Publication
Title
Fast bias field reduction by localized Lloyd-Max quantization
Author
Abstract
Bias field reduction is a common problem in medical imaging. A bias field usually manifests itself as a smooth intensity variation across the image. The resulting image inhomogeneity is a severe problem for posterior image processing and analysis techniques such as registration or segmentation. In this paper, we present a fast debiasing technique based on localized Lloyd-Max quantization. Thereby, the local bias is modelled as a multiplicative field and is assumed to be slowly varying. The method is based on the assumption that the local, undegraded histogram is characterized by a limited number of gray values. The goal is then to find the discrete intensity values such that spreading those values according to the local bias field reproduces the global histogram as good as possible. We show that our method is capable of efficiently reducing (even strong) bias fields in 3D volumes in only a few seconds.
Language
English
Source (book)
Proceedings of SPIE Medical Imaging, San Diego, Calif., USA
Publication
San Diego, Calif. : SPIE, 2008
ISBN
978-0-8194-7098-0
Volume/pages
6914:Part 1-3, p. A9141
ISI
000256058600044
Note
General: doi:10.1117/12.770724
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 08.10.2008
Last edited 08.06.2017
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