Antonio Mosquera González

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In this work, we have developed a computer-aided diagnosis system, based on a two-level artificial neural network (ANN) architecture. This was trained, tested, and evaluated specifically on the problem of detecting lung cancer nodules found on digitized chest radiographs. The first ANN performs the detection of suspicious regions in a low-resolution image.(More)
The tear film lipid layer is heterogeneous among the population. Its classification depends on its thickness and can be done using the interference pattern categories proposed by Guillon. This papers presents an exhaustive study about the characterisation of the interference phenomena as a texture pattern, using different feature extraction methods in(More)
Dry eye syndrome is affecting a remarkable percentage of population. The prevalence is 10-15% of normal population, and 18-30% of contact lenses users. The break-up time (BUT) is a clinical test used for the diagnosis of this disease. In this work, we perform an analysis of parameters for a global and a local automatic computation of the BUT measure, based(More)
—This paper presents a comparative study of different texture extraction methods for the automatic classification of the tear film lipid layer based on the categories enumerated by Guillon [1]. From a photography of the eye, a region of interest is detected and its low-level features are extracted, generating a feature vector that describes it, to be(More)
In this work, extraction of relevant objects from images and their matching for retrieval is proposed. Objects are represented by using a two dimensional deformable structure referred to as active net, capable to adapt to relevant image regions according to chromatic and edge information. In particular, this representation allows a joint description of(More)