Abstract
We present the results of constructing a probabilistic volumetric model of 3D MR kidney images. The ultimate goal of this work is the mouse kidney segmentation based on a probabilistic volumetric model. The kidneys were aligned into the base shape using an extended robust point matching algorithm. The registration step consists of the global linear transformation and the local B-spline based free form deformation. Shape modeling is performed with globally aligned shape and template volumetric image is generated with locally aligned images. We are currently working on developing a segmentation algorithm using our model.
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Okuda, H., Shkarin, P., Behar, K., Duncan, J.S., Papademetris, X. (2004). Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_134
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DOI: https://doi.org/10.1007/978-3-540-30136-3_134
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22977-3
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