arXiv · 1705.08236
3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures
Abstract
This paper analyzes the use of 3D Convolutional Neural Networks for brain tumor segmentation in MR images. We address the problem using three different architectures that combine fine and coarse features to obtain the final segmentation. We compare three different networks that use multi-resolution features in terms of both design and performance and we show that they improve their single-resolution counterparts.
Explore related subjects
Keep this discovery
Adrià Casamitjana, Santi Puch, Asier Aduriz, Verónica Vilaplana. 2017-05-23. 3D Convolutional Neural Networks for Brain Tumor Segmentation: A Comparison of Multi-resolution Architectures. https://arxiv.org/abs/1705.08236
Cite the original work for its findings. Save a collection to share your selection of sources.