Content based image retrieval using local binary pattern operator and data mining techniques.

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) operator. A study was performed in order to determine the optimum LBP variant for the general definition of image feature vectors. The chosen LBP variant is then subsequently used to build an ultrasound image database, and a database with images obtained from Wireless Capsule Endoscopy. The image indexing process is optimized using data clustering techniques for images belonging to the same class. Finally, the proposed indexing method is compared to the classical indexing technique, which is nowadays widely used.

Analysis and classification of ultrasound medical images using the Local Binary Pattern operator.

This paper aims to present a classification and retrieval technique applied to ultrasound medical images, based on different variations of Local Binary Pattern (LBP) algorithm. Using this technique, a dedicated application builds an ultrasound image database, determining the optimum variation of LBP algorithm. These techniques can be applied to an image or to a group of images. Characterization is done through an array of values extracted by the algorithm. The application allows the characterization of an image, a set of images, determining the similarity between different images and the degree of belonging to a particular group. There are also presented several comparisons between existent variations of this algorithm, applied on the same set of ultrasound images.

Is there a common background to support better healthcare in Central and South East Europe?

The workshop is proposed by the EFMI WG Health Informatics for Interregional Cooperation with the support of the Electronic Healthcare Records WG as a platform for finding common interests regarding improvement of healthcare services for the Central and East European geographical area. The goal is to assess conformance to international standards in healthcare and to find domains in which each country can provide best practices results of using ICT in support of healthcare.

The p53 network modeling - current state and future prospects.

p53 gene is a central hub in a network that have the role to protect the cells against carcinogenesis. A lot of research work has been done in this field, a huge amount of data was collected and many experiments have been performed. For a better understanding of the processes and for the help of experiments design some mathematical models were proposed in the literature. In this paper we make a brief overview of these models, pointing out their strong points and weak points. Some improvements of the models were also presented with some graphical representations of numerical simulation. Finally some conclusions were made regarding future prospects of p53 network modeling.