María P. Trujillo

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We propose a novel classification framework called the videospecific SVM (V-SVM) for normal-vs-abnormal white-light colonoscopy image classification. V-SVM is an ensemble of linear SVMs, with each trained to separate the abnormal images in a particular video from all the normal images in all the videos. Since V-SVM is designed to capture lesion-specific(More)
Separation of touching char particles is required for measuring morphological characteristics. In this paper, a segmentation approach for touching char particles is presented. The proposed approach is fourfold. Firstly, contours are extracted. Secondly, concave points are identified by the means of measuring concavity using gradient directions at contour(More)
Cardiovascular disease is the leading cause of death worldwide. Therefore, techniques for improving diagnosis and treatment in this field have become key areas for research. In particular, approaches for tissue image processing may support education system and medical practice. In this paper, an approach to automatic recognition and classification of(More)
BACKGROUND AND OBJECTIVE Histological images have characteristics, such as texture, shape, colour and spatial structure, that permit the differentiation of each fundamental tissue and organ. Texture is one of the most discriminative features. The automatic classification of tissues and organs based on histology images is an open problem, due to the lack of(More)
Video games may be a convenient methodology for conveying English vocabulary in context to the players, since they are story driven and can absorbs players' attention, increasing their motivation and engagement within a learning process. However, most of current vocabulary games are like digital versions of textbooks vocabulary exercises and do not meet(More)
BACKGROUND In this paper, we describe a histological ontology of the human cardiovascular system developed in collaboration among histology experts and computer scientists. RESULTS The histological ontology is developed following an existing methodology using Conceptual Models (CMs) and validated using OOPS!, expert evaluation with CMs, and how accurately(More)