Anomaly Detection Through Registration

Chen, Mei; Kanade, Takeo; Rowley, Henry A.; Pomerleau, Dean

doi:10.1109/CVPR.1998.698624

Anomaly Detection Through Registration

Mei Chen, Takeo Kanade, Henry A. Rowley, Dean Pomerleau

CVPR 1998 pp. 304-310

doi:10.1109/CVPR.1998.698624 /cvpr/1998/chen1998cvpr-anomaly/

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.

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Cite

Text

Chen et al. "Anomaly Detection Through Registration." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698624

Markdown

[Chen et al. "Anomaly Detection Through Registration." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/chen1998cvpr-anomaly/) doi:10.1109/CVPR.1998.698624

BibTeX

@inproceedings{chen1998cvpr-anomaly,
  title     = {{Anomaly Detection Through Registration}},
  author    = {Chen, Mei and Kanade, Takeo and Rowley, Henry A. and Pomerleau, Dean},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {304-310},
  doi       = {10.1109/CVPR.1998.698624},
  url       = {https://mlanthology.org/cvpr/1998/chen1998cvpr-anomaly/}
}