Outputs (2)

Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net. (2021)
Journal Article
REN, J., SUN, H., ZHAO, H., GAO, H., MACLELLAN, C., ZHAO, S. and LUO, X. 2022. Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net. Pattern recognition letters [online], 155, pages 165-170. Available from: https://doi.org/10.1016/j.patrec.2021.10.025

Accurate extraction of semantic objects such as ventricles and myocardium from magnetic resonance (MR) images is one essential but very challenging task for the diagnosis of the cardiac diseases. To tackle this problem, in this paper, an automatic en... Read More about Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net..

A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. (2021)
Journal Article
FANG, Z., REN, J., MACLELLAN, C., LI, H., ZHOA, H., HUSSAIN, A. and FORTINO, G. 2022. A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. IEEE transactions on molecular, biological and multi-scale communications [online], 8(1), pages 17-27. Available from: https://doi.org/10.1109/tmbmc.2021.3099367

To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due... Read More about A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images..