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A Direct PCA-Based Approach for Real-Time Description of Physiological Organ Deformations

Authors :
Chrit T. W. Moonen
Baudouin Denis de Senneville
Abdallah El Hamidi
Institut de Mathématiques de Bordeaux (IMB)
Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)
Laboratoire des Sciences de l'Ingénieur pour l'Environnement - UMR 7356 (LaSIE)
Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)
Imaging Division
University Medical Center [Utrecht]
Source :
IEEE Transactions on Medical Imaging, 34(4), 974. Institute of Electrical and Electronics Engineers Inc., IEEE Transactions on Medical Imaging, IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2015, 34 (4), pp.974-982. ⟨10.1109/TMI.2014.2371995⟩
Publication Year :
2015

Abstract

Dynamic magnetic resonance (MR)-imaging can provide functional and positional information in real-time, which can be conveniently used online to control a cancer therapy, e. g., using high intensity focused ultrasound or radio therapy. However, a precise real-time correction for motion is fundamental in abdominal organs to ensure an optimal treatment dose associated with a limited toxicity in nearby organs at risk. This paper proposes a real-time direct principal component analysis (PCA)-based technique which offers a robust approach for motion estimation of abdominal organs and allows correcting motion related artifacts. The PCA was used to detect spatio-temporal coherences of the periodic organ motion in a learning step. During the interventional procedure, physiological contributions were characterized quantitatively using a small set of parameters. A coarse-to-fine resolution scheme is proposed to improve the stability of the algorithm and afford a predictable constant latency of 80 ms. The technique was evaluated on 12 free-breathing volunteers and provided an improved real-time description of motion related to both breathing and cardiac cycles. A reduced learning step of 10 s was sufficient without any need for patient-specific control parameters, rendering the method suitable for clinical use.

Details

Language :
English
ISSN :
02780062
Database :
OpenAIRE
Journal :
IEEE Transactions on Medical Imaging, 34(4), 974. Institute of Electrical and Electronics Engineers Inc., IEEE Transactions on Medical Imaging, IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2015, 34 (4), pp.974-982. ⟨10.1109/TMI.2014.2371995⟩
Accession number :
edsair.doi.dedup.....86fb319f1204695ed2a805620e60a2d9