6 citations · 7 across the 6 of their papers we have counts for
6 papers
Implicit Neural Representations for Speed-of-Sound Estimation in Ultrasound
Michal Byra, Piotr Jarosik, Piotr Karwat +2
Accurate estimation of the speed-of-sound (SoS) is important for ultrasound (US) image reconstruction techniques and tissue characterization. Various approaches have been proposed…
Parameter estimation of the homodyned K distribution based on neural networks and trainable fractional-order moments
Michal Byra, Ziemowit Klimonda, Piotr Jarosik
Homodyned K (HK) distribution has been widely used to describe the scattering phenomena arising in various research fields, such as ultrasound imaging or optics. In this work, we p…
Estimating the ultrasound attenuation coefficient using convolutional neural networks -- a feasibility study
Piotr Jarosik, Michal Byra, Marcin Lewandowski +1
Attenuation coefficient (AC) is a fundamental measure of tissue acoustical properties, which can be used in medical diagnostics. In this work, we investigate the feasibility of usi…
Breast mass segmentation based on ultrasonic entropy maps and attention gated U-Net
Michal Byra, Piotr Jarosik, Katarzyna Dobruch-Sobczak +4
We propose a novel deep learning based approach to breast mass segmentation in ultrasound (US) imaging. In comparison to commonly applied segmentation methods, which use US images,…
WaveFlow - Towards Integration of Ultrasound Processing with Deep Learning
Piotr Jarosik, Michał Byra, Marcin Lewandowski
The ultimate goal of this work is a real-time processing framework for ultrasound image reconstruction augmented with machine learning. To attain this, we have implemented WaveFlow…
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments
Łukasz Kidziński, Sharada Prasanna Mohanty, Carmichael Ong +26
In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle c…