Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Classification of sags according to their origin based on the waveform similarity

A statistical method for classification of sags their origin downstream or upstream from the recording point is proposed in this work. The goal is to obtain a statistical model using the sag waveforms useful to characterise one type of sags and to discriminate them from the other type. This model is built on the basis of multi-way principal component analysis an later used to project the available registers in a new space with lower dimension. Thus, a case base of diagnosed sags is built in the projection space. Finally classification is done by comparing new sags against the existing in the case base. Similarity is defined in the projection space using a combination of distances to recover the nearest neighbours to the new sag. Finally the method assigns the origin of the new sag according to the origin of their neighbours

The effects of information and communication technologies on the banking sector and the payments system

This dissertation studies the effects of Information and Communication Technologies (ICT) on the banking sector and the payments system. It provides insight into how technology-induced changes occur, by exploring both the nature and scope of main technology innovations and evidencing their economic implications for banks and payment systems. Some parts in the dissertation are descriptive. They summarise the main technological developments in the field of finance and link them to economic policies. These parts are complemented with sections of the study that focus on assessing the extent of technology application to banking and payment activities. Finally, it includes also some work which borrows from the economic literature on banking. The need for an interdisciplinary approach arises from the complexity of the topic and the rapid path of change to which it is subject. The first chapter provides an overview of the influence of developments in ICT on the evolution of financial services and international capital flows. We include main indicators and discuss innovation in the financial sector, exchange rates and international capital flows. The chapter concludes with impact analysis and policy options regarding the international financial architecture, some monetary policy issues and the role of international institutions. The second chapter is a technology assessment study that focuses on the relationship between technology and money. The application of technology to payments systems is transforming the way we use money and, in some instances, is blurring the definition of what constitutes money. This chapter surveys the developments in electronic forms of payment and their relationship to the banking system. It also analyses the challenges posed by electronic money for regulators and policy makers, and in particular the opportunities created by two simultaneous processes: the Economic and Monetary Union and the increasing use of electronic payment instruments. The third chapter deals with the implications of developments in ICT on relationship banking. The financial intermediation literature explains relationship banking as a type of financial intermediation characterised by proprietary information and multiple interactions with customers. This form of banking is important for the financing of small and medium-sized enterprises. We discuss the effects of ICT on the banking sector as a whole and then apply these developments to the case of relationship banking. The fourth chapter is an empirical study of the effects of technology on the banking business, using a sample of data from the Spanish banking industry. The design of the study is based on some of the events described in the previous chapters, and also draws from the economic literature on banking. The study shows that developments in information management have differential effects on wholesale and retail banking activities. Finally, the last chapter is a technology assessment study on electronic payments systems in Spain and the European Union. It contains an analysis of existing payment systems and ongoing or planned initiatives in Spain. It forms part of a broader project comprising a series of country-specific analyses covering ten European countries. The main issues raised across the countries serve as the starting point to discuss implications of the development of electronic money for regulation and policies, and in particular, for monetary-policy making.