公开(公告)号：US20240242816A1

公开(公告)日：2024-07-18

申请号：US18558708

申请日：2022-05-02

Applicant: Memorial Sloan-Kettering Cancer Center ,  Sloan-Kettering Institute for Cancer Research ,  Memorial Hospital for Cancer and Allied Diseases

Inventor： Luke Geneslaw ,  Thomas Fuchs ,  Dig Vijay Kumar Yarlagadda

IPC: G16H30/20 ,  G06T7/00 ,  G06V10/20 ,  G06V10/56

CPC classification number: G16H30/20 ,  G06T7/0012 ,  G06V10/255 ,  G06V10/56 ,  G06V2201/03 ,  G06V2201/10

Abstract: Presented herein are systems and methods for detecting labels in biomedical images. A computing system having one or more processors coupled with memory may identify, from a data source, a biomedical image having a first plurality of pixels in a first color representation. The computing system may convert the first plurality of pixels from the first color representation to a second color representation to generate a second plurality of pixels. The computing system may identify, from the second plurality of pixels, a subset of pixels having a color value satisfying a threshold value. The computing system may detect the biomedical image as having at least one label based at least on a number of pixels in the subset of pixels satisfying a threshold count. The computing system may store, in one or more data structures, an indication for the biomedical image as having the at least one label.

公开(公告)号：US20240242520A1

公开(公告)日：2024-07-18

申请号：US18558041

申请日：2022-05-05

Applicant: X-ZELL BIOTECH PTE LTD

Inventor： John Lea ,  Sebastian Chakrit Punyaratabandhu Bhakdi

IPC: G06V20/69 ,  G06V10/26 ,  G06V10/774

CPC classification number: G06V20/698 ,  G06V10/273 ,  G06V10/774 ,  G06V20/695 ,  G06V2201/03

Abstract: Disclosed herein are systems and methods of identifying and classifying rare cells. A machine learning system comprising learning layers is trained to develop algorithms to rapidly identify and classify unknown biological samples on an image. The algorithms identify and classify regions of cells, cell types, and cell subtypes.

公开(公告)号：US12039729B2

公开(公告)日：2024-07-16

申请号：US17924678

申请日：2021-02-05

Applicant: MEDIPIXEL, INC.

Inventor： Jihoon Kweon ,  Young-Hak Kim ,  Hwi Kwon

IPC: G06T7/00 ,  G06T5/77 ,  G06T7/11 ,  G06T7/60 ,  G06V10/44 ,  G06V10/98

CPC classification number: G06T7/0012 ,  G06T5/77 ,  G06T7/11 ,  G06T7/60 ,  G06V10/457 ,  G06V10/993 ,  G06T2207/30101 ,  G06T2207/30168 ,  G06V2201/03

Abstract: A method, performed by a processor, for processing a blood vessel image from an angiography image may comprise the steps of: extracting a target blood vessel from a blood vessel image; identifying an error portion from the extraction result of the target blood vessel on the basis of at least one of blood vessel structure data related to the target blood vessel, curvature information of the target blood vessel, diameter information of the target blood vessel, and brightness information of the target blood vessel; and in response to a case where an error portion is identified in the target blood vessel, correcting the identified error portion.

公开(公告)号：US20240231593A1

公开(公告)日：2024-07-11

申请号：US18613152

申请日：2024-03-22

Applicant: FUJIFILM Corporation

Inventor： Eiichi IMAMICHI ,  Takuya YUZAWA

IPC: G06F3/04847 ,  G06F3/04842 ,  G06V10/25

CPC classification number: G06F3/04847 ,  G06F3/04842 ,  G06V10/25 ,  G06V2201/03

Abstract: An information processing apparatus including at least one processor, wherein the processor is configured to: acquire a group of images to which mutually independent attribute information is assigned and which are spatially or temporally continuous; and display a slider bar for receiving an operation of selecting an image to be displayed on a display among the group of images, on the display by changing a display form based on the attribute information that is assigned to each of the images.

公开(公告)号：US20240225797A1

公开(公告)日：2024-07-11

申请号：US18431128

申请日：2024-02-02

Applicant: DENTAL MONITORING

Inventor： Philippe SALAH ,  Thomas PELLISSARD ,  Laurent DEBRAUX

IPC: A61C9/00 ,  G06F18/22 ,  G06T7/00 ,  G06T7/33 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G16H50/70

CPC classification number: A61C9/0053 ,  G06F18/22 ,  G06T7/0016 ,  G06T7/337 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G16H50/70 ,  G06T2207/20084 ,  G06T2207/30036 ,  G06V2201/03

Abstract: Method of enrichment of a reference model to be enriched representing a dental arch. Acquisition, under first real conditions, of a current image of the arch displaying one region. Exploration of the reference model in such a manner as to determine a first view of the reference model, in a first direction of observation the reference image exhibiting a maximum match with the current image. Determination, by comparison of the images, of a first orphan point represented on the current image and not represented on the reference image when the current image is in a first register position in which it is superposed, in the space of the reference model, with the reference image. Addition, in the reference model, of a point on a first straight line parallel to the first direction of observation and passing through the first orphan point in the first register position.

公开(公告)号：US20240221366A1

公开(公告)日：2024-07-04

申请号：US18606892

申请日：2024-03-15

Applicant: TERUMO KABUSHIKI KAISHA

Inventor： Shunsuke YOSHIZAWA ,  Yasukazu SAKAMOTO ,  Katsuhiko SHIMIZU ,  Hiroyuki ISHIHARA

IPC: G06V10/774 ,  A61B1/00 ,  G06V10/26 ,  G06V10/44 ,  G06V10/764

CPC classification number: G06V10/774 ,  A61B1/000096 ,  G06V10/267 ,  G06V10/457 ,  G06V10/764 ,  G06V2201/03

Abstract: A learning model generation method for generating a learning model that aids understanding of an image acquired with an image-acquiring catheter. The learning model generation method includes: creating a division line that divides a lumen region into a first region into which the image-acquiring catheter is inserted and a second region reaching an edge of a two-dimensional image, when it is determined that the lumen region reaches an edge of the two-dimensional image; creating second classification data in which a probability of being the lumen region and a probability of being an extra-luminal region are allocated; recording the two-dimensional image associated with the second classification data in a training database; and generating a learning model that outputs third classification data in which an input two-dimensional image is classified into a plurality of regions including a living tissue region, the lumen region, and an extra-luminal region, by machine learning.

公开(公告)号：US12026890B2

公开(公告)日：2024-07-02

申请号：US17620079

申请日：2020-06-16

Applicant: SurgVision GmbH

Inventor： Maximilian Koch

IPC: G06T7/174 ,  A61B5/00 ,  G06T7/00 ,  G06T7/11 ,  G06V10/22 ,  G06V10/60

CPC classification number: G06T7/174 ,  A61B5/0071 ,  G06T7/0016 ,  G06T7/11 ,  G06V10/22 ,  G06V10/60 ,  G06T2207/10064 ,  G06T2207/10152 ,  G06T2207/20212 ,  G06T2207/30088 ,  G06V2201/03

Abstract: A solution is proposed for imaging an object containing a luminescence substance. A corresponding method (500) is based on a refining loop. At each iteration of the refining loop, different spatial patterns are determined (516-518, 524;536-540, 546), partial illuminations corresponding to the spatial patterns are applied to the object (520,526;542,548), component images are acquired in response to the partial illuminations (522,528;544,550) and the component images are combined (530;552) into a combined image. A corresponding system (100) is also proposed. Moreover, a computer program (400) and a corresponding computer program product are proposed. A diagnostic method, a surgical method and a therapeutic method based on the same solution are further proposed.

公开(公告)号：US12026881B2

公开(公告)日：2024-07-02

申请号：US17567458

申请日：2022-01-03

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Bin Kong ,  Youbing Yin ,  Xin Wang ,  Yi Lu ,  Haoyu Yang ,  Junjie Bai ,  Qi Song

IPC: G06T7/12 ,  G06F18/213 ,  G06F18/214 ,  G06T7/00 ,  G06T7/73 ,  G06V10/44

CPC classification number: G06T7/0012 ,  G06F18/213 ,  G06F18/214 ,  G06T7/75 ,  G06V10/44 ,  G06T2207/20081 ,  G06T2207/30104 ,  G06V2201/03

Abstract: Embodiments of the disclosure provide methods and systems for joint abnormality detection and physiological condition estimation from a medical image. The exemplary method may include receiving, by at least one processor, the medical image acquired by an image acquisition device. The medical image includes an anatomical structure. The method may further include applying, by the at least one processor, a joint learning model to determine an abnormality condition and a physiological parameter of the anatomical structure jointly based on the medical image. The joint learning model satisfies a predetermined constraint relationship between the abnormality condition and the physiological parameter.

公开(公告)号：US12026868B2

公开(公告)日：2024-07-02

申请号：US17314767

申请日：2021-05-07

Applicant: ELUCID BIOIMAGING INC.

Inventor： Andrew J. Buckler ,  Mark A. Buckler

IPC: G06T7/00 ,  A61B6/00 ,  A61B6/50 ,  G06T11/00 ,  G06V10/20 ,  G06V10/56 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60 ,  G06V10/94 ,  G16H50/30 ,  G16H50/70

CPC classification number: G06T7/001 ,  A61B6/504 ,  A61B6/5247 ,  G06T11/008 ,  G06V10/255 ,  G06V10/56 ,  G16H10/60 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/30101 ,  G06V10/95 ,  G06V2201/03 ,  G16H50/30 ,  G16H50/70

Abstract: Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

公开(公告)号：US20240212811A1

公开(公告)日：2024-06-27

申请号：US18288963

申请日：2022-04-20

Applicant: Bayer Aktiengesellschaft

Inventor： Steffen VOGLER ,  Johannes HOEHNE ,  Matthias LENGA

IPC: G16H15/00 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80 ,  G16H10/60

CPC classification number: G16H15/00 ,  G06V10/774 ,  G06V10/776 ,  G06V10/803 ,  G16H10/60 ,  G06V2201/03

Abstract: A method for training a machine learning model that is able to establish links between data of different modalities by creating a joint representation. In particular, application of the method to medical data including electronic medical records and medical images and/or other medical data. The trained machine learning model can among others fulfil tasks such as autocompletion of incomplete data, detection of uncertain and/or spurious data, generation of probable data and other tasks.