Evaluation of deep learning based PET image enhancement method in diagnosis of Lymphoma
431 Purpose: This study aims to evaluate the performance of deep learning enhancement
(SubtlePET) method on low dose PET images from both quantitative and qualitative …
(SubtlePET) method on low dose PET images from both quantitative and qualitative …
Performance of a deep learning enhancement method applied to PET images acquired with a reduced acquisition time
K Ciborowski, A Gramek-Jedwabna… - Nuclear Medicine …, 2023 - journals.viamedica.pl
Background: This study aims to evaluate the performance of a deep learning enhancement
method in PET images reconstructed with a shorter acquisition time, and different …
method in PET images reconstructed with a shorter acquisition time, and different …
[HTML][HTML] Image enhancement of whole-body oncology [18F]-FDG PET scans using deep neural networks to reduce noise
A Mehranian, SD Wollenweber, MD Walker… - European journal of …, 2022 - Springer
Purpose To enhance the image quality of oncology [18F]-FDG PET scans acquired in
shorter times and reconstructed by faster algorithms using deep neural networks. Methods …
shorter times and reconstructed by faster algorithms using deep neural networks. Methods …
[HTML][HTML] Low 18F-fluorodeoxyglucose dose positron emission tomography assisted by a deep-learning image-denoising technique in patients with lymphoma
L Yan, Z Wang, D Li, Y Wang, G Yang… - … Imaging in Medicine …, 2024 - ncbi.nlm.nih.gov
Background Patients with lymphoma receive multiple positron emission
tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic …
tomography/computed tomography (PET/CT) exams for monitoring of the therapeutic …
Clinical Evaluation of Deep Learning for Improving PET Image Quality
J Schaefferkoetter, A Sertic, E Lechtman… - 2020 - Soc Nuclear Med
1465 Background: Positron emission tomography (PET) is a noisy process. This becomes
even more problematic in low-count situations which might be encountered in the medical …
even more problematic in low-count situations which might be encountered in the medical …
[PDF][PDF] Usefulness of non attenuation corrected 18F-FDG-PET images for optimal assessment of disease activity in patients with lymphoma
M Houseni, W Chamroonrat, S Basu, G Bural, A Mavi… - Hell J Nucl …, 2009 - nuclmed.gr
This study aimed at determining whether non attenuation corrected (NAC) positron emission
tomography (PET) images, in addition to the attenuation corrected (AC) PET images, should …
tomography (PET) images, in addition to the attenuation corrected (AC) PET images, should …
[HTML][HTML] Deep learning-assisted PET imaging achieves fast scan/low-dose examination
Y Xing, W Qiao, T Wang, Y Wang, C Li, Y Lv, C Xi… - EJNMMI physics, 2022 - Springer
Purpose This study aimed to investigate the impact of a deep learning (DL)-based denoising
method on the image quality and lesion detectability of 18F-FDG positron emission …
method on the image quality and lesion detectability of 18F-FDG positron emission …
Clinical potential for artificial intelligence in PET imaging: phase 1 result of dose reduction using deep learning reconstruction
M Vangu, K Purbhoo, H Liu - 2021 - Soc Nuclear Med
1179 Objectives: Positron emission tomography/computed tomography (PET/CT) plays a
central role in the management of cancer. However, the radiation exposure to patients from …
central role in the management of cancer. However, the radiation exposure to patients from …
[HTML][HTML] Comparative study of the quantitative accuracy of oncological PET imaging based on deep learning methods
Y Hu, D Lv, S Jian, L Lang, C Cui, M Liang… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background [18 F] Fluorodeoxyglucose (FDG) positron emission tomography/computed
tomography (PET/CT) is an important tool for tumor assessment. Shortening scanning time …
tomography (PET/CT) is an important tool for tumor assessment. Shortening scanning time …
[HTML][HTML] Deep learning–based time-of-flight (ToF) image enhancement of non-ToF PET scans
A Mehranian, SD Wollenweber, MD Walker… - European Journal of …, 2022 - Springer
Purpose To improve the quantitative accuracy and diagnostic confidence of PET images
reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image …
reconstructed without time-of-flight (ToF) using deep learning models trained for ToF image …