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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| Format: | Online |
| Language: | eng |
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Universidad Pedagógica y Tecnológica de Colombia
2024
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| Online Access: | https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943 |
| _version_ | 1801706105084051456 |
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| author | Niño-Rondón, Carlos-Vicente Castellano-Carvajal, Diego-Andrés Castro-Casadiego, Sergio-Alexander Medina-Delgado, Byron Puerto-López, Karla-Cecilia |
| author_facet | Niño-Rondón, Carlos-Vicente Castellano-Carvajal, Diego-Andrés Castro-Casadiego, Sergio-Alexander Medina-Delgado, Byron Puerto-López, Karla-Cecilia |
| author_sort | Niño-Rondón, Carlos-Vicente |
| collection | OJS |
| 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. |
| format | Online |
| id | oai:oai.revistas.uptc.edu.co:article-16943 |
| institution | Revista Facultad de Ingeniería |
| language | eng |
| publishDate | 2024 |
| publisher | Universidad Pedagógica y Tecnológica de Colombia |
| record_format | ojs |
| spelling | oai:oai.revistas.uptc.edu.co:article-169432024-04-25T02:29:52Z HASCC: A Hybrid Algorithm for Skin Cancer Classification HASCC: Algoritmo Híbrido para Clasificación de Cáncer de Piel Niño-Rondón, Carlos-Vicente Castellano-Carvajal, Diego-Andrés Castro-Casadiego, Sergio-Alexander Medina-Delgado, Byron Puerto-López, Karla-Cecilia 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 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. 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. Universidad Pedagógica y Tecnológica de Colombia 2024-03-30 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943 10.19053/uptc.01211129.v33.n67.2024.16943 Revista Facultad de Ingeniería; Vol. 33 No. 67 (2024): January-March 2024; e16943 Revista Facultad de Ingeniería; Vol. 33 Núm. 67 (2024): Enero-Marzo 2024; e16943 2357-5328 0121-1129 eng https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943/14025 Copyright (c) 2024 Carlos-Vicente Niño-Rondón, Diego-Andrés Castellano-Carvajal, Sergio-Alexander Castro-Casadiego, Byron Medina-Delgado, Karla-Cecilia Puerto-López http://creativecommons.org/licenses/by/4.0 |
| spellingShingle | 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 Niño-Rondón, Carlos-Vicente Castellano-Carvajal, Diego-Andrés Castro-Casadiego, Sergio-Alexander Medina-Delgado, Byron Puerto-López, Karla-Cecilia HASCC: A Hybrid Algorithm for Skin Cancer Classification |
| title | HASCC: A Hybrid Algorithm for Skin Cancer Classification |
| title_alt | HASCC: Algoritmo Híbrido para Clasificación de Cáncer de Piel |
| 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_short | HASCC: A Hybrid Algorithm for Skin Cancer Classification |
| title_sort | hascc a hybrid algorithm for skin cancer classification |
| 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 |
| topic_facet | 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 |
| url | https://revistas.uptc.edu.co/index.php/ingenieria/article/view/16943 |
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