Detail publikace

Fast and Automatic Skull Segmentation of Multidetector CT Head Images

WALEK, P. JAN, J.

Originální název

Fast and Automatic Skull Segmentation of Multidetector CT Head Images

Anglický název

Fast and Automatic Skull Segmentation of Multidetector CT Head Images

Jazyk

en

Originální abstrakt

This paper describes automatic and fast skull segmentation of head X-ray computed tomog-raphy (X-ray CT) images. Acquired data suffers from salient stair-step artifact which is corrected by registration using combination of phase correlation and gradient descent optimization methods. Skull segmentation is performed in the two steps, the first is segmentation of cortical bones by means of simple thresholding, and the second is classification of trabecular bones utilize information about shape of local histograms.

Anglický abstrakt

This paper describes automatic and fast skull segmentation of head X-ray computed tomog-raphy (X-ray CT) images. Acquired data suffers from salient stair-step artifact which is corrected by registration using combination of phase correlation and gradient descent optimization methods. Skull segmentation is performed in the two steps, the first is segmentation of cortical bones by means of simple thresholding, and the second is classification of trabecular bones utilize information about shape of local histograms.

Dokumenty

BibTex 


@inproceedings{BUT91815,
  author="Petr {Walek} and Jiří {Jan}",
  title="Fast and Automatic Skull Segmentation of Multidetector CT Head Images",
  annote="This paper describes automatic and fast skull segmentation of head X-ray computed tomog-raphy (X-ray CT) images. Acquired data suffers from salient stair-step artifact which is corrected by registration using combination of phase correlation and gradient descent optimization methods. Skull segmentation is performed in the two steps, the first is segmentation of cortical bones by means of simple thresholding, and the second is classification of trabecular bones utilize information about shape of local histograms.",
  booktitle="Student EEICT Proceedings of the 18th Conference - Volume 3",
  chapter="91815",
  howpublished="print",
  year="2012",
  month="april",
  pages="79--83",
  type="conference paper"
}