학술논문
GAN-Based Ultrasound Localization Microscopy
Document Type
Conference
Author
Source
2022 IEEE International Ultrasonics Symposium (IUS) Ultrasonics Symposium (IUS), 2022 IEEE International. :1-4 Oct, 2022
Subject
Language
ISSN
1948-5727
Abstract
Ultrasound localization microscopy (ULM) breaks the acoustics diffraction limit and allows the imaging of the microvasculature within organs and tumors at sub-wavelength resolution while maintaining the imaging penetration. However, the reconstruction quality of localization-based methods highly depends on sufficient ultrasound data frames with sparsely distributed microbubbles (MBs) in each frame which results in great data storage burden and low processing speed. Here, we proposed a novel method based on generative adversarial networks (GANs) to implement the MB localization in ULM imaging to accelerate the data processing speed. The synthetic results indicate that the proposed method performs well in MB localization task with great robustness to overlapping MBs and achieves higher localization speed once the network be well trained.