Characterization of border structure using Fractal Dimension in melanomas

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 measuremen...

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Autor principal: Carbonetto, S.H
Otros Autores: Lew, S.E
Formato: Acta de conferencia Capítulo de libro
Lenguaje:Inglés
Publicado: 2010
Acceso en línea:Registro en Scopus
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100 1 |a Carbonetto, S.H. 
245 1 0 |a Characterization of border structure using Fractal Dimension in melanomas 
260 |c 2010 
270 1 0 |m Carbonetto, S. H.; Laboratorio de Física de Dispositivos-Microelectrónica, Departamento de Física, Universidad de Buenos Aires, Av. Paseo Colón 850, C1063ACV Buenos Aires, Argentina; email: scarbonetto@fi.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Ganster, H., Pinz, A., Röhrer, R., Wildling, E., Binder, M., Kittler, H., Automated melanoma recognition (2001) IEEE Transactions on Medical Imaging, 20 (3). , March 
504 |a Zagrouba, E., Barhoumi, W., A prelimary approach for the automated recognition of malignant melanoma (2004) Image Analysis and Stereology, 23 (2) 
504 |a Baish, J.W., Jain, R.K., Fractals and cancer (2000) Perspectives in Cancer Research 
504 |a Ng, V., Coldman, A., Diagnosis of melanoma with fractal dimension (1993) TENCON'93, 4, pp. 514-517. , October 
504 |a Piantanelli, A., Maponi, P., Scalise, L., Serresi, S., Cialabrini, A., Basso, A., Fractal characterisation of boundary irregularity in skin pigmented lesions (2005) Medical and Biological Engineering and Computing Journal, 43 (4), pp. 436-432. , August 
504 |a Gao, J., Zhang, J., Fleming, M.G., Pollak, I., Cognetta, A.B., Segmentation of dermatoscopic images by stabilized inverse diffusion equations (1998) 1998 International Conference on Image Processing (ICIP'98), 3, pp. 823-827 
504 |a Tuceryan, M., Moment based texture segmentation (1994) Pattern Recognition Letters, 15. , Julio 
520 3 |a 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. © 2010 IEEE.  |l eng 
593 |a Laboratorio de Física de Dispositivos-Microelectrónica, Departamento de Física, Universidad de Buenos Aires, Av. Paseo Colón 850, C1063ACV Buenos Aires, Argentina 
593 |a Instituto de Ingeniería Biomédica (IIBM), Facultad de Ingeniería, Universidad de Buenos Aires, Av. Paseo Colón 850, C1063ACV Buenos Aires, Argentina 
690 1 0 |a AUTOMATIC DETECTION 
690 1 0 |a BOUNDARY IRREGULARITIES 
690 1 0 |a BOX-COUNTING METHOD 
690 1 0 |a MEDICINE 
690 1 0 |a PARTIAL DISCHARGES 
690 1 0 |a FRACTAL DIMENSION 
690 1 0 |a ARTICLE 
690 1 0 |a FRACTAL ANALYSIS 
690 1 0 |a HUMAN 
690 1 0 |a MELANOMA 
690 1 0 |a PATHOLOGY 
690 1 0 |a SKIN TUMOR 
690 1 0 |a FRACTALS 
690 1 0 |a HUMANS 
690 1 0 |a MELANOMA 
690 1 0 |a SKIN NEOPLASMS 
700 1 |a Lew, S.E. 
711 2 |c Buenos Aires  |d 31 August 2010 through 4 September 2010  |g Código de la conferencia: 83008 
773 0 |d 2010  |h pp. 4088-4091  |p Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., EMBC  |n 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10  |z 9781424441235  |t 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 
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