3.6k citations · 5.7k across the 34 of their papers we have counts for
4 papers · 2 filters
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Konstantinos Kamnitsas, Wenjia Bai, Enzo Ferrante +8
Deep learning approaches such as convolutional neural nets have consistently outperformed previous methods on challenging tasks such as dense, semantic segmentation. However, the v…
Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation
Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas +10
Incorporation of prior knowledge about organ shape and location is key to improve performance of image analysis approaches. In particular, priors can be useful in cases where image…
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging
Steven McDonagh, Benjamin Hou, Konstantinos Kamnitsas +5
3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast but low-resolution image acquisition and highly detailed but slow image acquisition. Fast imaging is required…
Reverse Classification Accuracy: Predicting Segmentation Performance in the Absence of Ground Truth
Vanya V. Valindria, Ioannis Lavdas, Wenjia Bai +5
When integrating computational tools such as automatic segmentation into clinical practice, it is of utmost importance to be able to assess the level of accuracy on new data, and i…