DocumentCode :
3352115
Title :
A generic labeling scheme for segmented cardiac MR images
Author :
Bister, M. ; Cornelis, J. ; Taeymans, Y. ; Langloh, N.
Author_Institution :
Vrije Univ., Brussel, Belgium
fYear :
1990
fDate :
23-26 Sep 1990
Firstpage :
45
Lastpage :
48
Abstract :
M. Bister et al. (1989) developed an algorithm for the automatic segmentation of medical images: the cavity detector. A labeling scheme, the performance of which has been tested on cardiac magnetic resonance (MR) images, was designed based on this algorithm. The labeling scheme consists of three steps: the first step standardizes the image position, the second step checks the standardized image against spatial knowledge about the position of anatomical objects, and the third step generates a proposal for the labeling. The system is self-learning, and although it does not use typical AI tools, it makes use of some AI concepts such as trainability and separation between model and `reasoning engine´. The performance in terms of labeling quality and speed is discussed
Keywords :
biomedical NMR; cardiology; algorithm; anatomical objects position; cavity detector; generic labeling scheme; image position standardization; labeling quality; labeling speed; magnetic resonance imaging; medical diagnostic imaging; model; reasoning engine; segmented cardiac MR images; self-learning system; spatial knowledge; standardized image; trainability; Algorithm design and analysis; Artificial intelligence; Biomedical imaging; Detectors; Engines; Image segmentation; Labeling; Magnetic resonance; Proposals; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology 1990, Proceedings.
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-2225-3
Type :
conf
DOI :
10.1109/CIC.1990.144161
Filename :
144161
Link To Document :
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