|Background The statistical shape atlas is a 3D medical image analysis tool that encodes
shape variations between populations. However, efficiency, accuracy, and finding the correct
correspondence, are still unsolved issues during the construction of the atlas.
Methods We developed a two-level based framework which speeds up the registration process while maintaining accuracy of the atlas. We also proposed a semi-automatic strategy to achieve segmentation and registration simultaneously, without knowing any prior information about the shape.
Results We have constructed the atlas for the femur and spine, separately. Experimental results demonstrate the efficiency and accuracy of our methods.
Conclusions Our two-level framework and semi-automatic strategy are able to efficiently construct the atlas for bone structures without losing accuracy. We can handle either 3D surface data or raw DICOM images.
Number of pages: 48
|Chenyu Wu, Patricia E. Murtha, and Branislav Jaramaz, "Construction of statistical shape atlases for bone structures based on two-level framework ," International Journal of Medical Robotics and Computer Assisted Surgery, October, 2009.|
author = "Chenyu Wu and Patricia E. Murtha and Branislav Jaramaz",
title = "Construction of statistical shape atlases for bone structures based on two-level framework ",
journal = "International Journal of Medical Robotics and Computer Assisted Surgery",
month = "October",
year = "2009",
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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