Anatomically Consistent Segmentation of Organs at Risk in MRI with Convolutional Neural Networks

no code implementations • 3 Jul 2019 • Pawel Mlynarski, Hervé Delingette, Hamza Alghamdi, Pierre-Yves Bondiau, Nicholas Ayache

We report cross-validated quantitative results on a database of 44 contrast-enhanced T1-weighted MRIs with provided segmentations of the considered organs at risk, which were originally used for radiotherapy planning.

Hippocampus Segmentation

Deep Learning with Mixed Supervision for Brain Tumor Segmentation

no code implementations • 10 Dec 2018 • Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

In this paper, we propose to use both types of training data (fully-annotated and weakly-annotated) to train a deep learning model for segmentation.

Brain Tumor Segmentation General Classification +2

3D Convolutional Neural Networks for Tumor Segmentation using Long-range 2D Context

no code implementations • 23 Jul 2018 • Pawel Mlynarski, Hervé Delingette, Antonio Criminisi, Nicholas Ayache

Furthermore, we propose a network architecture in which the different MR sequences are processed by separate subnetworks in order to be more robust to the problem of missing MR sequences.

Segmentation Tumor Segmentation