The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

We study an application of image registration in the medical domain. Based on a 3-D hierarchical deformable registration algorithm, we have developed a prototype system which automatically aligns a standard atlas to a subject's data to create a customized atlas. Combined with domain knowledge, the registration algorithm can also detect asymmetries and abnormal variations in the subject's data that indicate the existence and location of pathologies. We have conducted tests on 106 MRI scans of normal brains, 3 MRI and 1 CT scan of brains with pathologies, with results qualitatively comparable to manual segmentation.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center

Associated Project(s): Knowledge-Guided Deformable Registration

Text Reference

Mei Chen, Takeo Kanade, Henry Rowley, and Dean Pomerleau, "Anomaly Detection through Registration," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June, 1998, pp. 304 - 310.

BibTeX Reference

@inproceedings{Chen_1998_2681,
   author = "Mei Chen and Takeo Kanade and Henry Rowley and Dean Pomerleau",
   title = "Anomaly Detection through Registration",
   booktitle = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
   pages = "304 - 310",
   month = "June",
   year = "1998",
}

The Robotics Institute

Menu