Recommender-based bone tumour classification with radiographs—a link to the past
Florian Hinterwimmer(TUM Klinikum), Daniel Rueckert(Munich Center for Machine Learning), Jan Neumann(TUM Klinikum), Rüdiger von Eisenhart‐Rothe(TUM Klinikum), Klaus Woertler(National Center for Tumor Diseases), Dominik Juestel(Helmholtz Zentrum München), Rainer Burgkart(TUM Klinikum), Nikolas Wilhelm(TUM Klinikum), Ricardo Smits Serena(TUM Klinikum), Fritz Seidl(Helmholtz Zentrum München), Sebastian Breden(TUM Klinikum), Sarah Consalvo(TUM Klinikum)
Cited by 9
Related Papers
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
|Unknown|2016|7.1k
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
|NeuroImage|2006|6.6k
Nonrigid registration using free-form deformations: application to breast MR images
|IEEE Transactions on Medical Imaging|1999|5.3k
Attention U-Net: Learning Where to Look for the Pancreas
|arXiv (Cornell University)|2018|4.6k
Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
|Medical Image Analysis|2016|3.5k