A Deep Texture Metric for PET Image Quantification and Image Synthesis-Reference-Cited by-同舟云学术

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A Deep Texture Metric for PET Image Quantification and Image Synthesis

Published:2023-11-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD)
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Author:

Smith R. L.¹,John R. R.²,Ackerley I.²,Al-Battat K.¹,Alsyed E.³,Spezi E.⁴,Wells K.²,Morley N.¹,Marshall C.¹

Affiliation:

1. Cardiff University,Wales Research and Diagnostic PET Imaging Centre (PETIC),Cardiff,United Kingdom

2. University of Surrey, Centre for Vision Speech & Signal Processing, University of Surrey, Guildford,Guildford,United Kingdom

3. King Abdulaziz University,Faculty of Engineering,Department of Nuclear Engineering,Jeddah,Saudi Arabia

4. Cardiff University,School of Engineering,Cardiff,United Kingdom

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10337770/10337807/10338021.pdf?arnumber=10338021

Reference5 articles.

1. Using deep machine learning to detect esophageal lesions in PET-CT scans

2. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes

3. Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future

4. Texture synthesis using convolutional neural networks;Gatys

5. A heterogeneous phantom study for investigating the stability of PET images radiomic features with varying reconstruction settings

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