Evaluation of fuzzy-neighborhood filters in medical imaging

Autor:	Bjoern Olstad, Sevald Berg
Rok vydání:	1997
Předmět:	Pixel business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Stability (learning theory) Filter (signal processing) Fuzzy control system Fuzzy logic Digital image Geography Medical imaging Computer vision Artificial intelligence business Digital filter
Zdroj:	SPIE Proceedings.
ISSN:	0277-786X
DOI:	10.1117/12.274077
Popis:	In this paper we adapt the framework of a new class of nonlinear digital filters based on fuzzy connected neighborhoods to medical imaging and compare it with other families of digital image filters. An introduction to filters based on fuzzy neighborhoods is given. The framework is adapted to different medical imaging modalities. We discuss the underlying definition of the distance metric in the given applications and appropriate hard constraints in the extraction of pixel neighborhoods. The study demonstrates that fuzzy neighborhood filters are very useful in medical imaging. The fuzzy neighborhood approach offers more flexibility in the design of the filter and in the stability of the filtering process. The fuzzy connected neighborhood filters can perform strong filtering and still maintain fine, thin structures. The filter will not blur edges and this fact is used to define spatio-temporal filters for ultrasonic video sequences.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Databáze:	OpenAIRE
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