A direct PCA-based approach for real-time description of physiological organ deformations - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Medical Imaging Année : 2015

A direct PCA-based approach for real-time description of physiological organ deformations

Résumé

Dynamic MR-imaging can provide functional and positional information in real-time, which can be conveniently used on-line 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 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.
Fichier principal
Vignette du fichier
2015_TMI_PCA.pdf (651.6 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01083281 , version 1 (17-11-2014)

Identifiants

Citer

Baudouin Denis de Senneville, Abdallah El Hamidi, Chrit Moonen. A direct PCA-based approach for real-time description of physiological organ deformations. IEEE Transactions on Medical Imaging, 2015, 34 (4), pp.974-982. ⟨10.1109/TMI.2014.2371995⟩. ⟨hal-01083281⟩
66 Consultations
140 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More