01

Applicant: Medicalip Co., Ltd.

Inventor： Jong Min Kim ,  Han Jae Chung ,  Seung Min Ham ,  Sang Joon Park

IPC: G06T5/00 ,  G06T5/50 ,  G06T11/00

CPC classification number: G06T5/008 ,  G06T5/50 ,  G06T11/008 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/10088 ,  G06T2207/20216

Abstract: A method and a device for converting a non-contrast image into a contrast image are disclosed. The image conversion device converts the non-contrast image into the contrast image by using a deep learning network trained with learning data including one or more contrast learning images and one or more non-contrast learning images. The disclosure was supported by the “Critical Care Patient Specialized Big Data Construction and AI-based CDSS Development” project hosted by Seoul National University Hospital (Task identification number: HI21C1074, Assignment number: HI21C1074050021).