By Peter J. Schüffler, Dwarikanath Mahapatra, Jeroen A. W. Tielbeek, Franciscus M. Vos (auth.), Hiroyuki Yoshida, Simon Warfield, Michael W. Vannier (eds.)
This publication constitutes the refereed complaints of the fifth foreign Workshop CCAA 2013, held at the side of MICCAI 2013, in Nagoya, Japan, in September 2013. The ebook comprises 32 papers which have been conscientiously reviewed and chosen from 38 submissions. the themes coated are belly atlases, form research and morphology in belly buildings and organs, detection of anatomical and practical landmarks, dynamic, sensible, physiologic, and anatomical stomach imaging, registration tools for stomach intra- and inter-patient variability, augmented fact options for intervention, scientific purposes in radio-frequency ablation, open surgical procedure, and minimally invasive surgery.
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Additional resources for Abdominal Imaging. Computation and Clinical Applications: 5th International Workshop, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings
J. Magn. Reson. 23781 13. : Reliable estimation of incoherent motion parametric maps from diﬀusion-weighted MRI using fusion bootstrap moves. Med. Image Anal. 001 14. : Reliable Assessment of Perfusivity and Diﬀusivity from Diﬀusion Imaging of the Body. , Mori, K. ) MICCAI 2012, Part I. LNCS, vol. 7510, pp. 1–9. Springer, Heidelberg (2012) 15. : Inﬂuence of multichannel combination, parallel imaging and other reconstruction techniques on MRI noise characteristics. Magn. Reson. Imaging 26(6), 754–762 (2008) 16.
Keywords: Image registration, hessian reorientation, Crohn’s disease. 1 Introduction Medical image registration is widely used for ﬁnding correspondence between images. Sum of square diﬀerences (SSD) and normalized cross covariance (NCC) are often applied for registering images from the same modality. Alternatively, mutual information (MI) is frequently used to deal with multi-modal image registration problems [1–3]. The above, basic similarity metrics are based on global measurements and in principle do not model spatial variance.
The sum-of-squared diﬀerences (SSD) of these SI measures are used to drive the cylindrical registration . After convergence of the algorithm, any point on the 3D surface can be mapped between both CTC acquisitions. Figure 1 illustrates the principle of this registration method. Fig. 1. Prone and supine registration of colon surfaces in cylindrical space. The color coding indicates the local shape index (SI) measurements . The method as described in [9,2] performs an alignment of SI images in cylindrical space.
Abdominal Imaging. Computation and Clinical Applications: 5th International Workshop, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings by Peter J. Schüffler, Dwarikanath Mahapatra, Jeroen A. W. Tielbeek, Franciscus M. Vos (auth.), Hiroyuki Yoshida, Simon Warfield, Michael W. Vannier (eds.)