Ken Gin
Orcid: 0000-0001-6331-7003
According to our database1,
Ken Gin
authored at least 22 papers
between 2017 and 2021.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2021
IEEE Trans. Medical Imaging, 2021
Echo-Rhythm Net: Semi-Supervised Learning For Automatic Detection of Atrial Fibrillation in Echocardiography.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
2020
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment.
IEEE Trans. Medical Imaging, 2020
Automatic cine-based detection of patients at high risk of heart failure with reduced ejection fraction in echocardiograms.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020
Cardiac point-of-care to cart-based ultrasound translation using constrained CycleGAN.
Int. J. Comput. Assist. Radiol. Surg., 2020
2019
Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss.
IEEE Trans. Medical Imaging, 2019
Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training.
Int. J. Comput. Assist. Radiol. Surg., 2019
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
Echocardiography View Classification Using Quality Transfer Star Generative Adversarial Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Echocardiography Segmentation by Quality Translation Using Anatomically Constrained CycleGAN.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Frame Rate Up-Conversion in Echocardiography Using a Conditioned Variational Autoencoder and Generative Adversarial Model.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Dual-View Joint Estimation of Left Ventricular Ejection Fraction with Uncertainty Modelling in Echocardiograms.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Semi-Supervised Learning For Cardiac Left Ventricle Segmentation Using Conditional Deep Generative Models as Prior.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
2018
Quantitative Echocardiography: Real-Time Quality Estimation and View Classification Implemented on a Mobile Android Device.
Proceedings of the Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, 2018
A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018
Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018
2017
Simultaneous Analysis of 2D Echo Views for Left Atrial Segmentation and Disease Detection.
IEEE Trans. Medical Imaging, 2017
Correction to "Automatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View".
IEEE Trans. Medical Imaging, 2017
Automatic Quality Assessment of Echocardiograms Using Convolutional Neural Networks: Feasibility on the Apical Four-Chamber View.
IEEE Trans. Medical Imaging, 2017
Automatic quality assessment of apical four-chamber echocardiograms using deep convolutional neural networks.
Proceedings of the Medical Imaging 2017: Image Processing, 2017
Deep Residual Recurrent Neural Networks for Characterisation of Cardiac Cycle Phase from Echocardiograms.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017
Quality Assessment of Echocardiographic Cine Using Recurrent Neural Networks: Feasibility on Five Standard View Planes.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017