DocumentCode
2067538
Title
Theoretical analysis of a multiscale algorithm for the direct segmentation of tomographic images
Author
Kerfoot, Ian B. ; Bresler, Yoram
Author_Institution
Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
Volume
2
fYear
1994
fDate
13-16 Nov 1994
Firstpage
177
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
Keywords
computerised tomography; error analysis; image segmentation; medical image processing; quantisation (signal); Shepp-Logan skull´s quantization error; direct segmentation; monoscale segmentation; multiscale algorithm; multiscale objective function; noise levels; performance analysis; tomographic images; Additive white noise; Algorithm design and analysis; Head; Image analysis; Image segmentation; Imaging phantoms; Pixel; Skull; Tomography; X-ray imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location
Austin, TX
Print_ISBN
0-8186-6952-7
Type
conf
DOI
10.1109/ICIP.1994.413555
Filename
413555
Link To Document