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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Autores principales: Carbonetto, S.H., Lew, S.E.
Formato: CONF
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p4088_Carbonetto
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spelling todo:paper_97814244_v_n_p4088_Carbonetto2023-10-03T16:43:10Z Characterization of border structure using Fractal Dimension in melanomas Carbonetto, S.H. Lew, S.E. Automatic Detection Boundary irregularities Box-counting method Medicine Partial discharges Fractal dimension article fractal analysis human melanoma pathology skin tumor Fractals Humans Melanoma Skin Neoplasms 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. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p4088_Carbonetto
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Automatic Detection
Boundary irregularities
Box-counting method
Medicine
Partial discharges
Fractal dimension
article
fractal analysis
human
melanoma
pathology
skin tumor
Fractals
Humans
Melanoma
Skin Neoplasms
spellingShingle Automatic Detection
Boundary irregularities
Box-counting method
Medicine
Partial discharges
Fractal dimension
article
fractal analysis
human
melanoma
pathology
skin tumor
Fractals
Humans
Melanoma
Skin Neoplasms
Carbonetto, S.H.
Lew, S.E.
Characterization of border structure using Fractal Dimension in melanomas
topic_facet Automatic Detection
Boundary irregularities
Box-counting method
Medicine
Partial discharges
Fractal dimension
article
fractal analysis
human
melanoma
pathology
skin tumor
Fractals
Humans
Melanoma
Skin Neoplasms
description 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.
format CONF
author Carbonetto, S.H.
Lew, S.E.
author_facet Carbonetto, S.H.
Lew, S.E.
author_sort Carbonetto, S.H.
title Characterization of border structure using Fractal Dimension in melanomas
title_short Characterization of border structure using Fractal Dimension in melanomas
title_full Characterization of border structure using Fractal Dimension in melanomas
title_fullStr Characterization of border structure using Fractal Dimension in melanomas
title_full_unstemmed Characterization of border structure using Fractal Dimension in melanomas
title_sort characterization of border structure using fractal dimension in melanomas
url http://hdl.handle.net/20.500.12110/paper_97814244_v_n_p4088_Carbonetto
work_keys_str_mv AT carbonettosh characterizationofborderstructureusingfractaldimensioninmelanomas
AT lewse characterizationofborderstructureusingfractaldimensioninmelanomas
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