US 2024/0404263 A1 · ULTRASOUND IMAGE FEATURE SEGMENTATION

Abstract

By example, a method for training a model to segment test images, wherein the test images comprise ultrasound image data, includes: receiving, at a self-supervised learning framework, a first plurality of training images, wherein the first plurality of training images include ultrasound data corresponding to patients' livers; processing the first plurality of plurality of training images with a learning algorithm of the self-supervised learning framework, and responsively adapting a trained model; and receiving, at a supervised learning framework, the trained model and a second plurality of training images, wherein the second plurality of training images include ultrasound data corresponding to patients' livers and annotations of the livers, and responsively adapting the trained model.

Claims20

Dependent claims

A method for training a model to segment test images, wherein the test images comprise ultrasound image data, the method comprising:

receiving, at a self-supervised learning framework, a first plurality of training images, wherein the first plurality of training images include ultrasound data corresponding to patients' livers;
processing the first plurality of plurality of training images with a learning algorithm of the self-supervised learning framework, and responsively adapting a trained model;
and
receiving, at a supervised learning framework, the trained model and a second plurality of training images, wherein the second plurality of training images include ultrasound data corresponding to patients' livers and annotations of the livers, and responsively adapting the trained model.

1 more element

Dependencies are inferred from the claim text.

Ultrasound image feature segmentation

Life of this patent

Ultrasound image feature segmentation

Life of this patent

Abstract

Claims20