NDLI: An Approach of Multiscale Complexity in Texture Analysis of Lymphomas

Content Provider	IEEE Xplore Digital Library
Author	Jia-Rong Yeh Chung-Wu Lin Jiann-Shing Shieh
Copyright Year	1994
Abstract	Complexity is considered with high interest to texture analysis, such as the application of lymphoma inspection. Previously, multiscale entropy was proposed to account for the multiple time scales inherent in complex biological signals, and complexity texture descriptors were considered for content-based medical image retrieval system. However, in the past, these complexity texture descriptors were derived by linear algorithms of Fourier and wavelet transforms. In this study, we introduce a new approach of multiscale complexity (MSC) for texture analysis of lymphomas based on a nonlinear parameter of entropy. An extended algorithm of 2-D entropy was used in the calculations of complexities for the coarse-grained images of different scale factors. Furthermore, five parameters are defined to characterize 58 images of reactive lymphadenopahty and five categories of lymphomas using complexity on three scales and the changes of complexity between two successive scales. MSC analysis performed well to figure out the statistical differences of paired comparisons picked from reactive lymphadenopahty and five categories of lymphomas.
Sponsorship	IEEE Signal Processing Society
Starting Page	239
Ending Page	242
Page Count	4
File Size	467178
File Format	PDF
ISSN	10709908
Volume Number	18
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Complexity theory Entropy Time series analysis Algorithm design and analysis Biomedical imaging Frequency modulation Prediction algorithms texture analysis Coarse-grained image lymphoma multiscale complexity multiscale entropy
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing Electrical and Electronic Engineering

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