公开(公告)号：US20230230263A1

公开(公告)日：2023-07-20

申请号：US18067691

申请日：2022-12-16

Applicant: Auris Health, Inc.

Inventor： Elif AYVALI ,  Bulat Ibragimov

IPC: G06T7/37 ,  G06V10/20 ,  G06V10/26 ,  G06T7/33 ,  A61B34/20

CPC classification number: G06T7/37 ,  A61B34/20 ,  G06T7/33 ,  G06V10/26 ,  G06V10/255 ,  A61B2034/2048 ,  A61B2034/2051 ,  A61B2034/2061 ,  G06T2207/10064 ,  G06T2207/30084 ,  G06V2201/031 ,  G06V2201/034

Abstract: The present disclosure relates to systems, devices, and methods to augment a two-dimensional image.

公开(公告)号：US11704790B2

公开(公告)日：2023-07-18

申请号：US16141605

申请日：2018-09-25

Applicant: Eric Leuthardt ,  Carl Hacker ,  Shan Siddiqi ,  Tim Laumann ,  Andy Daniel

Inventor： Eric Leuthardt ,  Carl Hacker ,  Shan Siddiqi ,  Tim Laumann ,  Andy Daniel

IPC: A61B5/00 ,  G06T7/00 ,  A61B34/10 ,  A61B5/055 ,  G16H30/40 ,  G06N3/00 ,  G16H50/20 ,  G06F18/213 ,  G06F18/21 ,  G06F18/2415 ,  G06F18/2413 ,  G06V10/764 ,  G01R33/48 ,  G16H20/40

CPC classification number: G06T7/0012 ,  A61B5/0042 ,  A61B5/055 ,  A61B5/4064 ,  A61B34/10 ,  G06F18/213 ,  G06F18/2178 ,  G06F18/2415 ,  G06F18/24133 ,  G06N3/00 ,  G06V10/764 ,  G16H30/40 ,  G16H50/20 ,  A61B5/4848 ,  A61B5/7267 ,  A61B2034/107 ,  A61B2576/026 ,  G01R33/4806 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016 ,  G06V2201/031 ,  G16H20/40

Abstract: A target location for a therapeutic intervention is determined in a subject with a neurological disorder. The target location is selected within at least one resting state network (RSN) map according to a predetermined criterion for the neurological disorder. The at least one RSN map includes a plurality of functional voxels within a brain of the subject, and each functional voxel of the plurality of functional voxels is associated with a probability of membership in an RSN. Instructions are transmitted to a treatment system that cause operation to be performed on the selected target location.

公开(公告)号：US20230206459A1

公开(公告)日：2023-06-29

申请号：US17816382

申请日：2022-07-29

Applicant: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.

Inventor： Yang XIN ,  Xu WANG ,  Guobin LI

IPC: G06T7/149 ,  G06T7/11 ,  G06V10/26 ,  G06T11/00 ,  G01R33/56 ,  G01R33/563

CPC classification number: G06T7/149 ,  G06T7/11 ,  G06V10/273 ,  G06T11/008 ,  G01R33/5608 ,  G01R33/5635 ,  G06T2207/30101 ,  G06T2207/30204 ,  G06T2210/41 ,  G06V2201/031

Abstract: The present disclosure is related to systems and methods for image processing. The method includes obtaining an original image. The original image includes at least one blood vessel region and at least one scalp region. The method includes determining an intermediate image by removing the at least one scalp region from the original image. The method includes generating at least one target image by performing a maximum intensity projection operation on the intermediate image. The at least one target image represents the at least one blood vessel region in the original image.

公开(公告)号：US20230148834A1

公开(公告)日：2023-05-18

申请号：US17916826

申请日：2021-04-27

Applicant: Given Imaging LTD.

Inventor： Dorit Baras ,  Eyal Dekel ,  Eva Niv

IPC: A61B1/00 ,  G06V10/82 ,  G06V10/764 ,  G06T7/00 ,  A61B1/04

CPC classification number: A61B1/000094 ,  G06V10/82 ,  G06V10/764 ,  G06T7/0012 ,  G06T7/97 ,  A61B1/041 ,  A61B1/000096 ,  A61B1/000095 ,  G06T2207/30092 ,  G06T2207/10068 ,  G06T2207/20084 ,  G06V2201/031 ,  G06T2207/30028

Abstract: In accordance with aspects of the present disclosure, a system includes at least one processor and at least one memory storing instructions which, when executed by the processor(s), cause the system to access images of a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device; for each of the images, provide, by a deep learning neural network, scores for classifying the image to each of consecutive segments of the GIT; classify each image of a subset of the images, whose scores satisfy a confidence criterion, to one of the consecutive segments of the GIT; refine the classifications of the images in the subset by processing a signal over time corresponding to the classifications of the images in the subset; and estimate, among the images in the subset, a transition (1010) between two adjacent segments of the GIT based on the refined classifications of the images in the subset.

公开(公告)号：US20230143748A1

公开(公告)日：2023-05-11

申请号：US17996860

申请日：2021-04-22

Applicant: MARS BIOIMAGING LIMITED

Inventor： Philip Howard BUTLER ,  Anthony Philip Howard BUTLER ,  Niels J A DE RUITER ,  Robert LINDEMAN ,  Praveenkumar KANITHI

IPC: G06T7/174 ,  G06N20/20 ,  G06V10/44 ,  G06T7/194 ,  G06V10/26 ,  G06T7/00

CPC classification number: G06T7/174 ,  G06N20/20 ,  G06V10/457 ,  G06T7/194 ,  G06V10/267 ,  G06T7/0012 ,  G06T2207/20081 ,  G06T2207/20076 ,  G06V2201/031 ,  G06T2207/30096 ,  G06T2207/30012 ,  G06T2207/10084

Abstract: Segmentation of multi-energy CT data, including data in three or more energy bands. A user is enabled to input one or more region indicators in displayed CT data. Probability maps are generated and may be refined using distance metrics, which may include geodesic and Euclidean distance metrics. Segmentation may be based on the probability maps and/or refined probability maps. Segmentation of medical image data is also disclosed.

公开(公告)号：US20240354954A1

公开(公告)日：2024-10-24

申请号：US18681632

申请日：2022-07-25

Applicant: KONINKLIJKE PHILIPS N.V.

Inventor： ANDRE BRAUNAGEL ,  THOMAS KOEHLER

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/26

CPC classification number: G06T7/0014 ,  G06V10/25 ,  G06V10/26 ,  G06T2200/04 ,  G06T2207/10116 ,  G06T2207/20021 ,  G06T2207/30061 ,  G06V2201/031

Abstract: Apart from signal changes in three-dimensional X-ray dark-field (3D-DAX) imaging, also significant signal heterogeneity can be revealed. A method and apparatus for heterogencity analysis in 3D X-ray dark field imaging are provided, to enable the generation of parameters for an objective quantification and assessment of signal heterogeneity in 3D-DAX image data of a subject. In addition, a system for 3D X-ray imaging comprising said apparatus, a computer program element for carrying out the method and/or controlling the apparatus and/or system, and a computer readable medium having stored thereon the program element, are provided.

公开(公告)号：US20240331415A1

公开(公告)日：2024-10-03

申请号：US18294059

申请日：2022-08-10

Applicant: Hoffmann-La Roche Inc.

Inventor： Filippo ARCADU ,  Citlalli GAMEZ SERNA ,  Fernando ROMERO PALOMO

IPC: G06V20/69 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80 ,  G06V10/82 ,  G06V20/70

CPC classification number: G06V20/698 ,  G06V10/774 ,  G06V10/776 ,  G06V10/806 ,  G06V10/82 ,  G06V20/695 ,  G06V20/70 ,  G06V2201/031

Abstract: A computer-implemented method of identifying a tissue type in digital histological images of human or animal tissue comprises training a convolutional neural network CNN to identify a particular target tissue type in a plurality of training data sets of digital histological images, inputting a test data set of digital histological images into the trained convolutional neural network, receiving as an output result of the convolutional neural network a probability value that the inputted test data set corresponds to the target tissue type. A training procedure of the CNN comprises performing with a plurality of training data sets the steps of selecting a target tissue area of the training data set, dividing the target tissue area into a different sets of tiles of constant size but having different image magnifications, inputting the sets of tiles into a multi-headed convolutional neural network, wherein the sets of tiles having different image magnifications are processed in parallel and the features of the sets of tiles are concatenated.

公开(公告)号：US20240331358A1

公开(公告)日：2024-10-03

申请号：US18599150

申请日：2024-03-07

Applicant: FUJIFILM Corporation

Inventor： Aya OGASAWARA

IPC: G06V10/774 ,  G06T11/00

CPC classification number: G06V10/774 ,  G06T11/00 ,  G06T2210/41 ,  G06V2201/031

Abstract: An image processing apparatus receives relationship information indicating a relationship between a plurality of partial regions in a target organ, and generates a medical image in which an indirect finding associated with occurrence of a lesion exists in the target organ based on the relationship information.

公开(公告)号：US12106473B2

公开(公告)日：2024-10-01

申请号：US17507949

申请日：2021-10-22

Applicant: National Taiwan University

Inventor： Wei-Chung Wang ,  Wei-Chih Liao ,  Kao-Lang Liu ,  Po-Ting Chen ,  Po-Chuan Wang ,  Da-Wei Chang

IPC: G06T7/00 ,  A61B5/00 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20

CPC classification number: G06T7/0012 ,  A61B5/425 ,  A61B5/4887 ,  A61B5/726 ,  A61B5/7267 ,  G06N3/08 ,  G06T7/70 ,  G06T7/73 ,  G06V10/774 ,  G06V10/776 ,  G06V10/82 ,  G16H30/20 ,  G06T2207/20016 ,  G06T2207/20064 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T2207/30204 ,  G06V2201/031

Abstract: A medical image analyzing system and a medical image analyzing method are provided and include inputting at least one patient image into a first model of a neural network module to obtain a result having determined positions and ranges of an organ and a tumor of the patient image; inputting the result into a second model of a first analysis module and a third model of a second analysis module, respectively, to obtain at least one first prediction value and at least one second prediction value corresponding to the patient image; and outputting a determined result based on the first prediction value and the second prediction value. Further, processes between the first model, the second model and the third model can be automated, thereby improving identification rate of pancreatic cancer.

公开(公告)号：US20240320842A1

公开(公告)日：2024-09-26

申请号：US18610895

申请日：2024-03-20

Applicant: Siemens Healthineers AG

Inventor： Michael Manhart ,  Stanislav Tashenov

IPC: G06T7/33 ,  G06T11/60 ,  G06V10/74

CPC classification number: G06T7/337 ,  G06T11/60 ,  G06V10/761 ,  G06T2207/30101 ,  G06T2210/41 ,  G06V2201/031

Abstract: A method for providing a result dataset includes capturing a vessel dataset. The vessel dataset has time-resolved images of at least one vessel section of an examination object in a number of physiological phases. The method includes capturing an object dataset. The object dataset has an image of a medical object in the examination object in at least one physiological phase of the number of physiological phases. The method includes identifying a corresponding image in the vessel dataset in each case for the images of the object dataset with matching physiological phase, and providing the result dataset by at least partial overlaying and/or mixing of the images of the object dataset with the corresponding images of the vessel dataset.