公开(公告)号：US20230018499A1

公开(公告)日：2023-01-19

申请号：US17862991

申请日：2022-07-12

Applicant: LightLab Imaging, Inc.

Inventor： Justin Akira Blaber ,  Ajay Gopinath ,  Humphrey Chen ,  Kyle Edward Savidge ,  Angela Zhang ,  Gregory Patrick Amis

IPC: G06T7/00 ,  G16H50/20 ,  G16H30/40

Abstract: Aspects of the disclosure relate to systems, methods, and algorithms to train a machine learning model or neural network to classify OCT images. The neural network or machine learning model can receive annotated OCT images indicating which portions of the OCT image are blocked and which are clear as well as a classification of the OCT image as clear or blocked. After training, the neural network can be used to classify one or more new OCT images. A user interface can be provided to output the results of the classification and summarize the analysis of the one or more OCT images.

公开(公告)号：US20240099585A1

公开(公告)日：2024-03-28

申请号：US18267670

申请日：2021-12-17

Applicant: LightLab Imaging, Inc.

Inventor： Justin Akira Blaber ,  Ajay Gopinath ,  Wei Chiu

IPC: A61B5/00 ,  A61B5/026 ,  A61B5/107

CPC classification number: A61B5/0066 ,  A61B5/0261 ,  A61B5/1076

Abstract: The present disclosure provides systems and methods for determining a mean transit time of a bolus within the blood vessel by passing the bolus through the blood vessel while an intravascular imaging probe is held stationary. The probe may collect a plurality of image frames as the bolus passes the probe. The cross-sectional area of the bolus within the images frames may be determined by segmenting each image frame by thresholding, creating a vessel mask, and creating a contrast mask by applying an element-wise AND operator to the thresholded image and the vessel mask. The cross-sectional area of the bolus for the image frames may be plotted on an area dilution curve. Various fits may be applied to and various points may be identified on the area dilution curve. The various fits and points may be used to determine the mean transit time.

公开(公告)号：US20230005139A1

公开(公告)日：2023-01-05

申请号：US17854994

申请日：2022-06-30

Applicant: LightLab Imaging, Inc.

Inventor： Justin Akira Blaber ,  Ajay Gopinath ,  Gregory Patrick Amis ,  Kyle Savidge

IPC: G06T7/00 ,  G06T7/12 ,  G16H30/40 ,  G16H50/20 ,  G06N20/00

Abstract: Aspects of the disclosure provide for methods, systems, and apparatuses, including computer-readable storage media, for lipid detection by identifying fibrotic caps in medical images of blood vessels. A method includes receiving one or more input images of a blood vessel and processing the one or more input images using a machine learning model trained to identify locations of fibrotic caps in blood vessels. The machine learning model is trained using a plurality of training images each annotated with locations of one or more fibrotic caps. A method includes identifying and characterizing fibrotic caps of lipid pools based on differences in radial signal intensities measured at different locations of an input image. A system can generate one or more output images having segments that are visually annotated representing predicted locations of fibrotic caps covering lipidic plaques.