Search Results for author:
Found 8 papers, 1 papers with code
Diffeomorphic Spatial Transformer Networks
In this paper we propose a spatial transformer network where the spatial transformations are limited to the group of diffeomorphisms.
Inferring a Third Spatial Dimension from 2D Histological Images
Histological images are obtained by transmitting light through a tissue specimen that has been stained in order to produce contrast.
Isointense infant brain MRI segmentation with a dilated convolutional neural network
Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter.
Domain-adversarial neural networks to address the appearance variability of histopathology images
Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters.
Adversarial training and dilated convolutions for brain MRI segmentation
To this end, we include an additional loss function that motivates the network to generate segmentations that are difficult to distinguish from manual segmentations.
Exploring the similarity of medical imaging classification problems
Supervised learning is ubiquitous in medical image analysis.
Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities
The CNN therefore learns to identify the imaging modality, the visualised anatomical structures, and the tissue classes.
Automatic segmentation of MR brain images with a convolutional neural network
Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages.
