HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis

1 code implementation • 9 Mar 2022 • Xiaodan Xing, Javier Del Ser, Yinzhe Wu, Yang Li, Jun Xia, Lei Xu, David Firmin, Peter Gatehouse, Guang Yang

A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic medical signals without requiring to cope with the modelling complexity of anatomical and biochemical phenomena producing them in reality.

Decision Making Generative Adversarial Network +1

Synthetic Velocity Mapping Cardiac MRI Coupled with Automated Left Ventricle Segmentation

no code implementations • 4 Oct 2021 • Xiaodan Xing, Yinzhe Wu, David Firmin, Peter Gatehouse, Guang Yang

Temporal patterns of cardiac motion provide important information for cardiac disease diagnosis.

Left Ventricle Segmentation Myocardium Segmentation +1

Three-Dimensional Embedded Attentive RNN (3D-EAR) Segmentor for Left Ventricle Delineation from Myocardial Velocity Mapping

no code implementations • 26 Apr 2021 • Mengmeng Kuang, Yinzhe Wu, Diego Alonso-Álvarez, David Firmin, Jennifer Keegan, Peter Gatehouse, Guang Yang

Myocardial Velocity Mapping Cardiac MR (MVM-CMR) can be used to measure global and regional myocardial velocities with proved reproducibility.

Semantic Segmentation

Automated Multi-Channel Segmentation for the 4D Myocardial Velocity Mapping Cardiac MR

no code implementations • 16 Dec 2020 • Yinzhe Wu, Suzan Hatipoglu, Diego Alonso-Álvarez, Peter Gatehouse, David Firmin, Jennifer Keegan, Guang Yang

Based on the results, our method provides compelling evidence for the design and application for the multi-channel image analysis of the 4D MVM CMR data.