Title :
Multifractal Measures for Tissue Image Classification and Retrieval
Author :
Hemsley, Anna ; Mukundan, Ramakrishnan
Author_Institution :
Comput. Sci. & Software Eng., Univ. of Canterbury, Christchurch, New Zealand
Abstract :
Multifractal analysis has recently found applications in the field of automatic classification and content based retreival of tissue and cell images. The classification accuracy in such methods largely depends on the invariant characteristics of the spectra computed for a chosen intensity measure. It is therefore necessary to carry out a detailed analysis of suitable measures and the invariance of the resulting spectra. This paper discusses some key implementation aspects of multifractal based classification techniques, gives a comparative analysis of different types of intensity measures, and presents experimental results showing the corresponding inter-class and intra-class variations in the multifractal spectra.
Keywords :
biological tissues; biology computing; cellular biophysics; content-based retrieval; fractals; image classification; image retrieval; medical image processing; automatic classification; cell images; classification accuracy; content based retreival; multifractal analysis; multifractal measures; tissue image classification; tissue image retrieval; Biomedical imaging; Biomedical measurements; Computer science; Fractals; Image analysis; Image classification; Image retrieval; Shape; Size measurement; Software engineering; multifractal measures; tissue classification;
Conference_Titel :
Multimedia, 2009. ISM '09. 11th IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-5231-6
Electronic_ISBN :
978-0-7695-3890-7
DOI :
10.1109/ISM.2009.94