Labelling with dynamics: A data-efficient learning paradigm for medical image segmentation.
Medical Image Anal., 2024
Densely connected GCN model for motion prediction.
Comput. Animat. Virtual Worlds, 2020
DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.
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IEEE Trans. Medical Imaging, 2018
The Deep Poincaré Map: A Novel Approach for Left Ventricle Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Deep De-Aliasing for Fast Compressive Sensing MRI.
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CoRR, 2017
Deep Poincare Map For Robust Medical Image Segmentation.
CoRR, 2017
TensorLayer: A Versatile Library for Efficient Deep Learning Development.
Proceedings of the 2017 ACM on Multimedia Conference, 2017
Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks.
Proceedings of the Medical Image Understanding and Analysis - 21st Annual Conference, 2017
Fast and Adaptive Fractal Tree-Based Path Planning for Programmable Bevel Tip Steerable Needles.
IEEE Robotics Autom. Lett., 2016
Parallel moduli space sampling: Robust and fast surgery planning for image guided steerable needles.
Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics, 2015
Smooth on-line path planning for needle steering with non-linear constraints.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015
Motion Adaptation With Motor Invariant Theory.
IEEE Trans. Cybern., 2013
Deformation-as-control for a biologically inspired steerable needle.
Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2013
Adaptive motion synthesis and motor invariant theory.
PhD thesis, 2012
A biologically inspired latent space for gait parameterization.
Proceedings of the International Conference on Computer Graphics and Interactive Techniques, 2012