Self-supervised learning for accelerated 3D high-resolution ultrasound imaging
Abstract
Purpose null Ultrasound (US) imaging has been widely used in diagnosis, image-guided intervention and therapy, where high-quality three-dimensional (3D) images are highly desired from sparsely acquired two-dimensional (2D) images. This study aims to develop a deep learning-based algorithm to reconstruct high-resolution 3D US images only reliant on the acquired sparsely distributed 2D images. null Methods null We propose a self-supervised...
Paper Details
Title
Self-supervised learning for accelerated 3D high-resolution ultrasound imaging
Published Date
Jul 1, 2021
Journal
Volume
48
Issue
7
Pages
3916 - 3926
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