NDLI: Comparison of real and computer-simulated clustered microcalcifications on digital mammograms. ROC study

Content Provider	IEEE Xplore Digital Library
Author	Lado, M.J. Mendez, A.J. Tahoces, P.G. Souto, M. Correa, J. Vidal, J.J.
Copyright Year	1996
Description	Author affiliation: Dept. de Radiol., Santiago de Compostela Univ., Spain (Lado, M.J.)
Abstract	The authors propose a model to simulate clustered microcalcifications on digital mammograms. The simulation model is based on the gray-level, size and number of microcalcifications per cluster. All the parameters describing the individual microcalcifications and clusters were randomly sampled from the values of the real clustered microcalcifications (extracted in a feature analysis process) present in the mammogram, the exception being the center of the cluster, that was interactively positioned to ensure the location of all the microcalcifications inside the breast. Subsequently, a database of clustered microcalcifications was created. These clusters of microcalcifications from this database were tested from indistinguishability from real ones. Two radiologists and one physicist were asked to indicate wether the microcalcifications were either real or simulated. The responses of the readers were evaluated with an ROC analysis, and the area under the curve was calculated. The average ROC area was 0.54/spl plusmn/0.05, indicating that there was no statistical difference between real and simulated clustered microcalcifications.
Starting Page	355
Ending Page	358
File Size	517265
Page Count	4
File Format	PDF
ISBN	0780332598
DOI	10.1109/ICIP.1996.559506
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-09-19
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Medical simulation Spatial databases Breast cancer Laser modes Analytical models Wavelet transforms Medical diagnostic imaging Feature extraction Testing
Content Type	Text
Resource Type	Article

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