Ir al contenido

Documat


Pattern recognition in medical images using neural networks

  • Autores: Laura Cristina Lanzarini Árbol académico, Armando De Giusti Árbol académico
  • Localización: Journal of Computer Science and Technology, ISSN-e 1666-6038, Vol. 1, Nº. 4, 2001 (Ejemplar dedicado a: Fourth Issue; 3 p.)
  • Idioma: inglés
  • Enlaces
  • Resumen
    • The proposal of this research line is the search for alternatives to the resolution of complex problems where human knowledge should be apprehended in a general fashion. In particular, the activities developed so far can be included in the area of Medical Diagnosis, even though similar applications in other fields are not discarded. In general, one of the greatest problems of medical diagnosis is the subjectivity of the specialist. The experience of the professional greatly affects the final diagnosis. This is due to the fact that the result does not depend on a systematized solution, but on the interpretation of the patient´s answer. The solution to this kind of problems can be found in the area of Adaptive Pattern Recognition, where the solution rests on the easiness with which the systems adapts to the information available, in this case coming from the patient. In this sense, neural networks are extremely useful, since they are not only capable of learning with the aid of an expert, but they can also make generalizations based on the information from the input data, thus showing relations that are a priori of a complex nature.

  • Referencias bibliográficas
    • References [1] Supervised Adaptive Resonance Networks. Baxter. Center for Adaptive Systems. Boston University. 1991
    • [2] Neural Network Segmentation of Magnetic Resonance Spin Echo Images of theBrain. Cagnoni, Coppini, Rucci, Caramella,Valli. Jounal of Biomedical...
    • [3] Digital Image Processing. Gonzalez y Woods. Addison-Wesley. 1992
    • [4] Neurocomputing. Robert Hecht-Nielsen. Addison-Wesley. 1990
    • [5] Fundamentals of Digital Image Processing. Anil Jain. Prentice Hall.1989
    • [6] Caracterización de los Elementos de una Muestra Histológica utilizando Khoros. Lanzarini, Castañeda, Badrán, De Giusti. II International...
    • [7] Real Time Analysis of the Nystagmus and Movement Patterns in Balance Disturbances. Lanzarini, Vargas, Estelrrich, De Giusti. 19th International...
    • [8] Reconocimiento y Clasificación de los elementos de una muestra de sangre
    • utilizando Redes Neuronales. Lanzarini, Vargas, Badrán, De Giusti. 6º Congreso Internacional de Nuevas Tecnologías y Aplicaciones Informáticas....
    • [9] Fuzzy Neural Network for Classification and Detection of Anomalies. Meneganti, Saviello y Tagliaferri. IEEE Transactions on Neural Networks,...
    • [10] Neural Networks for Pattern Recognition. Albert Nigrin. MIT Press 1993
    • [11] Optimun Segmentation of Medical Images with Hopfield Neural Networks. Poliy Valli. CSRP-95-12. School of Computer Science. The University...
    • [12] A method for fuzzy rules extraction directly from numerical data and its application to pattern recognition. Shiego Abe and Ming-Shong...
    • [13] Fuzzy min-max neural networks - Part1 : Clasification. P.Simpson. IEEE Trans.Neural Networks, Vol3, pp 776-786,1992
    • [14] Fuzzy min-max neural networks – Part2 : Clasification. P.Simpson. IEEE Trans.Neural Networks, Vol1, pp 32-45,1993
    • [15] A new neural network for cluster-detection-and-labeling. Torbjorn Eltoft. IEEE Transactions on Neural Networks, Vol. 9, nr. 5, pp 1021-1035....
    • [16] Neural Networks and Prior Knowledge Help the Segmentation of Medical Images. Valli, Poli, Cagnoni and Coppini. Journal of Computing and...

Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno