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Automated Malignant Melanoma Classification Using Convolutional Neural Networks

Automated Malignant Melanoma Classification Using Convolutional Neural Networks

dc.creatorGuillermo Guarnizo, José
dc.creatorRiaño Borda, Sebastián
dc.creatorCamacho Poveda, Edgar Camilo
dc.creatorMateus Rojas, Armando
dc.date2022-12-26
dc.date.accessioned2026-03-25T19:27:02Z
dc.date.available2026-03-25T19:27:02Z
dc.identifierhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/6270
dc.identifier10.18359/rcin.6270
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/201157
dc.descriptionThis research is proposed a design of architecture for melanoma (a kind of skin cancer) recognition by using a Convolutional Neural Network (CNN), work that will be useful for researchers in future projects in areas like biomedicine, machine learning, and others related moving forward with their studies and improving this proposal. CNN is mostly used in computer vision (a branch of artificial intelligence), applied to pattern recognition in skin moles and to determine the existence of malignant melanoma, or not, with a limited dataset. The CNN classifier designed and trained in this case was built through a couple of layers of convolution and pooling stacked to form a neural network of 6 layers followed by the fully connected to complete the architecture with an output classifier. The proposed database to train our CNN is the largest publicly collection of dermoscopic images of melanomas and other skin lesions, provided by the International Skin Imaging Collaboration (ISIC), sponsored by International Society for Digital Imaging of the Skin (ISDIS), an international effort to improve melanoma diagnosis. The purpose of this research was to design a Convolutional Neural Network with a high level of accuracy to help professionals in medicine with a melanoma diagnosis, in this case, it was possible to get accuracy up to 88.75 %.
dc.descriptionEn esta investigación se propone un diseño de arquitectura para el reconocimiento de melanoma (un tipo de cáncer de piel) mediante el uso de una CNN (Red Neuronal Convolucional), trabajo que será de utilidad para investigadores en futuros proyectos en áreas como biomedicina, aprendizaje automático, y otras relacionadas avanzando en sus estudios y mejorando esta propuesta. La CNN se utiliza principalmente en visión por computador (una rama de la inteligencia artificial), aplicada al reconocimiento de patrones en lunares de la piel y para determinar la existencia de melanoma maligno, o no, con un conjunto de datos limitado. El clasificador CNN diseñado y entrenado en este caso se construyó mediante un par de capas de convolución y acumulación para formar una red neuronal de seis capas seguida de la totalmente conectada para completar la arquitectura con un clasificador de salida. La base de datos propuesta para entrenar nuestra CNN es la mayor colección pública de imágenes dermatoscópicas de melanomas y otras lesiones cutáneas, proporcionada por la International Skin Imaging Collaboration (ISIC), patrocinada por la International Society for Digital Imaging of the Skin (ISDIS), un esfuerzo internacional para mejorar el diagnóstico del melanoma. El propósito de esta investigación fue diseñar una Red Neuronal Convolucional con un alto nivel de precisión para ayudar a los profesionales de la medicina con un diagnóstico de melanoma, en este caso, fue posible obtener una precisión hasta del 88,75 %.
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dc.languagespa
dc.languageeng
dc.publisherUniversidad Militar Nueva Granada
dc.relationhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/6270/5241
dc.relationhttps://revistas.unimilitar.edu.co/index.php/rcin/article/view/6270/5367
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dc.rightsDerechos de autor 2022 Ciencia e Ingeniería Neogranadina
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.sourceCiencia e Ingenieria Neogranadina; Vol. 32 No. 2 (2022); 171-185
dc.sourceCiencia e Ingeniería Neogranadina; Vol. 32 Núm. 2 (2022); 171-185
dc.sourceCiencia e Ingeniería Neogranadina; v. 32 n. 2 (2022); 171-185
dc.source1909-7735
dc.source0124-8170
dc.subjectConvolution
dc.subjectConvolutional Neural Networks
dc.subjectDermoscopy
dc.subjectMelanoma Detection
dc.subjectConvolución
dc.subjectRedes Neuronales Convolucionales
dc.subjectDermatoscopia
dc.subjectDetección de Melanoma
dc.titleAutomated Malignant Melanoma Classification Using Convolutional Neural Networks
dc.titleAutomated Malignant Melanoma Classification Using Convolutional Neural Networks
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion


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