DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem

Ida Häggström(Memorial Sloan Kettering Cancer Center), C. Ross Schmidtlein(Memorial Sloan Kettering Cancer Center), Gabriele Campanella(Memorial Sloan Kettering Cancer Center), Thomas J. Fuchs(Memorial Sloan Kettering Cancer Center)
Medical Image Analysis
March 30, 2019
10.1016/j.media.2019.03.013
Cited by 312Open Access
Full Text

Abstract

Related Papers

Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan, Andrew Zisserman|arXiv (Cornell University)|2014|75.5k
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh et al.|IEEE Transactions on Image Processing|2004|55.7k
Deep Convolutional Neural Network for Inverse Problems in Imaging
Kyong Hwan Jin, Michael T. McCann, Emmanuel Froustey et al.|IEEE Transactions on Image Processing|2017|2.5k
GATE: a simulation toolkit for PET and SPECT
S Jan, G. Santin, D. Strul et al.|Physics in Medicine and Biology|2004|2.1k
Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
Hu Chen, Yi Zhang, Mannudeep K. Kalra et al.|IEEE Transactions on Medical Imaging|2017|1.8k