Controllable Quality Improvement of Mobile Ultrasound

Haoming Chen, Yuqi Guo, Yue Sun, Xiang Li, Hongping Song, Tao Tan

研究成果: Conference contribution同行評審

摘要

Mobile ultrasound imaging, widely used in clinical diagnosis due to its non-invasive, convenient, and rapid characteristics, faces challenges such as low image contrast, various artifacts, and noise interference, demanding high clinical experience from physicians. Utilizing image super-resolution technology to enhance ultrasound image quality holds significant clinical importance. Unlike natural scene images, ultrasound images lack paired high and low-resolution datasets, making the reconstruction task more challenging. This paper conducts an in-depth study on the super-resolution reconstruction of ultrasound images using Generative Adversarial Networks (GANs). It performs extensive experiments on a dataset accumulated at the Hospital, achieving favorable results. The main contributions of this paper are as follows: 1) Optimizing the CycleGAN network's generator with hyperparameter convolution kernels to extract multiscale features from input images and train them in combination with hyper-parameters. The super-resolution (SR) images at different scales are reconstructed by a decoder controlled by hyperparameter prompts. 2) Employing both paired simulated and unpaired clinical ultrasound images and natural images to train a super-resolution model that acquires ultrasound-specific features based on natural cognition. 3) Various random damage techniques are applied by employing dynamic random image damage methods such as Gaussian, grid, mosaic, directional, etc. These damage methods can simulate low-resolution when imaging with a mobile ultrasound device based on a limited unpaired dataset, providing many paired samples.

原文English
主出版物標題2024 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350307993
DOIs
出版狀態Published - 2024
事件2024 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024 - Eindhoven, Netherlands
持續時間: 26 6月 202428 6月 2024

出版系列

名字2024 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024 - Proceedings

Conference

Conference2024 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2024
國家/地區Netherlands
城市Eindhoven
期間26/06/2428/06/24

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