63 citations · 150 across the 7 of their papers we have counts for
10 papers · 1 filter
Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation
Dong Yang, Holger Roth, Ziyue Xu +3
Deep neural network (DNN) based approaches have been widely investigated and deployed in medical image analysis. For example, fully convolutional neural networks (FCN) achieve the…
NeurReg: Neural Registration and Its Application to Image Segmentation
Wentao Zhu, Andriy Myronenko, Ziyue Xu +5
Registration is a fundamental task in medical image analysis which can be applied to several tasks including image segmentation, intra-operative tracking, multi-modal image alignme…
Weakly supervised segmentation from extreme points
Holger Roth, Ling Zhang, Dong Yang +4
Annotation of medical images has been a major bottleneck for the development of accurate and robust machine learning models. Annotation is costly and time-consuming and typically r…
Privacy-preserving Federated Brain Tumour Segmentation
Wenqi Li, Fausto Milletarì, Daguang Xu +8
Due to medical data privacy regulations, it is often infeasible to collect and share patient data in a centralised data lake. This poses challenges for training machine learning al…
Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin +5
Radiogenomic map linking image features and gene expression profiles is useful for noninvasively identifying molecular properties of a particular type of disease. Conventionally, s…
Interactive segmentation of medical images through fully convolutional neural networks
Tomas Sakinis, Fausto Milletari, Holger Roth +7
Image segmentation plays an essential role in medicine for both diagnostic and interventional tasks. Segmentation approaches are either manual, semi-automated or fully-automated. M…