Titlebook: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; Second International Alessandro Crimi,Bjoern Menze,Heinz Hand

背心

Flinch

兩種語言

Giuseppe Fontana,Mark Setterfieldtion. However, most of existing brain tumor segmentation methods based on deep learning are not able to ensure appearance and spatial consistency of segmentation results. In this study we propose a novel brain tumor segmentation method by integrating a Fully Convolutional Neural Network (FCNN) and C

枯燥

BLAZE

aggressor

Charles L. Weise,Robert J. Barbera employed here in the setting of brain tumors. Inspired by deep residual networks which won the ImageNet ILSVRC 2015 classification challenge, the FCR-NN combines optimization gains from residual identity mappings with a fully convolutional architecture for image segmentation that efficiently accoun

增長

Eckhard Hein,Engelbert Stockhammera fully-convolutional network for local features and an encoder-decoder network in which convolutional layers and maxpooling compute high-level features, which are then upsampled to the resolution of the initial image using further convolutional layers and tied unpooling. We apply the method to segm

無價值

性滿足

大喘氣

Anatoliy Peresetsky,Vladimir Popovt 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.