Design of a graphic interface for tongue tissue image processing and classification employing neural networks

Contenido principal del artículo

A. A. González-González
D. Bueno-Hernández
I. A. Cantillo-Sánchez
Y. Martínez-Pioquinto
I. Bueno-Juárez
V. H. Ortiz-Flores

Resumen

In this work, we introduce a graphical interface for detection and classification of different tissue, focusing on tongue soft tissue, based on ADALINE neural networks to provide tools for a highly accurate diagnosis. The interface is capable to identify an affected area or even by exploration of an image of the same sample, to identify normal and pathological conditions. The Adaptive Linear Element (ADALINE) neural network successfully achieved a correct classification of 95% of total study cases, identifying either healthy or abnormal tissue, presented from a set of 70% of images for validations and 30% for training out of the total images.

Detalles del artículo

Cómo citar
González-González, A. A., Bueno-Hernández, D., Cantillo-Sánchez, I. A., Martínez-Pioquinto, Y., Bueno-Juárez, I., & Ortiz-Flores, V. H. (2018). Design of a graphic interface for tongue tissue image processing and classification employing neural networks. Memorias Del Congreso Nacional De Ingeniería Biomédica, 5(1), 134–137. Recuperado a partir de https://memoriascnib.mx/index.php/memorias/article/view/615
Sección
Procesamiento de Señales e Imágenes Médicas