[HTML][HTML] The ultrasound use of simulators, current view, and perspectives: Requirements and technical aspects (WFUMB state of the art paper)

CF Dietrich, C Lucius, MB Nielsen… - Endoscopic …, 2023 - journals.lww.com
Simulation has been shown to improve clinical learning outcomes, speed up the learning
process and improve learner confidence, whilst initially taking pressure off busy clinical lists …

Deep learning in ultrasound elastography imaging: A review

H Li, M Bhatt, Z Qu, S Zhang, MC Hartel… - Medical …, 2022 - Wiley Online Library
It is known that changes in the mechanical properties of tissues are associated with the
onset and progression of certain diseases. Ultrasound elastography is a technique to …

Evaluating synthetic medical images using artificial intelligence with the GAN algorithm

AB Abdusalomov, R Nasimov, N Nasimova, B Muminov… - Sensors, 2023 - mdpi.com
In recent years, considerable work has been conducted on the development of synthetic
medical images, but there are no satisfactory methods for evaluating their medical suitability …

In silico simulation: a key enabling technology for next-generation intelligent surgical systems

BD Killeen, SM Cho, M Armand… - Progress in …, 2023 - iopscience.iop.org
To mitigate the challenges of operating through narrow incisions under image guidance,
there is a desire to develop intelligent systems that assist decision making and spatial …

Generative adversarial networks for DNA storage channel simulator

S Kang, Y Gao, J Jeong, SJ Park, JW Kim, JS No… - IEEE …, 2023 - ieeexplore.ieee.org
DNA data storage systems have rapidly developed with novel error-correcting techniques,
random access algorithms, and query systems. However, designing an algorithm for DNA …

Segmentation of breast ultrasound images using densely connected deep convolutional neural network and attention gates

N Thirusangu, M Almekkawy - 2021 IEEE UFFC Latin America …, 2021 - ieeexplore.ieee.org
Ultrasound imagining modality is a popular complementary technique for diagnosing breast
cancer. A standardized reporting process called Breast imaging reporting and data system …

An application of super-resolution generative adversary networks for quasi-static ultrasound strain elastography: A feasibility study

L He, B Peng, T Yang, J Jiang - IEEE Access, 2020 - ieeexplore.ieee.org
In this work, a super-resolution approach based on generative adversary network (GAN)
was used to interpolate (up-sample) ultrasound radio-frequency (RF) echo data along the …

Ultrasound image classification using ACGAN with small training dataset

S Saha, N Sheikh - Recent Trends in Signal and Image Processing: ISSIP …, 2021 - Springer
B-mode ultrasound imaging is a popular medical imaging technique. Like other image
processing tasks, deep learning has been used for analysis of B-mode ultrasound images in …

Radiomics Harmonization in Ultrasound Images for Cervical Cancer Lymph Node Metastasis Prediction Using Cycle-GAN

Z Zhao, Y Qin, K Shao, Y Liu, Y Zhang… - … in Cancer Research …, 2024 - journals.sagepub.com
Background: Ultrasound (US) based radiomics is susceptible to variations in scanners,
sonographers. Objective: To retrospectively investigate the feasibility of an adapted cycle …

WITHDRAWN: Advanced machine learning-based analytics on COVID-19 data using generative adversarial networks

A Harshavardhan, H Bhukya, AVK Prasad - 2020 - Elsevier
Withdrawal Notice WITHDRAWN: Advanced machine learning-based analytics on COVID-
19 data using generative adversarial networksJanga Vijay kumar a, â‡', A. Harshavardhan …