352 citations · 352 across the 1 of their papers we have counts for
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MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning
Xiangde Luo, Guotai Wang, Tao Song +6
Segmentation of organs or lesions from medical images plays an essential role in many clinical applications such as diagnosis and treatment planning. Though Convolutional Neural Ne…
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation
Guotai Wang, Wenqi Li, Sebastien Ourselin +1
Automatic brain tumor segmentation plays an important role for diagnosis, surgical planning and treatment assessment of brain tumors. Deep convolutional neural networks (CNNs) have…
Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration
Yipeng Hu, Marc Modat, Eli Gibson +11
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a…
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Guotai Wang, Wenqi Li, Michael Aertsen +3
Despite the state-of-the-art performance for medical image segmentation, deep convolutional neural networks (CNNs) have rarely provided uncertainty estimations regarding their segm…
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task
Wenqi Li, Guotai Wang, Lucas Fidon +3
Deep convolutional neural networks are powerful tools for learning visual representations from images. However, designing efficient deep architectures to analyse volumetric medical…