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CNR enhancement in the presence of multiple interfering processes using linear filters
Author(s) -
Brown D. G.,
Lee J. N.,
Blinder R. A.,
Wang H. Z.,
Riederer S. J.,
Nolte L. W.
Publication year - 1990
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.1910140109
Subject(s) - filter (signal processing) , imaging phantom , linear filter , set (abstract data type) , computer science , contrast (vision) , feature (linguistics) , image enhancement , noise (video) , process (computing) , artificial intelligence , computer vision , mathematics , pattern recognition (psychology) , image (mathematics) , nuclear medicine , medicine , linguistics , philosophy , programming language , operating system
Given several images of the same slice, a linear filter can produce an image in which the contrast‐to‐noise ratio (CNR) between pathological and normal tissues is greater than in any of the initial images. To distinguish the pathology from more than one tissue, the filter should optimize the set of CNRs between the pathology and each of the interfering tissues. We define the optimal filter as the one which provides the largest value for the minimum CNR in the set and show how it is selected from a field of only four possibilities. The filter is demonstrated with both experimental phantom studies and clinical cases. Filter performance is compared with that of other techniques for distinguishing a desired feature from more than one interfering process. © 1990 Academic Press, Inc.