Abstract
Quantitative Magnetic Resonance Imaging (qMRI) is backed by extensive validation in research literature but has seen limited use in clinical practice because of long acquisition times, lack of standardization and no statistical models for analysis. Our research focuses on developing a novel quasi-intermodal 2D slice to 3D volumetric pipeline for an emerging qMR technology that aims to bridge the gap between research and practice. The two-part method first initializes the registration using a 3D reconstruction technique then refines it using a 3D to 2D projection technique. Intermediate results promise feasibility and efficacy of our proposed method.
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Appendix
Appendix
Typical SFS reconstruction procedure as illustrated in [6] (a) Camera captures a silhouette (b) The silhouette defines a visual cone. (c) The intersection of two visual cones contains an object. (d) A visual hull of an object is the intersection of many visual cones
Actual appearance of the six 2D qMR scans acquired from a volunteer
Expected appearance of the six 2D qMR scans
The image on the far right depicts the localizer plane and so it is unchanging in both sets of emulations. The images on the center and left are captured using two planes orthogonal to the localizer plane and to each other. The initial locations of these planes was chosen arbitrarily but kept constant in both this and Fig. 7. This set produced via rotation by 90\(^{\circ }\) clockwise
The image on the far right depicts the localizer plane and so it is unchanging in both sets of emulations. The images on the center and left are captured using two planes orthogonal to the localizer plane and to each other. The initial locations of these planes was chosen arbitrarily but kept constant in both this and Fig. 6. This set produced via rotation by 45\(^{\circ }\) counter-clockwise
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Abbas, B., Lattanzi, R., Petchprapa, C., Gerig, G. (2022). 2D/3D Quasi-Intramodal Registration of Quantitative Magnetic Resonance Images. In: Hering, A., Schnabel, J., Zhang, M., Ferrante, E., Heinrich, M., Rueckert, D. (eds) Biomedical Image Registration. WBIR 2022. Lecture Notes in Computer Science, vol 13386. Springer, Cham. https://doi.org/10.1007/978-3-031-11203-4_23
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