公开(公告)号：US12039717B2

公开(公告)日：2024-07-16

申请号：US17183369

申请日：2021-02-24

Applicant: FUJIFILM Corporation

Inventor： Shoji Kanada

IPC: G06K9/00 ,  A61B5/00 ,  A61B5/08 ,  G06F18/22 ,  G06F18/241 ,  G06T7/00 ,  G06V10/25

CPC classification number: G06T7/0012 ,  A61B5/08 ,  A61B5/4887 ,  G06F18/22 ,  G06F18/241 ,  G06T7/0014 ,  G06V10/25 ,  G06T2207/30061 ,  G06T2207/30096 ,  G06V2201/031

Abstract: A lung region can be appropriately divided with a region dividing device, method, and program for dividing a lung region included in a medical image. A bronchus extracting unit 30 of a region dividing unit 22 extracts a bronchus from a lung region included in a medical image acquired by imaging a subject including a lung. A first dividing unit 31 to a fourth dividing unit 34 identify a plurality of branch positions of the bronchus and divide, based on the branch positions, the lung region into a plurality of regions.

公开(公告)号：US20240225588A1

公开(公告)日：2024-07-11

申请号：US18615351

申请日：2024-03-25

Applicant: Hsiao-Ching Nien ,  YUAN High-Tech Development Co., Ltd.

Inventor： Hsiao-Ching Nien ,  Ta-Hsiang Lin ,  Pei-Lien Chou

IPC: A61B8/08 ,  A61B8/00 ,  G06T7/00 ,  G06V10/764 ,  G06V10/774 ,  G06V20/70 ,  G16H15/00 ,  G16H30/40 ,  G16H50/30

CPC classification number: A61B8/085 ,  A61B8/4427 ,  A61B8/463 ,  A61B8/54 ,  G06T7/0014 ,  G06V10/764 ,  G06V10/774 ,  G06V20/70 ,  G16H15/00 ,  G16H30/40 ,  G16H50/30 ,  G06T2207/10132 ,  G06T2207/20081 ,  G06T2207/30056 ,  G06T2207/30096 ,  G06V2201/031

Abstract: Provided is a method and apparatus of intelligent analysis for liver tumors, including an analysis module for receiving YOLOR-based training to acquire sufficient intelligence to detect and locate liver tumor automatically and attain a mAP score as high as 0.56 required to distinguish lesions of benignant and malignant liver tumors in medical images from each other, attaining a mAP score of 0.628 for tumors at least 5 cm in size or a mAP score of 0.33 for tumors less than 5 cm in size. Thus, the area under the liver tumor differentiation curve of the analysis module and the mAP score reach 0.9 and 0.56 respectively. The values equal those of the effect of the diagnosis rate of liver tumors with CT and MRI in practice. The method is advantageous in terms of higher speed and thus can diagnose liver tumors earlier, preclude delays and radiation, but incur low cost.

公开(公告)号：US20240197446A1

公开(公告)日：2024-06-20

申请号：US18403012

申请日：2024-01-03

Applicant: 3SHAPE A/S

Inventor： Henrik John BRANDT

IPC: A61C9/00 ,  G06T17/00 ,  G16H30/20 ,  G16H50/50

CPC classification number: A61C9/0053 ,  G06T17/00 ,  G16H30/20 ,  G16H50/50 ,  G06V2201/031 ,  G06V2201/12

Abstract: Disclosed is method, a user interface, a computer program product and a system for predicting future development of a dental condition of a patient's set of teeth, wherein the method comprises: —obtaining two or more digital 3D representations for the teeth recorded at different points in time; —deriving based on the obtained digital 3D representations a formula expressing the development of the dental condition in terms of at least one parameter as a function of time; and—predicting the future development of the condition based on the derived formula.

公开(公告)号：US12004891B1

公开(公告)日：2024-06-11

申请号：US17217675

申请日：2021-03-30

Applicant: Amazon Technologies, Inc.

Inventor： Sharon Alpert ,  Antonio Criminisi

IPC: A61B6/00 ,  A61B5/055 ,  A61B6/03 ,  A61B8/08 ,  G06F3/0482 ,  G06F3/14 ,  G06F18/22 ,  G06T7/00 ,  G06T7/70 ,  G16H15/00 ,  G16H30/20 ,  G16H30/40 ,  G16H50/70 ,  G10L15/18 ,  G10L15/22 ,  G16H40/20 ,  G16H50/20 ,  G16H70/20 ,  G16H70/60

CPC classification number: A61B6/5211 ,  A61B5/055 ,  A61B6/032 ,  A61B8/5215 ,  G06F3/0482 ,  G06F3/1423 ,  G06F18/22 ,  G06T7/0012 ,  G06T7/70 ,  G16H15/00 ,  G16H30/20 ,  G16H30/40 ,  G16H50/70 ,  G06T2200/24 ,  G06T2207/30004 ,  G06V2201/031 ,  G10L15/18 ,  G10L15/22 ,  G10L2015/223 ,  G16H40/20 ,  G16H50/20 ,  G16H70/20 ,  G16H70/60

Abstract: Systems for preparing a medical report, and related methods, generate and output feedback indicative or potential errors in the medical report. A system for preparing a medical report is configured to receive image data for a medical image of a patient, display the medical image, monitor content of the medical report during preparation of the medical report, process the image data to detect one or more organs of the patient imaged in the medical image, compare the content of the medical report with the one or more organs imaged in the medical image to detect one or more potential errors in the medical report, and output feedback indicative of the one or more potential errors in the medical report.

公开(公告)号：US20240169748A1

公开(公告)日：2024-05-23

申请号：US18391820

申请日：2023-12-21

Applicant: CARNEGIE MELLON UNIVERSITY

Inventor： JONATHAN CAGAN ,  PHILIP LeDUC ,  DANIEL CLYMER

IPC: G06V20/69 ,  G06F18/10 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/241 ,  G06F18/2415 ,  G06T7/00

CPC classification number: G06V20/69 ,  G06F18/10 ,  G06F18/2135 ,  G06F18/2148 ,  G06F18/241 ,  G06F18/2415 ,  G06T7/0012 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10056 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30101 ,  G06V40/14 ,  G06V2201/031

Abstract: A hierarchical deep-learning object detection framework provides a method for identifying objects of interest in high-resolution, high pixel count images, wherein the objects of interest comprise a relatively a small pixel count when compared to the overall image. The method uses first deep-learning model to analyze the high pixel count images, in whole or as a patchwork, at a lower resolution to identify objects, and a second deep-learning model to analyze the objects at a higher resolution to classify the objects.

公开(公告)号：US20240161305A1

公开(公告)日：2024-05-16

申请号：US18449417

申请日：2023-08-14

Applicant: THE BOARD OF REGENTS OF THE UNIVERSITY OF TEXAS SYSTEM

Inventor： Darin T OKUDA ,  Braeden D NEWTON

IPC: G06T7/11 ,  G06F18/22 ,  G06T15/08 ,  G06T17/00 ,  G06V10/26 ,  G06V10/75

CPC classification number: G06T7/11 ,  G06F18/22 ,  G06T15/08 ,  G06T17/00 ,  G06V10/26 ,  G06V10/75 ,  G06T2207/10088 ,  G06T2207/30016 ,  G06T2207/30096 ,  G06T2210/41 ,  G06V2201/031 ,  G16H30/40

Abstract: Methods, apparatuses, systems, and implementations for creating 3-dimensional (3D) representations exhibiting geometric and surface characteristics of brain lesions are disclosed. 2D and/or 3D MRI images of the brain may be acquired. Brain lesions and other abnormalities may be identified and isolated with each lesion serving as a region of interest (ROI). Saved ROI may be converted into stereolithography format, maximum intensity projection (MIP) images, and/or orthographic projection images. Data corresponding to these resulting 3D brain lesion images may be used to create 3D printed models of the isolated brain lesions using 3D printing technology. Analysis of the 3D brain lesion images and the 3D printed brain lesion models may enable a more efficient and accurate way of determining brain lesion etiologies.

公开(公告)号：US11941817B2

公开(公告)日：2024-03-26

申请号：US18127991

申请日：2023-03-29

Applicant: EXINI Diagnostics AB

Inventor： Jens Filip Andreas Richter ,  Kerstin Elsa Maria Johnsson ,  Erik Konrad Gjertsson ,  Aseem Undvall Anand

IPC: G06T7/00 ,  A61B6/00 ,  A61B6/03 ,  A61K51/04 ,  G06F18/214 ,  G06T7/11 ,  G06V20/64 ,  G06V20/69 ,  G06V30/24 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50

CPC classification number: G06T7/11 ,  A61B6/032 ,  A61B6/037 ,  A61B6/463 ,  A61B6/466 ,  A61B6/481 ,  A61B6/505 ,  A61B6/507 ,  A61B6/5205 ,  A61B6/5241 ,  A61B6/5247 ,  A61K51/0455 ,  G06F18/214 ,  G06V20/64 ,  G06V20/695 ,  G06V20/698 ,  G06V30/2504 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50 ,  G06V2201/031 ,  G06V2201/033

Abstract: Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and/or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and/or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and/or determine efficacy of a treatment modality.

公开(公告)号：US20240096065A1

公开(公告)日：2024-03-21

申请号：US17932311

申请日：2022-09-15

Applicant: Siemens Healthcare GmbH

Inventor： Bernhard Geiger

IPC: G06V10/774 ,  A61D99/00 ,  A61N5/10 ,  G06T7/11 ,  G06T7/33 ,  G06T7/35 ,  G06V10/24 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/774 ,  A61D99/00 ,  A61N5/1039 ,  G06T7/11 ,  G06T7/33 ,  G06T7/35 ,  G06V10/243 ,  G06V10/764 ,  G06V10/82 ,  G06V2201/031

Abstract: Systems and methods that normalize medical imaging data between different species and breeds of animals in order to allow for cross-species and crossbreed usage of machine trained models. Image data of a non-human subject is acquired, registered using a standardized model, and segmented using a machine trained model.

公开(公告)号：US20240090795A1

公开(公告)日：2024-03-21

申请号：US18275170

申请日：2022-02-02

Applicant: The Regents of the University of California

Inventor： Franklin Heng ,  Xavier Minh Mathieu Orain

IPC: A61B5/091 ,  A61B5/00 ,  A61B5/087 ,  G06T7/00 ,  G06T7/246 ,  G06V10/25 ,  G16H30/40 ,  G16H50/30

CPC classification number: A61B5/091 ,  A61B5/087 ,  A61B5/7275 ,  A61B5/742 ,  A61B5/7485 ,  G06T7/0016 ,  G06T7/248 ,  G06V10/25 ,  G16H30/40 ,  G16H50/30 ,  G06T2207/10028 ,  G06T2207/30061 ,  G06V2201/031

Abstract: Methods and systems for pulmonary function testing of a subject are provided. Aspects of the present invention include methods and systems configured to generate flow volume curves and compute lung function parameters of a subject and determine potential clinical interpretations of pulmonary function. In addition, the present invention offers advantages including (i) measuring lung function without initial calibration of spirometer information, (ii) the ability to use spirometer information to develop a machine learning based algorithm which will eventually measure lung function without needing spirometer information at all, (iii) computing metrics such as chest and waist width and sitting height of subject.

公开(公告)号：US20240029359A1

公开(公告)日：2024-01-25

申请号：US18477535

申请日：2023-09-28

Applicant: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.

Inventor： Weipin NIE ,  Yue GAO ,  Hao ZENG ,  Chao FU ,  Ce WANG

IPC: G06T19/00 ,  G06T7/11 ,  G06T7/187 ,  G06T19/20 ,  G06T7/12 ,  G06V10/25

CPC classification number: G06T19/00 ,  G06T7/11 ,  G06T7/187 ,  G06T19/20 ,  G06T7/12 ,  G06V10/25 ,  G06T2207/30101 ,  G06T2219/2021 ,  G06T2207/20104 ,  G06T2219/028 ,  G06T2210/41 ,  G06T2207/30056 ,  G06T2207/30096 ,  G06V2201/031

Abstract: The present disclosure relates to a system and method for extracting a region of interest. Image data in a first sectional plane may be acquired. The image data in the first sectional plane may include at least one first slice image and one second slice image. A first region of interest (ROI) in the first slice image may be determined. A second ROI in the second slice image may be determined. A first volume of interest (VOI) may be determined based on the first ROI, the second ROI, and characteristic information of the image data in the first sectional plane.