Theoretical analysis of a multiscale algorithm for the direct segmentation of tomographic images

I. B. Kerfoot, Y. Bresler

Research output: Contribution to journalConference article

Abstract

Several multiscale objective functions for the direct segmentation of tomographic images are presented. Standard methods of signal detection and estimation are used to develop a theoretical performance analysis, which quantitatively predicts the performance at realistic noise levels. The analysis compares the relative merit of multiscale and monoscale segmentation, and shows the impact of the Shepp-Logan skull's quantization error.

Original languageEnglish (US)
Article number413555
Pages (from-to)177-181
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Volume2
DOIs
StatePublished - Jan 1 1994
EventProceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

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Signal detection

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Theoretical analysis of a multiscale algorithm for the direct segmentation of tomographic images. / Kerfoot, I. B.; Bresler, Y.

In: Proceedings - International Conference on Image Processing, ICIP, Vol. 2, 413555, 01.01.1994, p. 177-181.

Research output: Contribution to journalConference article

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