NDLI: Segmentation of MR images by a fuzzy c-mean algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ramze Rezaee, M. Nyqvist, C. van der Zwet, P.M.J. Jansen, E. Reiber, J.H.C.
Copyright Year	1995
Description	Author affiliation: Dept. of Diagnostic Radiol., Univ. Hospital Leiden, Netherlands (Ramze Rezaee, M.; Nyqvist, C.; van der Zwet, P.M.J.; Jansen, E.; Reiber, J.H.C.)
Abstract	Since the manual delineation of the left ventricular (LV) contour in MR images is subject to intra- and inter-observer variations, an automated procedure is proposed. The fuzzy c-mean clustering approach was used to segment the images. The segments were labeled as either the left ventricular lumen or the background by using additionally the information provided by the Hough transform which delivered a rough estimation of the center of the ventricle. To find an optimal agreement between the manually and automatically delineated LV contours, 2700 combinations of different parameters were used in a set of 20 images of patients and normal subjects. An excellent correlation coefficient (r=0.95) was found when parameters were optimized for each individual image. However if the parameter set was fixed for all images, the correlation coefficient decreased to r=0.8. This suggests that a cluster validation measure must be defined for a good performance. This is the topic of further research.
Starting Page	21
Ending Page	24
File Size	465995
Page Count	4
File Format	PDF
ISBN	0780330536
DOI	10.1109/CIC.1995.482561
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-09-10
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Clustering algorithms Prototypes Image analysis Image processing Algorithm design and analysis Laboratories Radiology Hospitals Extraterrestrial measurements
Content Type	Text
Resource Type	Article

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