A novel approach to motion correction for ASL images based on brain contours

Giacomo Tarroni; Marco Castellaro; Carlo Boffano; Maria Grazia Bruzzone; Alessandra Bertoldo; Enrico Grisan

doi:10.1117/12.2081784

17 March 2015 A novel approach to motion correction for ASL images based on brain contours

Giacomo Tarroni, Marco Castellaro, Carlo Boffano, Maria Grazia Bruzzone, Alessandra Bertoldo, Enrico Grisan

Proceedings Volume 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging; 94171U (2015) https://doi.org/10.1117/12.2081784
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

Motion correction in Arterial Spin Labeling (ASL) is essential to accurately assess brain perfusion. Motion correction techniques are usually based on intensity-related information, which might be unreliable in ASL due to local intensity differences between control and labeled acquisitions and to non-uniform volume magnetization caused by background-suppressed acquisition protocols. Accordingly, a novel motion correction technique based only on brain contour points is presented and tested against a widely used intensity-based technique (MCFLIRT). The proposed Contour-Based Motion Correction (CBCM) technique relies on image segmentation (to extract brain contour point clouds) and on Iterative Closest Point algorithm (to estimate the roto-translation required to align them). At variance with other approaches based on point clouds alignment, the local 3D curvature is also computed for each contour point and used as an additional coordinate to increase the accuracy of the alignment. The technique has been tested along with MCFLIRT on a database of randomly roto-translated brain volumes. Several error metrics have been computed and compared between the two techniques. The results show that the proposed technique is able to achieve a higher accuracy than MCFLIRT without any intensity-dependent information.

Citation Download Citation

Giacomo Tarroni, Marco Castellaro, Carlo Boffano, Maria Grazia Bruzzone, Alessandra Bertoldo, and Enrico Grisan "A novel approach to motion correction for ASL images based on brain contours", Proc. SPIE 9417, Medical Imaging 2015: Biomedical Applications in Molecular, Structural, and Functional Imaging, 94171U (17 March 2015); https://doi.org/10.1117/12.2081784

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KEYWORDS

Brain

Clouds

Image segmentation

Neuroimaging

Image processing algorithms and systems

Databases

Magnetic resonance imaging

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