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Oriol Pujol

Publications and source records attributed to Oriol Pujol.

2 recordsLinked to original sources

Discriminant ECOC: a heuristic method for application dependent design of error correcting output codes.

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images.

Algorithms↗

On the assessment of texture feature descriptors in intravascular ultrasound images: a boosting approach to a feasible plaque classification.

Intravascular ultrasound images represent a unique tool to guide interventional coronary procedures, this technique allows to supervise the cross-sectional locations of the vessel morphology and to provide quantitative and qualitative information about the causes and severity of coronary diseases. At the moment, the automatic extraction of this kind of information is performed without taking into account the basic signal principles that guide the process of image generation. In this chapter, we overview the main physical principles and factors that affect the IVUS generation; we propose a simple physics-based approach for IVUS image simulation that is defined as a discrete representation of the tissue by individual scatterrers elements with given spatial distribution and backscattering differential cross sections. In order to generate the physical model that allows to construct synthetic IVUS images, we analyze the process of pulse emission, transmission and reception of the ultrasound signal as well as its interaction with the different tissues scatterrers of the simulated artery. In order to obtain the 3D synthetic image sequences we involve the dynamic behavior of the heart/arteries and the catheter movement in the image generation model. Having an image formation model allows to study rhe physics parameters that participate during the image generation and to achieve a better understanding and robust interpreting of IVUS image structures. Moreover, this model allows to comprehend, simulate and solve several limitations of IVUS sequences, to extract important image parameters to be taken into account when developing robust image processing algorithms as well as to construct wide synthetic image sequence databases in order to validate different image processing techniques.

Algorithms↗