Title :
Characterization of border structure using fractal dimension in melanomas
Author :
Carbonetto, S.H. ; Lew, S.E.
Author_Institution :
Dept. de Fis., Univ. de Buenos Aires, Buenos Aires, Argentina
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
There are many characteristics that differentiate normal moles (nevi) from melanomas. One of them is their boundary irregularity, which can be quantified using Fractal Dimension. In this work, fractal dimension of normal moles and melanoma was computed using the box counting method. These measurements were used to train a linear decoder in order to predict the pathology. The average performance to discriminate normal moles from melanomas reached 85% giving some insights about the power of the fractal dimension as a candidate for automatic detection and diagnosis.
Keywords :
edge detection; fractals; medical image processing; patient diagnosis; skin; automatic detection; automatic diagnosis; border structure characterization; boundary irregularity; box counting method; fractal dimension; linear decoder training; melanomas; normal moles; pathology prediction; Cancer; Estimation; Fractals; Malignant tumors; Skin; Testing; Training; Fractals; Humans; Melanoma; Skin Neoplasms;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627296