Deep reconstruction model for dynamic PET images.
Accurate and robust tomographic reconstruction from dynamic positron emission tomography (PET) acquired data is a difficult problem. Conventional methods, such as the maximum likelihood expectation maximization (MLEM) algorithm for reconstructing the activity distribution-based on individual frames,...
Main Authors: | Jianan Cui, Xin Liu, Yile Wang, Huafeng Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2017-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC5608245?pdf=render |
Similar Items
-
Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging.
by: Xingjian Yu, et al.
Published: (2015-01-01) -
Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.
by: Xingjian Yu, et al.
Published: (2016-01-01) -
Robust framework for PET image reconstruction incorporating system and measurement uncertainties.
by: Huafeng Liu, et al.
Published: (2012-01-01) -
PET Statistical Models in Image Reconstruction
by: 高葵婷
Published: (2000) -
IMAGE RECONSTRUCTION IN PET
by: Richard Laforest
Published: (2015-08-01)