VNC-Net architecture.

VNC-Net architecture.

<p>The model takes contrast enhanced dual-energy CT (CE DECT) images as input and generates virtual non-contrast (VNC) images as output. The numbers denoted below the encoder/decoder blocks represent the number of channels. The bottom of the figure depicts the structure of the down-sampling bl...

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Bibliographic Details
Main Author: Jungye Kim (20485427) (author)
Other Authors: Jimin Lee (2552782) (author), Bitbyeol Kim (17020584) (author), Sangwook Kim (2235727) (author), Hyeongmin Jin (20485430) (author), Seongmoon Jung (9310778) (author)
Published: 2024
Subjects:
Neuroscience
Physiology
Biotechnology
Science Policy
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Chemical Sciences not elsewhere classified
Information Systems not elsewhere classified
unlike previous studies
showing close correspondence
demonstrating high scores
deep learning models
generating virtual non
deep learning model
improve imaging protocols
maintaining ct numbers
using virtual non
radiotherapy </ p
pseudo dect images
model &# 8217
contrast planning ct
overall good performance
enhanced planning ct
contrast ct images
radiotherapy planning
&# 8217
planning ct
ct numbers
contrast ct
scans using
energy ct
true non
model training
images validated
contrast agent
vnc ct
xlink ">
ten left
study highlights
quantitative performance
quantitative comparison
paper presents
outputs instead
limitations remained
future research
dose calculations
deterministic method
clinical relevance
45 patients
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