Back to search

Article

Accuracy of deep learning-based attenuation correction in 99mTc-GSA SPECT/CT hepatic imaging

2024-05-07

Abstract excerpt

<title>Abstract</title> <p>Objective The aim of this study was to generate pseudo CT images for attenuation correction (AC) from non-AC SPECT images and evaluate the accuracy of deep learning-based AC in <sup>99m</sup>Tc-labeled galactosyl human serum albumin (<sup>99m</sup>Tc-GSA) SPECT/CT hepatic imaging. Methods A cycle-consistent generative network (CycleGAN) was used to generate pseudo CT images of 40 pati...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
3d16fbdc-5623-5ce5-92c7-be6520f049f2
DOI
10.21203/rs.3.rs-4179083/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Accuracy of deep learning-based attenuation correction in 99mTc-GSA SPECT/CT hepatic imagingDOI 10.21203/rs.3.rs-4179083/v1
Select a neighboring publication to make it the new centre.