End-to-End Model-Based Deep Learning for Dual-Energy Computed Tomography Material Decomposition
Author:
Affiliation:
1. Shenzhen Xilaiheng Medical Electronics Co, Ltd.,HORRON,China
2. Centre for Medical Engineering and Technology, University of Dundee,United Kingdom,DD1 4HN
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635736.pdf?arnumber=10635736
Reference18 articles.
1. Report on the AAPM deep‐learning spectral CT Grand Challenge
2. A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images
3. Material differentiation by dual energy CT: initial experience
4. Image-based dual energy CT using optimized precorrection functions: A practical new approach of material decomposition in image domain
5. Material decomposition from photon-counting CT using a convolutional neural network and energy-integrating CT training labels
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