Dynamic recurrent inference machines for accelerated MRI-guided radiotherapy of the liver.

Accelerated dynamic MRI reconstruction Deep learning MR guided liver SBRT Recurrent inference machines

Journal

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
ISSN: 1879-0771
Titre abrégé: Comput Med Imaging Graph
Pays: United States
ID NLM: 8806104

Informations de publication

Date de publication:
08 Feb 2024
Historique:
received: 04 08 2023
revised: 10 01 2024
accepted: 01 02 2024
medline: 19 2 2024
pubmed: 19 2 2024
entrez: 18 2 2024
Statut: aheadofprint

Résumé

Recurrent inference machines (RIM), a deep learning model that learns an iterative scheme for reconstructing sparsely sampled MRI, has been shown able to perform well on accelerated 2D and 3D MRI scans, learn from small datasets and generalize well to unseen types of data. Here we propose the dynamic recurrent inference machine (DRIM) for reconstructing sparsely sampled 4D MRI by exploiting correlations between respiratory states. The DRIM was applied to a 4D protocol for MR-guided radiotherapy of liver lesions based on repetitive interleaved coronal 2D multi-slice T

Identifiants

pubmed: 38368665
pii: S0895-6111(24)00025-9
doi: 10.1016/j.compmedimag.2024.102348
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102348

Informations de copyright

Copyright © 2024 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jan-Jakob Sonke reports a relationship with Elekta AB that includes: funding grants. Jan-Jakob Sonke reports a relationship with Dutch Cancer Society that includes: funding grants. Jan-Jakob Sonke reports a relationship with Netherlands Enterprise Agency that includes: funding grants. Matthan W.A. Caan reports a relationship with Nicolab International Ltd. that includes: equity or stocks. Our department is a member of the Elekta ML Linac consortium. Our department received royalties for imaged radiotherapy software from Elekta AB.

Auteurs

Kai Lønning (K)

Netherlands Cancer Institute, Department of Radiotherapy, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands; Spinoza Centre for Neuroimaging, Meibergdreef 75, 1105 BK Amsterdam, The Netherlands.

Matthan W A Caan (MWA)

Amsterdam UMC location University of Amsterdam, Department of Biomedical Engineering and Physics, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.

Marlies E Nowee (ME)

Netherlands Cancer Institute, Department of Radiotherapy, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands.

Jan-Jakob Sonke (JJ)

Netherlands Cancer Institute, Department of Radiotherapy, Plesmanlaan 121, 1066 CX Amsterdam, The Netherlands. Electronic address: j.sonke@nki.nl.

Classifications MeSH