COMPUTER AIDED DIAGNOSIS USING SOFT-COMPUTING TECHNIQUES AND IMAGE’S ISSUED REPRESENTATION: APPLICATION TO BIOMEDICAL AND INDUSTRIAL FIELDS
Autor: | Nadia Kanaoui, Francois Houbre, Véronique Amarger, Matthieu Voiry, Amine Chohra, Kurosh Madani |
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Rok vydání: | 2014 |
Předmět: | |
Zdroj: | International Journal of Computing. :43-53 |
ISSN: | 2312-5381 1727-6209 |
DOI: | 10.47839/ijc.5.3.408 |
Popis: | It is interesting to notice that from “problem’s formulation” point of view “Industrial Computer Aided Diagnosis” and “Biomedical Computer Aided Diagnosis” could be formulated as a same diagnosis riddle: “How point out a correct diagnosis from a set of symptoms?”. The only difference between the two above-mentioned groups of problems is the nature of the monitored (diagnosed) system: in the first group the monitored system is an artificial machinery (plant, industrial process, etc…), while in the second, the monitored system is a living body (animal or human).One of the most appealing classes of approaches allowing handling the Computer Aided Diagnosis Systems’ design in the frame of the aforementioned dual point of view is Soft-Computing based techniques, especially those dealing with neural networks and fuzzy logic. In this article, we present two soft-computing based approaches dealing with CADS design. One aims designing a biomedical oriented CADS and the other sets sights on conceiving a CADS to overcome a real-world industrial quality control dilemma. The goal of the first system is to diagnose the human’s auditory pathway’s health. The target of the second is to detect and diagnose the high tech optical devices’ defects. |
Databáze: | OpenAIRE |
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