Anomaly Detection through Registration

Mei Chen, Takeo Kanade, Henry Rowley, and Dean Pomerleau
IEEE Computer Society Conference on Computer Vision and Pattern Recognition, July, 1998, pp. 304 - 310.


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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, July, 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 = "July",
   year = "1998",
}