Sensitivity of an AI method for [18F]FDG PET/CT outcome prediction of diffuse large B-cell lymphoma patients to image reconstruction protocols

Sensitivity of an AI method for [18F]FDG PET/CT outcome prediction of diffuse large B-cell lymphoma patients to image reconstruction protocols

Abstract Background Convolutional neural networks (CNNs), applied to baseline [18F]-FDG PET/CT maximum intensity projections (MIPs), show potential for treatment outcome prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study is to investigate the robustness of CNN predictions to...

Full description

Bibliographic Details
Main Authors: Maria C. Ferrández, Sandeep S. V. Golla, Jakoba J. Eertink, Bart M. de Vries, Sanne E. Wiegers, Gerben J. C. Zwezerijnen, Simone Pieplenbosch, Louise Schilder, Martijn W. Heymans, Josée M. Zijlstra, Ronald Boellaard
Format: Article
Language:English
Published: SpringerOpen 2023-09-01
Series:EJNMMI Research
Subjects:
Diffuse large B-cell lymphoma
PET
Convolutional neural networks
Reconstruction
Online Access:https://doi.org/10.1186/s13550-023-01036-8

Internet

https://doi.org/10.1186/s13550-023-01036-8

Similar Items