Title :
A Direct PCA-Based Approach for Real-Time Description of Physiological Organ Deformations
Author :
de Senneville, Baudouin Denis ; El Hamidi, Abdallah ; Moonen, Chrit
Author_Institution :
Imaging Div., UMC Utrecht, Utrecht, Netherlands
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.
Keywords :
biological organs; biomedical MRI; cancer; cardiology; motion estimation; pneumodynamics; principal component analysis; spatiotemporal phenomena; MR imaging; PCA-based technique; abdominal organ motion estimation; breathing cycle; cancer therapy; cardiac cycle; coarse-to-fine resolution scheme; dynamic magnetic resonance imaging; optimal treatment dose; periodic organ motion detection; physiological organ deformation; principal component analysis; real-time description; Kidney; Liver; Minimization; Motion estimation; Physiology; Principal component analysis; Real-time systems; Motion analysis; real-time system;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2014.2371995