公开(公告)号：US12033324B2

公开(公告)日：2024-07-09

申请号：US17619085

申请日：2020-06-08

Applicant: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK

Inventor： Fazel A. Khan ,  Imin Kao ,  Carlos Gabriel Helguero

IPC: G06T7/00 ,  A61B6/00 ,  A61B6/50 ,  G06T5/40 ,  G06T5/92 ,  G06T7/11 ,  G06T7/12 ,  G06T11/00 ,  G06V10/28 ,  G06V10/75 ,  G06V10/776 ,  G16H30/40

CPC classification number: G06T7/0012 ,  A61B6/505 ,  A61B6/5205 ,  G06T5/40 ,  G06T5/92 ,  G06T7/11 ,  G06T7/12 ,  G06T11/00 ,  G06V10/28 ,  G06V10/751 ,  G06V10/776 ,  G16H30/40 ,  G06T2207/10116 ,  G06T2207/30008 ,  G06V2201/033

Abstract: A method for identifying one or more fractures in a digitized x-ray image includes: obtaining a digitized x-ray image; performing preprocessing on the digitized x-ray image to generate a modified x-ray image having enhanced resolution; partitioning the modified x-ray image into a two-dimensional array including multiple pixels; obtaining an intensity of each of the pixels in the modified x-ray image; evaluating each of the pixels in the modified x-ray image to determine whether at least a given one of the pixels has an intensity indicative of a black pixel; for each given pixel having an intensity indicative of a black pixel, flagging the given pixel when pixels immediately adjacent to the given pixel have an intensity greater than a prescribed threshold value; and placing a visual indication of a possible fracture on the modified x-ray image corresponding to a location of each flagged pixel.

公开(公告)号：US12020821B2

公开(公告)日：2024-06-25

申请号：US17539434

申请日：2021-12-01

Applicant: INDUSTRY-ACADEMIC COOPERATION FOUNDATION, YONSEI UNIVERSITY

Inventor： Namki Hong ,  Yumie Rhee ,  Hea-jeong Park

IPC: G16H50/30 ,  G06N20/10 ,  G06N20/20 ,  G06T5/20 ,  G06T5/40 ,  G06T7/00 ,  G06T7/40 ,  G06T11/00 ,  G06V10/25 ,  G06V10/54 ,  G16H30/40 ,  G16H50/70

CPC classification number: G16H50/30 ,  G06N20/10 ,  G06N20/20 ,  G06T5/20 ,  G06T5/40 ,  G06T7/0012 ,  G06T7/40 ,  G06T11/001 ,  G06V10/25 ,  G06V10/54 ,  G16H30/40 ,  G16H50/70 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/30008 ,  G06V2201/033

Abstract: Embodiments of the present invention relate to methods of predicting fracture risk, which improve fracture risk prediction by developing a bone radiomics score model based on machine learning. As an embodiment of the present invention, the method of predicting the fracture risk is configured to perform the steps of designing a development set, processing bone images for a plurality of subjects included in the development set, extracting texture features from the bone images, selecting optimal texture features required to predict the fracture risk from the extracted texture features, performing machine learning for the optimal texture features using a training set of the development set, and designing a bone radiomics score model to predict the fracture risk.

公开(公告)号：US12008695B2

公开(公告)日：2024-06-11

申请号：US17033183

申请日：2020-09-25

Applicant: GE Precision Healthcare LLC

Inventor： Sandeep Kaushik ,  Dattesh Shanbhag ,  Cristina Cozzini ,  Florian Wiesinger

IPC: G06T11/60 ,  A61B5/00 ,  A61B5/055 ,  G01R33/56 ,  G06F18/214

CPC classification number: G06T11/60 ,  A61B5/0033 ,  A61B5/055 ,  A61B5/7267 ,  G01R33/5608 ,  G06F18/214 ,  G06T2210/41 ,  G06V2201/033

Abstract: Various methods and systems are provided for translating magnetic resonance (MR) images to pseudo computed tomography (CT) images. In one embodiment, a method comprises acquiring an MR image, generating, with a multi-task neural network, a pseudo CT image corresponding to the MR image, and outputting the MR image and the pseudo CT image. In this way, the benefits of CT imaging with respect to accurate density information, especially in sparse regions of bone which exhibit with high dynamic range, may be obtained in an MR-only workflow, thereby achieving the benefits of enhanced soft-tissue contrast in MR images while eliminating CT dose exposure for a patient.

公开(公告)号：US20240177477A1

公开(公告)日：2024-05-30

申请号：US18430040

申请日：2024-02-01

Applicant: metamorphosis GmbH

Inventor： Arno BLAU

IPC: G06V10/94 ,  G06T7/13 ,  G06T7/73 ,  G06V10/44

CPC classification number: G06V10/95 ,  G06T7/13 ,  G06T7/75 ,  G06V10/44 ,  G06T2207/10116 ,  G06V2201/033

Abstract: Method and apparatus are provided for assisting with bone fracture detection. In particular, image data of a medical image is received in a processing unit from a device, which may be an imaging device, a data detection device or an image storage device. A bone structure is identified in the medical image. A fracture line in the identified bone structure is determined. A bone feature, which may include a portion of an outline of the identified bone structure, a point of the fracture line on an outline of the identified bone structure, a relative displacement of bone parts of the identified bone structure, or a combination thereof is detected. The bone feature may be classified and a corresponding output generated.

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：US11925481B2

公开(公告)日：2024-03-12

申请号：US17241077

申请日：2021-04-27

Applicant: FUJIFILM Corporation

Inventor： Kenta Yamada

IPC: A61B5/00 ,  G06F18/2431 ,  G06N20/00 ,  G06T7/00 ,  G06V10/40 ,  G06V10/764 ,  G06V10/82 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70

CPC classification number: A61B5/7267 ,  A61B5/0077 ,  A61B5/4504 ,  A61B5/7278 ,  G06F18/2431 ,  G06N20/00 ,  G06T7/0012 ,  G06V10/40 ,  G06V10/764 ,  G06V10/82 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  A61B2576/00 ,  G06T2207/30008 ,  G06V2201/033

Abstract: Information representing a physique of a subject is extracted from an image obtained by imaging the subject. A group in which the subject is classified is specified, using the extracted information representing the physique of the subject. Image data representing a medical image obtained by imaging the subject is input to a learned model corresponding to a specified group among learned models obtained for each group by machine learning using learning data for each group. Information representing an area extracted from the medical image is acquired, which is output from the learned model with the input.

公开(公告)号：US11883219B2

公开(公告)日：2024-01-30

申请号：US17895948

申请日：2022-08-25

Applicant: Orthogrid Systems Holdings, LLC

Inventor： Richard Boddington ,  Edouard Saget ,  Joshua Cates ,  Hind Oulhaj ,  Erik Noble Kubiak

IPC: G06T7/30 ,  A61B6/00 ,  A61B6/12 ,  G06V10/764 ,  G06V10/82 ,  G06T11/00 ,  G06T7/60

CPC classification number: A61B6/463 ,  A61B6/12 ,  A61B6/487 ,  A61B6/505 ,  G06T7/30 ,  G06T7/60 ,  G06T11/00 ,  G06V10/764 ,  G06V10/82 ,  G06T2200/24 ,  G06T2207/10064 ,  G06T2207/10116 ,  G06V2201/033 ,  G06V2201/034

Abstract: The inventive subject matter is directed to a computing platform configured to execute one or more automated artificial intelligence models, wherein the one or more automated artificial intelligence models includes a neural network model, wherein the one or more automated artificial intelligence models are trained on a plurality of radiographic images from a data layer to detect a plurality of anatomical structures or a plurality of hardware, wherein at least one anatomical structure is a pelvic teardrop and a symphysis pubis joint; detecting at a plurality of anatomical structures in a radiographic image of a subject, wherein the plurality of anatomical structures are detected by the computing platform by the step of classifying the radiographic image with reference to a subject good side radiographic image; and constructing a graphical representation of data, wherein the graphical representation is a subject specific functional pelvis grid; the subject specific functional pelvis grid generated based upon the anatomical structures detected by the computing platform in the radiographic image. Various types of functional grids can be generated based on the situation detected.

公开(公告)号：US20230410495A1

公开(公告)日：2023-12-21

申请号：US18241709

申请日：2023-09-01

Applicant: Align Technology, Inc.

Inventor： Ya Xue ,  Yingjie Li ,  Chao Shi ,  Aleksandr Anikin ,  Mikhail Toporkov ,  Aleksandr Sergeevich Karsakov

IPC: G06V10/82 ,  G06V10/44 ,  G06F18/2413 ,  G06V30/19 ,  G06T7/13 ,  G06T7/00

CPC classification number: G06V10/82 ,  G06V10/44 ,  G06F18/24143 ,  G06V30/19173 ,  G06T7/13 ,  G06T7/0012 ,  G06V2201/033 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2207/30004

Abstract: A method includes receiving an image of a face, processing the image using a first trained machine learning model to determine a bounding shape around teeth in the image, cropping the image based on the bounding shape to produce a cropped image, processing the cropped image using an edge detection operation to generate edge data for the cropped image, and processing the cropped image and the edge data using a second trained machine learning model to label edges in the cropped image.

公开(公告)号：US11847755B2

公开(公告)日：2023-12-19

申请号：US17326069

申请日：2021-05-20

Applicant: Howmedica Osteonics Corporation

Inventor： Ilwhan Park ,  Charlie W. Chi ,  Venkata Surya Sarva ,  Irene Min Choi ,  Elena Pavlovskaia ,  Oleg Mishin ,  Boris E. Shpungin

IPC: G06T19/20 ,  A61B17/70 ,  B33Y80/00 ,  G06T17/00 ,  A61B34/10 ,  A61B17/16 ,  A61B6/03 ,  G06T17/20 ,  A61B5/055 ,  G06T7/12 ,  G06T7/13 ,  A61B90/00 ,  A61B17/17 ,  B33Y50/02 ,  G16H50/50 ,  B33Y10/00 ,  G06T7/00 ,  B33Y50/00 ,  G06F30/00 ,  G06F30/20 ,  G06V10/46 ,  G06V10/22 ,  G06T7/70 ,  A61B17/15

CPC classification number: G06T19/20 ,  A61B5/055 ,  A61B6/032 ,  A61B17/1675 ,  A61B17/1703 ,  A61B17/7013 ,  A61B34/10 ,  A61B90/37 ,  B33Y10/00 ,  B33Y50/00 ,  B33Y50/02 ,  B33Y80/00 ,  G06F30/00 ,  G06F30/20 ,  G06T7/0012 ,  G06T7/12 ,  G06T7/13 ,  G06T17/00 ,  G06T17/20 ,  G06V10/225 ,  G06V10/46 ,  G16H50/50 ,  A61B17/155 ,  A61B17/157 ,  A61B2017/1602 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108 ,  A61B2090/374 ,  A61B2090/3762 ,  G06T7/70 ,  G06T2200/08 ,  G06T2207/30008 ,  G06T2210/41 ,  G06T2219/2021 ,  G06V10/471 ,  G06V2201/033 ,  Y10T29/49826

Abstract: A computer-implemented method of preoperatively planning a surgical procedure on a knee of a patient including determining femoral condyle vectors and tibial plateau vectors based on image data of the knee, the femoral condyle vectors and the tibial plateau vectors corresponding to motion vectors of the femoral condyles and the tibial plateau as they move relative to each other. The method may also include modifying a bone model representative of at least one of the femur and the tibia into a modified bone model based on the femoral condyle vectors and the tibial plateau vectors. And the method may further include determining coordinate locations for a resection of the modified bone model.

公开(公告)号：US11819282B2

公开(公告)日：2023-11-21

申请号：US17246604

申请日：2021-05-01

Applicant: Howmedica Osteonics Corporation

Inventor： Elena I. Pavlovskaia ,  Oleg Mishin ,  Boris E. Shpungin ,  Ilwhan Park ,  Venkata Surya Sarva ,  Irene Min Choi

IPC: A61B34/10 ,  A61B17/70 ,  A61B6/03 ,  A61B5/055 ,  G06T7/13 ,  G06T7/12 ,  G16H50/50 ,  G06T7/00 ,  B33Y50/02 ,  B33Y10/00 ,  G06T17/20 ,  A61B17/17 ,  A61B17/16 ,  G06T17/00 ,  B33Y80/00 ,  B33Y50/00 ,  A61B90/00 ,  G06F30/00 ,  G06F30/20 ,  G06V10/44 ,  A61B17/15 ,  G06T7/70

CPC classification number: A61B34/10 ,  A61B5/055 ,  A61B6/032 ,  A61B17/1675 ,  A61B17/1703 ,  A61B17/7013 ,  A61B90/37 ,  B33Y10/00 ,  B33Y50/00 ,  B33Y50/02 ,  B33Y80/00 ,  G06F30/00 ,  G06F30/20 ,  G06T7/0012 ,  G06T7/12 ,  G06T7/13 ,  G06T17/00 ,  G06T17/20 ,  G06V10/454 ,  G16H50/50 ,  A61B17/155 ,  A61B17/157 ,  A61B2017/1602 ,  A61B2034/105 ,  A61B2034/107 ,  A61B2034/108 ,  A61B2090/374 ,  A61B2090/3762 ,  G06T7/70 ,  G06T2200/08 ,  G06T2207/30008 ,  G06V2201/033 ,  Y10T29/49826

Abstract: A method for planning an arthroplasty procedure on a patient bone. The method may include accessing generic bone data stored in a memory of a computer, using the computer to generate modified bone data by modifying the generic bone data according to medical imaging data of the patient bone, using the computer to derive a location of non-bone tissue data relative to the modified bone data, and superimposing implant data and the modified bone data in defining a resection of an arthroplasty target region of the patient bone.