Youssef  Douzi, Abdelmalek  Azizi, Mohamed  Benabdellah, Touria  Boukhana, Tarik  Hajji, Nabil  Kannouf, 
    Recognition Textures of the Tumors of the Medical Pictures by Neural Networks,
    Journal of Engineering and Applied Sciences,
    Volume 13,Issue 11,
    2018,
    Pages 4020-4024,
    ISSN 1816-949x,
    jeasci.2018.4020.4024,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2018.4020.4024)
    Abstract: Texture plays a very important role in identifying and extracting the thematic information contained
in the image. Texture analysis is a vast field whose objective is to identify the nature of a texture, either via.
classification algorithms or via. synthetic algorithms aimed at the creation of a texture, visually similar to the
original texture. As specialists are looking for radio-tracers to use in order to do a more advanced study on
diseases that infect the skin and organs in general, we have come back to thinking about using ultrasound as
ultrasound may well replace radiography in some cases like breast cancer screening. Our goal is to introduce
methods to classify different diseases which infect the skin and organs leaving traces by adaptive texture
analysis of ultrasound images, i.e., to make a recognition of different types of tumors on medical images and
to describe a new approach to automatic texture recognition in digital images using Artificial Neural Networks
(ANN).
    Keywords: Textures;recognition;tumors;medical images;learning;artificial neural networks