HASCC: A Hybrid Algorithm for Skin Cancer Classification

Skin cancer is a dangerous and potentially lethal disease that is steadily increasing worldwide. Signs of skin cancer may include changes in the appearance of moles or the emergence of new spots on the skin. Early detection is crucial, as many types of skin cancer respond well to treatment when addr...

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Autores:
Tipo de recurso:
Fecha de publicación:
2024
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
eng
OAI Identifier:
oai:repositorio.uptc.edu.co:001/14387
Acceso en línea:
https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943
https://repositorio.uptc.edu.co/handle/001/14387
Palabra clave:
skin cancer
computer-aided diagnosis
open-source
embedded system
hybrid algortihm
graphical user interface
algoritmo híbrido
cáncer de piel
código abierto
diagnóstico asistido por computador
interfaz gráfica de usuario
sistema embebido
Rights
License
http://creativecommons.org/licenses/by/4.0
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dc.title.en-US.fl_str_mv HASCC: A Hybrid Algorithm for Skin Cancer Classification
dc.title.es-ES.fl_str_mv HASCC: Algoritmo Híbrido para Clasificación de Cáncer de Piel
title HASCC: A Hybrid Algorithm for Skin Cancer Classification
spellingShingle HASCC: A Hybrid Algorithm for Skin Cancer Classification
skin cancer
computer-aided diagnosis
open-source
embedded system
hybrid algortihm
graphical user interface
algoritmo híbrido
cáncer de piel
código abierto
diagnóstico asistido por computador
interfaz gráfica de usuario
sistema embebido
title_short HASCC: A Hybrid Algorithm for Skin Cancer Classification
title_full HASCC: A Hybrid Algorithm for Skin Cancer Classification
title_fullStr HASCC: A Hybrid Algorithm for Skin Cancer Classification
title_full_unstemmed HASCC: A Hybrid Algorithm for Skin Cancer Classification
title_sort HASCC: A Hybrid Algorithm for Skin Cancer Classification
dc.subject.en-US.fl_str_mv skin cancer
computer-aided diagnosis
open-source
embedded system
hybrid algortihm
graphical user interface
topic skin cancer
computer-aided diagnosis
open-source
embedded system
hybrid algortihm
graphical user interface
algoritmo híbrido
cáncer de piel
código abierto
diagnóstico asistido por computador
interfaz gráfica de usuario
sistema embebido
dc.subject.es-ES.fl_str_mv algoritmo híbrido
cáncer de piel
código abierto
diagnóstico asistido por computador
interfaz gráfica de usuario
sistema embebido
description Skin cancer is a dangerous and potentially lethal disease that is steadily increasing worldwide. Signs of skin cancer may include changes in the appearance of moles or the emergence of new spots on the skin. Early detection is crucial, as many types of skin cancer respond well to treatment when addressed in the early stages. Computer-aided diagnostic tools are employed to aid in the diagnosis of this disease. This article introduces HASCC, a hybrid algorithm implemented through a graphical user interface for skin cancer classification. The algorithm integrates image processing, feature extraction using the VGG16 algorithm with component reduction through PCA, and classification using XGBoost trained on images from the HAM10000 dataset. The hybrid algorithm was executed and tested on a Raspberry Pi 4 embedded system. HASCC was compared at both hardware and software levels with other computational intelligence methods and architectures, revealing notable improvements in terms of accuracy, ranging from 88.2% to 93.2%, with an average execution time of 250 milliseconds at low machine resource demand during the diagnostic process. Additionally, HASCC's performance was compared against previous research focused on skin cancer detection and classification. The hardware performance demonstrates that HASCC can be implemented on single-board microprocessor devices, and its software performance suggests viability for supporting the diagnosis and classification of skin cancer.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-07-05T19:12:12Z
dc.date.available.none.fl_str_mv 2024-07-05T19:12:12Z
dc.date.none.fl_str_mv 2024-03-30
dc.type.none.fl_str_mv info:eu-repo/semantics/article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.coarversion.spa.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a322
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943
10.19053/uptc.01211129.v33.n67.2024.16943
dc.identifier.uri.none.fl_str_mv https://repositorio.uptc.edu.co/handle/001/14387
url https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943
https://repositorio.uptc.edu.co/handle/001/14387
identifier_str_mv 10.19053/uptc.01211129.v33.n67.2024.16943
dc.language.none.fl_str_mv eng
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943/14025
dc.rights.en-US.fl_str_mv http://creativecommons.org/licenses/by/4.0
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf239
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
http://purl.org/coar/access_right/c_abf239
http://purl.org/coar/access_right/c_abf2
dc.format.none.fl_str_mv application/pdf
dc.publisher.en-US.fl_str_mv Universidad Pedagógica y Tecnológica de Colombia
dc.source.en-US.fl_str_mv Revista Facultad de Ingeniería; Vol. 33 No. 67 (2024): January-March 2024; e16943
dc.source.es-ES.fl_str_mv Revista Facultad de Ingeniería; Vol. 33 Núm. 67 (2024): Enero-Marzo 2024; e16943
dc.source.none.fl_str_mv 2357-5328
0121-1129
institution Universidad Pedagógica y Tecnológica de Colombia
repository.name.fl_str_mv Repositorio Institucional UPTC
repository.mail.fl_str_mv repositorio.uptc@uptc.edu.co
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spelling 2024-03-302024-07-05T19:12:12Z2024-07-05T19:12:12Zhttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/1694310.19053/uptc.01211129.v33.n67.2024.16943https://repositorio.uptc.edu.co/handle/001/14387Skin cancer is a dangerous and potentially lethal disease that is steadily increasing worldwide. Signs of skin cancer may include changes in the appearance of moles or the emergence of new spots on the skin. Early detection is crucial, as many types of skin cancer respond well to treatment when addressed in the early stages. Computer-aided diagnostic tools are employed to aid in the diagnosis of this disease. This article introduces HASCC, a hybrid algorithm implemented through a graphical user interface for skin cancer classification. The algorithm integrates image processing, feature extraction using the VGG16 algorithm with component reduction through PCA, and classification using XGBoost trained on images from the HAM10000 dataset. The hybrid algorithm was executed and tested on a Raspberry Pi 4 embedded system. HASCC was compared at both hardware and software levels with other computational intelligence methods and architectures, revealing notable improvements in terms of accuracy, ranging from 88.2% to 93.2%, with an average execution time of 250 milliseconds at low machine resource demand during the diagnostic process. Additionally, HASCC's performance was compared against previous research focused on skin cancer detection and classification. The hardware performance demonstrates that HASCC can be implemented on single-board microprocessor devices, and its software performance suggests viability for supporting the diagnosis and classification of skin cancer.El cáncer de piel es una enfermedad peligrosa y potencialmente letal que aumenta constantemente en los reportes de casos de cáncer a nivel mundial. Los signos de cáncer de piel pueden incluir cambios en la apariencia de los lunares o la aparición de nuevas manchas en la piel. La detección temprana es fundamental, ya que muchos tipos de cáncer de piel responden bien al tratamiento si se abordan en las etapas iniciales. Para el apoyo en el diagnóstico de esta enfermedad se emplean herramientas de diagnóstico asistido. Este artículo presenta HASCC, un algoritmo híbrido implementado mediante una interfaz gráfica de usuario para la clasificación del cáncer de piel. El algoritmo integra procesamiento de imágenes, extracción de características mediante el algoritmo VGG16 con reducción de componentes mediante PCA y clasificación mediante XGBoost entrenado con imágenes del Conjunto de Datos HAM10000. El algoritmo híbrido se ejecutó y se probó sobre un sistema embebido Raspberry Pi 4. HASCC se comparó a nivel hardware y a nivel software con otros métodos y arquitecturas de inteligencia computacional, y se obtuvo que el sistema propuesto mostró mejores notables en términos de precisión, que osciló entre el 88.2 % y 93.2 %, con un tiempo promedio de ejecución de 250 milisegundos a baja demanda de recursos de máquina durante el proceso de diagnóstico. Adicionalmente, el rendimiento de HASCC se comparó contra investigaciones previas enfocadas a la detección y clasificación de cáncer de piel. El rendimiento a nivel hardware demuestra que HASCC es viable para implementación en dispositivos microprocesadores de placa única, y con su desempeño a nivel de software se infiere que es viable para el apoyo en el diagnóstico y clasificación del cáncer de piel.  application/pdfengengUniversidad Pedagógica y Tecnológica de Colombiahttps://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943/14025Copyright (c) 2024 Carlos-Vicente Niño-Rondón, Diego-Andrés Castellano-Carvajal, Sergio-Alexander Castro-Casadiego, Byron Medina-Delgado, Karla-Cecilia Puerto-Lópezhttp://creativecommons.org/licenses/by/4.0http://purl.org/coar/access_right/c_abf239http://purl.org/coar/access_right/c_abf2Revista Facultad de Ingeniería; Vol. 33 No. 67 (2024): January-March 2024; e16943Revista Facultad de Ingeniería; Vol. 33 Núm. 67 (2024): Enero-Marzo 2024; e169432357-53280121-1129skin cancercomputer-aided diagnosisopen-sourceembedded systemhybrid algortihmgraphical user interfacealgoritmo híbridocáncer de pielcódigo abiertodiagnóstico asistido por computadorinterfaz gráfica de usuariosistema embebidoHASCC: A Hybrid Algorithm for Skin Cancer ClassificationHASCC: Algoritmo Híbrido para Clasificación de Cáncer de Pielinfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a322http://purl.org/coar/version/c_970fb48d4fbd8a85Niño-Rondón, Carlos-VicenteCastellano-Carvajal, Diego-AndrésCastro-Casadiego, Sergio-AlexanderMedina-Delgado, ByronPuerto-López, Karla-Cecilia001/14387oai:repositorio.uptc.edu.co:001/143872025-07-18 11:53:44.152metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCrepositorio.uptc@uptc.edu.co