公开(公告)号：US12026927B2

公开(公告)日：2024-07-02

申请号：US17469472

申请日：2021-09-08

Applicant: FUJIFILM Corporation

Inventor： Shin Hamauzu

IPC: G06V10/00 ,  G06F18/214 ,  G06T7/00 ,  G06V10/25 ,  G06V20/00 ,  G16H50/20

CPC classification number: G06V10/25 ,  G06F18/214 ,  G06T7/0012 ,  G06V20/00 ,  G16H50/20 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20221 ,  G06T2207/30004 ,  G06V2201/034

Abstract: A processor performs machine learning, which uses a radiographic image that does not include a suture needle as a surgical tool and a surgical tool image that includes the suture needle in a posture different from a linear posture as training data, to construct a trained model for detecting a region of the suture needle from an input radiographic image.

公开(公告)号：US20240180627A1

公开(公告)日：2024-06-06

申请号：US18417779

申请日：2024-01-19

Applicant: Board of Regents of the University of Nebraska

Inventor： Hani HAIDER ,  Ibrahim AL-SHAWI ,  Osvaldo Andres BARRERA

IPC: A61B34/20 ,  A61B1/313 ,  A61B5/00 ,  A61B5/06 ,  A61B5/107 ,  A61B17/14 ,  A61B17/17 ,  A61B34/00 ,  A61B34/10 ,  A61B34/37 ,  A61B90/00

CPC classification number: A61B34/20 ,  A61B1/3132 ,  A61B5/061 ,  A61B5/1076 ,  A61B17/142 ,  A61B17/1703 ,  A61B34/37 ,  A61B34/76 ,  A61B5/00 ,  A61B2034/102 ,  A61B2034/2057 ,  A61B2034/2065 ,  A61B2090/061 ,  A61B2090/064 ,  A61B2090/3983 ,  G06T2207/30004 ,  G06V2201/034

Abstract: A number of improvements are provided relating to computer aided surgery utilizing an on tool tracking system. The various improvements relate generally to both the methods used during computer aided surgery and the devices used during such procedures. Other improvements relate to the structure of the tools used during a procedure and how the tools can be controlled using the OTT device. Still other improvements relate to methods of providing feedback during a procedure to improve either the efficiency or quality, or both, for a procedure including the rate of and type of data processed depending upon a CAS mode.

公开(公告)号：US20240144629A1

公开(公告)日：2024-05-02

申请号：US18280997

申请日：2022-03-09

Applicant: BD KIESTRA B.V.

Inventor： Franciscus Hermannus Feijen ,  Brent Ronald Pohl ,  Craig W. Bark ,  Jan Bart Van Der Vijver ,  Timothy Roy Hansen ,  Jurjen Sinnema ,  Martijn Kleefstra

IPC: G06V10/14 ,  G06V10/22 ,  G06V10/25

CPC classification number: G06V10/14 ,  G06V10/22 ,  G06V10/25 ,  G06V2201/034

Abstract: A system that may automatically and rapidly process blood culture bottles. Such processing includes obtaining an image of a label placed on the cylindrical surface of the blood culture bottle. The system may also determine an amount of blood sample that has been added to the blood culture bottle by comparing a sample level to pre-placed fiducial. The distance between the liquid meniscus in the blood culture bottle and fiducial may be used to determine blood volume. The imaging apparatus may also detect internal conditions of the blood culture bottle such as the presence of foam or the presence of culture media in a neck portion of the blood culture bottle. The image of the label is obtained from one or more images captured by a camera or scanner. The information on the label may be read automatically and therefore the blood culture bottles do not have to be processed manually, increasing throughput of the apparatus.

公开(公告)号：US11972593B2

公开(公告)日：2024-04-30

申请号：US17453319

申请日：2021-11-02

Applicant: GE Precision Healthcare LLC

Inventor： Hariharan Ravishankar ,  Pavan Annangi

IPC: G06T7/77 ,  A61B5/00 ,  A61B5/107 ,  G06T7/11 ,  G06T7/73 ,  G06T11/00

CPC classification number: G06T7/77 ,  A61B5/1079 ,  A61B5/7267 ,  A61B5/742 ,  A61B5/7475 ,  G06T7/11 ,  G06T7/73 ,  G06T11/00 ,  G06T2200/24 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20104 ,  G06T2207/30004 ,  G06V2201/034

Abstract: Systems and methods are provided for quantifying uncertainty of segmentation mask predictions made by machine learning models, where the uncertainty may be used to streamline an anatomical measurement workflow by automatically identifying less certain caliper placements. In one example, the current disclosure teaches receiving an image including a region of interest, determining a segmentation mask for the region of interest using a trained machine learning model, placing a caliper at a position within the image based on the segmentation mask, determining an uncertainty of the position of the caliper, and responding to the uncertainty of the position of the caliper being greater than a pre-determined threshold by displaying a visual indication of the position of the caliper via a display device and prompting a user to confirm or edit the position of the caliper.

公开(公告)号：US20240122463A1

公开(公告)日：2024-04-18

申请号：US18487942

申请日：2023-10-16

Applicant: ALIGN TECHNOLOGY, INC.

Inventor： Guotu LI ,  Chao SHI ,  Chad Clayton BROWN ,  Christopher E. CRAMER ,  Phillip Thomas HARRIS ,  Adam SILL ,  Will NEVILLE ,  Ritvik BANSAL

IPC: A61B1/24 ,  A61B1/00 ,  A61B1/045 ,  A61B1/32 ,  G06T7/00 ,  G06T7/11 ,  G06V20/50 ,  G06V40/16 ,  H04N23/60 ,  H04N23/611 ,  H04N23/667

CPC classification number: A61B1/24 ,  A61B1/00006 ,  A61B1/000096 ,  A61B1/045 ,  A61B1/32 ,  G06T7/0012 ,  G06T7/11 ,  G06V20/50 ,  G06V40/166 ,  G06V40/171 ,  H04N23/611 ,  H04N23/64 ,  H04N23/667 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2207/30036 ,  G06T2207/30168 ,  G06V2201/034

Abstract: Various apparatuses are disclosed (e.g., system, device, method, or the like) for guiding the capture and assessing the quality of an image, including dental images. The apparatuses may use trained neural networks to examine images and provide users feedback regarding image quality. The neural networks may be trained based on images within image groups that have been ranked based on perceived image quality.

公开(公告)号：US20240087322A1

公开(公告)日：2024-03-14

申请号：US18463683

申请日：2023-09-08

Applicant: University of Washington ,  Seattle Children's Hospital d/b/a Seattle Children's Research Institute

Inventor： Daniel King ,  Blake Hannaford ,  Yangming Li ,  Lingga Adidharma ,  Randall Bly ,  Al-Waleed M. Abuzeid ,  Kristen S. Moe

IPC: G06V20/50 ,  G06N3/0464 ,  G06N3/047 ,  G06N3/088 ,  G06T7/70 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G16H70/20

CPC classification number: G06V20/50 ,  G06N3/0464 ,  G06N3/047 ,  G06N3/088 ,  G06T7/70 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G16H70/20 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004 ,  G06V2201/034

Abstract: A method includes accessing training images that collectively depict multiple stages of a surgical procedure. The method also includes accessing labels that indicate, for each of the training images, characteristics of one or more surgical tools depicted and a stage of the multiple stages of the surgical procedure depicted. The method also includes training a computational model, using the training images and the labels, to associate runtime images with a stage of the multiple stages based on characteristics of one or more surgical tools that are depicted by the runtime images. Another method includes associating, using a computational model, runtime images with a stage of a surgical procedure based on characteristics of one or more surgical tools depicted by the runtime images and generating output that indicates the stage associated with each of the runtime images.

公开(公告)号：US20240073353A1

公开(公告)日：2024-02-29

申请号：US17893744

申请日：2022-08-23

Applicant: Rods&Cones Holding bv

Inventor： Jan DHEEDENE ,  Bruno DHEEDENE ,  Benoit QUIRYNEN ,  Dario VULJANIC ,  Dalibor KOFJAC

IPC: H04N5/272 ,  G06T11/00 ,  G06V10/22 ,  G06V10/26 ,  G06V20/40 ,  G06V20/62 ,  H04L12/18

CPC classification number: H04N5/272 ,  G06T11/00 ,  G06V10/235 ,  G06V10/267 ,  G06V20/41 ,  G06V20/46 ,  G06V20/63 ,  H04L12/1822 ,  G06V2201/034

Abstract: Capturing, masking and transmitting video feed from a medical unit in a videoconference can be performed with one or more remote users and preferably a local user in proximity to the medical unit. The method includes steps for the identification of the medical unit being used, creation of masks suitable to mask patient information, overlaying said mask to the original video feed and providing a single masked video feed. A system can be suitable to connect to receive input from a medical unit, apply the abovementioned method and provide the produced masked video feed to a videoconference system.

公开(公告)号：US11883312B2

公开(公告)日：2024-01-30

申请号：US17899687

申请日：2022-08-31

Applicant: DIGITAL SURGERY LIMITED

Inventor： Andre Chow ,  Danail Stoyanov ,  Imanol Luengo Muntion ,  Petros Giataganas ,  Jean Nehme

IPC: A61F5/00 ,  A61B34/10 ,  G06N20/00 ,  G05B19/4155 ,  A61B17/32 ,  A61B17/068 ,  G06V20/40 ,  A61B1/00 ,  G06F18/21 ,  G06V10/70 ,  A61B17/00

CPC classification number: A61F5/0076 ,  A61B1/000096 ,  A61B17/068 ,  A61B17/320016 ,  A61B17/320092 ,  A61B34/10 ,  G05B19/4155 ,  G06F18/217 ,  G06N20/00 ,  G06V10/70 ,  G06V20/41 ,  A61B2017/00061 ,  A61B2017/00119 ,  A61B2017/00199 ,  A61B2017/00212 ,  A61B2017/320082 ,  A61B2017/320095 ,  A61B2034/107 ,  G05B2219/36414 ,  G06V2201/034

Abstract: The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.

公开(公告)号：US11871901B2

公开(公告)日：2024-01-16

申请号：US16209478

申请日：2018-12-04

Applicant: Cilag GmbH International

Inventor： Frederick E. Shelton, IV ,  Jason L. Harris ,  David C. Yates

IPC: G16H50/30 ,  A61B1/00 ,  A61B1/005 ,  A61B1/06 ,  A61B1/05 ,  A61B5/00 ,  A61B34/00 ,  A61B18/00 ,  A61B90/00 ,  A61B18/14 ,  G16H40/60 ,  A61B34/37 ,  G06T7/20 ,  G06T7/70 ,  A61B17/00 ,  A61B17/068 ,  A61B5/026 ,  A61B5/02 ,  A61B5/021 ,  A61B5/318

CPC classification number: A61B1/00006 ,  A61B1/00042 ,  A61B1/0052 ,  A61B1/000094 ,  A61B1/000096 ,  A61B1/051 ,  A61B1/0661 ,  A61B1/0684 ,  A61B5/0071 ,  A61B18/00 ,  A61B18/1445 ,  A61B34/25 ,  A61B34/37 ,  A61B90/361 ,  G16H40/60 ,  A61B5/0035 ,  A61B5/021 ,  A61B5/026 ,  A61B5/02042 ,  A61B5/318 ,  A61B5/4821 ,  A61B5/7264 ,  A61B17/068 ,  A61B2017/00022 ,  A61B2017/00044 ,  A61B2017/00061 ,  A61B2017/00106 ,  A61B2017/00119 ,  A61B2017/00442 ,  A61B2034/254 ,  A61B2090/061 ,  A61B2090/365 ,  A61B2218/008 ,  A61B2505/05 ,  G06T7/20 ,  G06T7/70 ,  G06T2207/10068 ,  G06V2201/034

Abstract: A computer-implemented method for contextually controlling a surgical device is disclosed. The method includes receiving, by a computer system, perioperative data from the surgical device, the perioperative data associated with a surgical procedure; receiving, by the computer system, images from a scope, the images visualizing the surgical device during the surgical procedure; determining, by the computer system, an attribute of the surgical device from the images; determining, by the computer system, procedural context data based at least on the perioperative data and the attribute of the surgical device; and controlling, by the computer system, the surgical device according to the procedural context data.

公开(公告)号：US20230360416A1

公开(公告)日：2023-11-09

申请号：US17650019

申请日：2020-08-05

Applicant: 3M INNOVATIVE PROPERTIES COMPANY

Inventor： Muhammad J. Afridi ,  Mojtaba Kadkhodaie Elyaderani ,  Matthew T. Scholz

IPC: G06V20/80

CPC classification number: G06V20/80 ,  G06V2201/034

Abstract: A product authentication system includes one or more image capture devices that provide video data representative of an enhanced safety environment. The product authentication system can determine the continuous presence of a designated product during a time period, for example, during performance of a task in an enhanced safety environment. The video data can be spatiotemporally sliced according to multiple orientations with respect to the time axis and the two spatial axes. A plurality of data streams are created In where the slices of each respective data stream have the same orientation. The data streams are processed according to one or more machine learning models, such as convolutional neural networks trained to determine whether the designated product is continuously present in the video data. An indicator of the continuous presence of the designated product can be provided to a downstream system and used to indicate whether functions of the downstream system are to be performed.