Lidia Ogiela

Image languages in intelligent radiological palm diagnostics

This paper presents a new technique of computer-aided analysis and recognition of pathological wrist bone lesions. This method uses artificial intelligence (AI) techniques and mathematical linguistics allowing to evaluate automatically and analyse the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm (wrist) bones. This description has been built with the use of graph linguistic formalisms already applied in artificial intelligence. These were, however, developed and adjusted to the needs of automatic medical image understanding in earlier works of the authors, as specified in the bibliography section of this paper. The research described in this paper has demonstrated that the for needs of palm (wrist) bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well-suited. Defining a graph image language adjusted to the specific features of the scientific problem here-described allowed for a semantic description of correct palm bone structures (with consideration to idiosyncratic features). It also enabled interpretation of images showing some in-born lesions, such as additional bones; or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.

Cognitive Techniques in Visual Data Interpretation

The following chapters of this book presents key issues concerning the neurophysiological aspects of executing cognitive thought processes and the basics of cognitive informatics and new proposals of UBIAS systems dedicated to the meaning-based analysis of selected types of medical images. In particular, to structure the considerations of pattern classification methods, Chapter 2 discusses traditional image recognition techniques and algorithms from the simplest methods based on metric spaces up to methods that use the paradigms of computer image understanding. Chapter 3 deals with the cognitive aspects of brain function. Information from this chapter allows the authors, in a latter part of this book, to show functional analogies between the operation of biological systems and computer implementations. Chapter 4 provides a short compendium of knowledge about the new branch of informatics which formally describes thought processes, namely cognitive informatics. The introduction to subjects of cognitive processes analysed by cognitive informatics will then allow us to introduce new classes of computer systems executing cognitive resonance processes. The following Chapter 5 defines a new class of information systems using cognitive resonance processes. This chapter reviews several proposals of various classes of cognitive categorisation systems put forward by the authors. Chapter 6 contains a broader discussion of the UBIAS system class which the authors proposed for the meaning-based analysis of medical images. Then, Chapter 7 discusses in detail two examples of UBIAS systems built for the semantic classification of foot bone X-rays and images of long bone injuries in extremities. Chapter 8, the last, compiles and summarises information on creating cognitive vision systems designed for the semantic classification of patterns. The authors present this book to Readers in the hope that it will stir their fascination with the scientific aspects of creating new generation computer systems which imitate thought processes and can determine the meaning of complex image patterns.

Advances in Cognitive Information Systems

The development of computer science is now so rapid that we, the readers, in-creasingly receive technology news about new solutions and applications which very often straddle the border between the real and the virtual worlds. Computer science is also the area in which cognitive science is witnessing a renaissance, be-cause its combination with technical sciences has given birth to a broad scientific discipline called cognitive informatics. And it is this discipline which has become the main theme of this monograph, which is also to serve as a kind of guide to cognitive informatics problems. This book is the result of work on systems for the cognitive analysis and inter-pretation of various data. The purpose of such an analytical approach is to show that for an in-depth analysis of data, the layers of semantics contained in these sets must be taken into account. The interdisciplinary nature of the solutions proposed means that the subject of cognitive systems forming part of cognitive informatics becomes a new challenge for the research and application work carried out. The authors of this monograph hope that it will guide Readers on an interesting and accurate journey through the intricacies of information and cognitive science.

Semantic Analysis Processes in Advanced Pattern Understanding Systems

This publication presents the use of semantic data analysis in cognitive processes of data analysis, interpretation, recognition and understanding in advanced pattern understanding systems. These processes form a part of a field called cognitive informatics, which encompasses subjects related to the semantic analysis and interpretation of data leading to understanding the analysed data sets. These systems dedicated for cognitive analysis of image data called Understanding Based Image Analysis Systems. Examples of applications of this type of semantic analysis processes and methods will be shown using the case of an cognitive system for the semantic analysis of image data presenting X-ray images of foot bone lesions.

UBIAS systems for cognitive interpretation and analysis of medical images

The main subject of this publication is to present a selected class of cognitive categorisation systems - understanding based image analysis systems (UBIAS) which support analyses of data recorded in the form of images. Cognitive categorisation systems operate by following particular type of thought, cognitive, and reasoning processes which take place in a human mind and which ultimately lead to making an in-depth description of the analysis and reasoning process. The most important element in this analysis and reasoning process is that it occurs both in the human ability cognitive/thinking process and in the system’s information/reasoning process that conducts the in-depth interpretation and analysis of data.

Cognitive systems and bio-inspired computing in homeland security

This publication primarily deals with biological modelling in the context of data protection and securing confidential information from disclosure or being accessed by third parties. Biological modelling of information/data of an individual, personal and unique nature, namely individual biometrics, leads to extracting information classes necessary for personal data protection processes. Such processes can be used to secure various types of data. Adding semantic data analysis processes to IT system classes which are used to conceal processes of personal data management offers opportunities for semantically analysing and interpreting data while it is being disclosed/decrypted.

Cognitive systems for intelligent business information management in cognitive economy

In the paper was described cognitive information systems for business information management.This system is designed to semantically analyse some economic data with selected financial ratios.Semantic reasoning algorithms based on cognitive resonance was applied for such analysis.An idea of cognitive economy was presented. This paper will present new theoretical and applied solutions for intelligent data analysis and information management in the fields of cognitive economics. Intelligent data analysis and information management are performed by information systems called cognitive systems, dedicated for semantic interpretation of acquired business information. To interpret the meaning of the analysed data, complex linguistic algorithms must be used, based on which it is possible to find the core information elements for business processes forecasting and economical knowledge management. The presentation of selected methods of semantic data analysis in cognitive economy, which allow to perform both local and global information management forms the main subject of this paper. Here, semantic analysis methods are dedicated to cognitive economics problems, namely the interpretation, analysis and assessment of the meaning of selected sets of economic/financial ratios. The meaning of the interpreted data sets is assessed by analysing the layers of meaning contained in data analysed sets. Obtained semantic information may be used in future business processes evaluation and forecasting.

Semantic analysis and biological modelling in selected classes of cognitive information systems

Abstract Cognitive categorisation systems are used for in-depth analyses of data which contains significant layers of information. These layers consist of the semantic information found in the data sets, whose information allows the system executing data analysis processes to understand the data to a certain extent and to reason based on this analysed information. Such processes are executed by semantic data analysis systems which are called cognitive categorisation systems in the introduced classification of cognitive systems dedicated to analyses in various fields of application. Cognitive data analysis systems are also expanded by adding processes of learning new solutions hitherto unknown to the system because it had no appropriate pattern defined or because it had no data allowing the analysed data to be unambiguously assigned to its corresponding pattern. The ability to train the system so that it would correctly interpret the analysed data marks the beginning of the development of a new class of systems analysing data/individual features in the course of biological modelling, personalisation and personal identification processes. Identification systems are enhanced by adding elements of cognitive categorisation systems in order to execute an in-depth, more detailed personal analysis using the information collected in the system, whose information concerns not only the anatomical and physical features, but also, or maybe primarily, lesions found in various human organs. Such systems could be used in personal identification cases in which there are doubts and a risk arises due to reasoning from incomplete data sets. Adding semantic analysis modules to personal identification systems represents a novel scientific proposition which marks the beginning of the use of semantic analysis processes for biological modelling and personalisation tasks. The solutions proposed are illustrated with the example of selected E-UBIAS systems which analyse medical image data in combination with the identity analysis. The use of DNA cryptography and DNA code to analyse personal data makes it possible to unanimously assign analysed data to an individual at the personal identification stage. This publication presents also the system with semantic analysis processes conducted based on semantic interpretation and cognitive processes allows the possible lesions that the person suffers from to be identified and authorised.

Cognitive informatics in image semantics description, identification and automatic pattern understanding

In the paper a new way of pattern semantic interpretation directed at automatic semantic classification and image content understanding will be described. Such an understanding will be based on the linguistic theories of pattern classification and is aimed at facilitation of content analysis for some classes of medical patterns. The approach presented in this paper will show the great possibilities of automatic disease interpretation in some analyzed data. The interpretation will be based on cognitive processes, which imitate the psychological processes of understanding the registered patterns as they take place in the brain of a human being. Cognitive analysis will be based on languages of shape description and picture grammars which allow the creation of syntactic descriptions of selected anatomic organs together with a definition of the semantic meaning of the changes in their shapes. Such descriptions will further allow creating a semantically-oriented representation of visual data describing pattern features which are useful in medical decisions and computer-aided diagnostic systems. This publication presents the cognitive systems of medical data image analysis. Systems that conduct cognitive analyses are designed so that semantic analyses can be used to interpret data and reconstruct medical images. These systems are built for medical types of data analysis systems. An analysis in classical CIAIS (Cognitive Image Analysis Information Systems) will be used to illustrate and present the method of learning new solutions which the systems have no knowledge of. The proposed solution presents the method of building a new class of cognitive systems names E-CIAIS (Extended Cognitive Image Analysis Information Systems).

Data management in cognitive financial systems

Abstract This publication discusses ways of using cognitive analyses for semantically interpreting economic figures. A semantic analysis making use of mathematical linguistic algorithms in order to extract meaning from sets of analysed data is illustrated with an example of a class of cognitive systems designed to analyse economic figures, or more precisely, financial ratios. The cognitive analysis systems presented in this publication are discussed as exemplified by the class of Cognitive Financial Analysis Information Systems (CFAIS). This publication proposes algorithms executed by a broad class of automatic data interpretation and understanding systems designed for the in-depth semantic analysis and interpretation of the results obtained. This will be done by defining new system classes as applications supporting decision-making processes, useful in various areas of knowledge.