Distinction of lymphoma from sarcoidosis on 18F-FDG PET/CT: evaluation of radiomics-feature–guided machine learning versus human reader performance
P Lovinfosse, M Ferreira, N Withofs… - Journal of Nuclear …, 2022 - Soc Nuclear Med
Sarcoidosis and lymphoma often share common features on 18F-FDG PET/CT, such as
intense hypermetabolic lesions in lymph nodes and multiple organs. We aimed at …
intense hypermetabolic lesions in lymph nodes and multiple organs. We aimed at …
Deep convolutional neural network for differentiating between sarcoidosis and lymphoma based on [18F]FDG maximum-intensity projection images
H Aoki, Y Miyazaki, T Anzai, K Yokoyama… - European …, 2024 - Springer
Objectives To compare the [18F] FDG PET/CT findings of untreated sarcoidosis and
malignant lymphoma (ML) and develop convolutional neural network (CNN) models to …
malignant lymphoma (ML) and develop convolutional neural network (CNN) models to …
FDG PET/CT imaging of sarcoidosis
C Régis, K Benali, F Rouzet - Seminars in Nuclear Medicine, 2023 - Elsevier
Sarcoidosis is a multisystemic granulomatous disease of unknown etiology. The diagnostic
can be made by histological identification of non-caseous granuloma or by a combination of …
can be made by histological identification of non-caseous granuloma or by a combination of …
[HTML][HTML] Deep learning for [18F] fluorodeoxyglucose-PET-CT classification in patients with lymphoma: a dual-centre retrospective analysis
I Häggström, D Leithner, J Alvén… - The Lancet Digital …, 2024 - thelancet.com
Background The rising global cancer burden has led to an increasing demand for imaging
tests such as [18 F] fluorodeoxyglucose ([18 F] FDG)-PET-CT. To aid imaging specialists in …
tests such as [18 F] fluorodeoxyglucose ([18 F] FDG)-PET-CT. To aid imaging specialists in …
Machine learning in the differentiation of follicular lymphoma from diffuse large B-cell lymphoma with radiomic [18F]FDG PET/CT features
FM de Jesus, Y Yin, E Mantzorou-Kyriaki… - European Journal of …, 2022 - Springer
Background One of the challenges in the management of patients with follicular lymphoma
(FL) is the identification of individuals with histological transformation, most commonly into …
(FL) is the identification of individuals with histological transformation, most commonly into …
Optimal PET-based radiomic signature construction based on the cross-combination method for predicting the survival of patients with diffuse large B-cell lymphoma
C Jiang, A Li, Y Teng, X Huang, C Ding, J Chen… - European Journal of …, 2022 - Springer
Purpose To develop and externally validate models incorporating a PET radiomics signature
(R-signature) obtained by the cross-combination method for predicting the survival of …
(R-signature) obtained by the cross-combination method for predicting the survival of …
Convolutional neural networks for automated PET/CT detection of diseased lymph node burden in patients with lymphoma
AJ Weisman, MW Kieler, SB Perlman… - Radiology: Artificial …, 2020 - pubs.rsna.org
Purpose To automatically detect lymph nodes involved in lymphoma on fluorine 18 (18F)
fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs) …
fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs) …
[HTML][HTML] CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations
LJ Jensen, JMM Rogasch, D Kim, J Rießelmann… - Scientific Reports, 2022 - nature.com
Abstract 18F-FDG-PET/CT is standard to assess response in Hodgkin lymphoma by
quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming …
quantifying metabolic activity with the Deauville score. PET/CT, however, is time-consuming …
[HTML][HTML] Characterization of mediastinal bulky lymphomas with FDG-PET-based radiomics and machine learning techniques
EM Abenavoli, M Barbetti, F Linguanti, F Mungai… - Cancers, 2023 - mdpi.com
Simple Summary This manuscript aims to address the diagnostic challenges of mediastinal
bulky lymphomas with the baseline value of 18F-FDG PET/CT metabolic, volumetric and …
bulky lymphomas with the baseline value of 18F-FDG PET/CT metabolic, volumetric and …
Stacking Ensemble Learning–Based [18F] FDG PET Radiomics for Outcome Prediction in Diffuse Large B-Cell Lymphoma
This study aimed to develop an analytic approach based on [18F] FDG PET radiomics using
stacking ensemble learning to improve the outcome prediction in diffuse large B-cell …
stacking ensemble learning to improve the outcome prediction in diffuse large B-cell …
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