公开(公告)号：US20240382180A1

公开(公告)日：2024-11-21

申请号：US18667989

申请日：2024-05-17

Applicant: Boston Scientific Scimed Inc.

Inventor： Alexander Shang ,  Wenguang Li ,  Kevin Bloms ,  Yan Li

IPC: A61B8/08 ,  A61B8/00 ,  A61B8/12

Abstract: The present disclosure provides to process intravascular ultrasound (IVUS) images from different runs through a vessel to generate a mapping between frames of each IVUS run and to generate a graphical user interface (GUI) to graphically present the IVUS runs in relationship to each other. In some examples, a vessel fiducial is identified in a frame of each IVUS run and one or both runs are offset in time, distance, and/or angle to align the frames with the identified vessel fiducial. Further, the disclosure provides to angularly align intravascular images to a viewing perspective of an external image of the vessel.

公开(公告)号：US20250061653A1

公开(公告)日：2025-02-20

申请号：US18797804

申请日：2024-08-08

Applicant: Boston Scientific Scimed Inc.

Inventor： Erik Stephen Freed ,  Sebastian Ordas ,  Alexander Shang ,  Wenguang Li ,  Alan Torborg

IPC: G06T17/00 ,  G06T7/00 ,  G06T7/12 ,  G06T7/13 ,  G06T7/33 ,  G06T7/90

Abstract: The present disclosure provides to generate a 3D visualization of a vessel from intravascular ultrasound (IVUS) images. In particular, the present disclosure provides to reduce jitter between frames of an IVUS recording to provide a smoother appearance of a longitudinal view of the vessel from the IVUS image frames and to construct a 3D visualization of the vessel from the jitter compensated IVUS image frames.

公开(公告)号：US20240428429A1

公开(公告)日：2024-12-26

申请号：US18667561

申请日：2024-05-17

Applicant: Boston Scientific Scimed Inc.

Inventor： Qian Li ,  Hatice Cinar Akakin ,  Alexander Shang ,  Wenguang Li

IPC: G06T7/33 ,  G06T7/73 ,  G06V10/82

Abstract: The present disclosure provides devices and methods to identify locations of side branches in a series of intravascular images (e.g., a pre-treatment IVUS pullback, a post-treatment IVUS pullback, or the like) to assist with co-registering the IVUS images with an extravascular image (e.g., angiogram, or the like) or with another set of IVUS images. The present disclosure further provides devices and methods for training a machine learning (ML) model to infer side branch locations from IVUS images and an analytic algorithm for extracting frames from the IVUS images representing side branches.

公开(公告)号：US20240382181A1

公开(公告)日：2024-11-21

申请号：US18667955

申请日：2024-05-17

Applicant: Boston Scientific Scimed Inc.

Inventor： Alexander Shang ,  Wenguang Li ,  Yan Li ,  Kevin Bloms

IPC: A61B8/08 ,  A61B8/00 ,  A61B8/12

Abstract: The present disclosure provides to process intravascular ultrasound (IVUS) images from different runs through a vessel to generate a mapping between frames of each IVUS run and to generate a graphical user interface (GUI) to graphically present the IVUS runs in relationship to each other. In some examples, a vessel fiducial is identified in a frame of each IVUS run and one or both runs are offset in time, distance, and/or angle to align the frames with the identified vessel fiducial. Further, the disclosure provides to angularly align intravascular images to a viewing perspective of an external image of the vessel.

公开(公告)号：US20230210381A1

公开(公告)日：2023-07-06

申请号：US18091772

申请日：2022-12-30

Applicant: Boston Scientific Scimed, Inc.

Inventor： Kevin Bloms ,  Wenguang Li ,  Hatice Cinar Akakin ,  Alexander Shang

IPC: A61B5/02 ,  A61B8/08

CPC classification number: A61B5/02028 ,  A61B8/0891 ,  G06T2207/30101 ,  G06N3/08

Abstract: A neural network is trained for estimating patient hemodynamic data using a plurality of extravascular imaging data sets and a plurality of intravascular imaging data sets that are each co-registered to a corresponding extravascular imaging data set. A plurality of hemodynamic data sets are provided, each hemodynamic data set co-registered with the corresponding extravascular imaging data set. The neural network learns what hemodynamic data to expect for a given intravascular imaging data set. An intravascular imaging event is subsequently performed in which an intravascular imaging element is translated within a blood vessel of the patient to produce one or more intravascular images. The neural network uses its training to predict hemodynamic values corresponding to the one or more intravascular images from the intravascular imaging event, and the one or more intravascular images are outputted in combination with the predicted hemodynamic values.