RICERCA ITALIANA     

Implementation and integration of a telematic system for the follow-up of high cardiovascular risk population.

Università degli Studi di Napoli "Federico II"

Abstract

The cardio and cerebro-vascular diseases represent the major cause of morbility and mortality in the general population for this reason their treatment increase financial and human resources neverherless the activities devoted to this problem are fragmentary and less coordinated and the expected results are unsatisfactory. It is therefore necessary the development of integrated informatic systems to allow an organicity in the activities devoted in the clinical control of the patients with high cardiovascular risk both during and after their hospitalization. Indeed in our region the use of telematic systems in health-care is unsutisfactory and it si also needed an improvement in exchange of competence between Specialistic Centers. Indeed, besides the actual context has stregthened the large diffusion of methodology correlated to the innovation tecnology in order to improve the quality of the performances nothing is already well-done. This project try to realize an integrated System able to obtain a data-base with clinical data integrated with video data which should be used also in remote mode on regional basis. In the present project a cooperation will be done between different research structures according to their competence: medical, computer science and informatic. A first phase for the project is estlablished for the realization of the structure of the data-base and a second phase to develop applications that allow the data manipulation and image evaluation. The >>>

Principal Investigator

Nicola DE LUCA Università degli Studi di NAPOLI "Federico II"

Research Objectives

The project integrates the interdisciplinary competence of several national research centers (Computer Science, Physics and Biomedicine) with the aim of developing and validating advanced biomedical applications in the field of image representation and anlisys.
The involved research group has already demonstrated, in previous regional and national experiences, the ability to develop and apply advanced and innovative image analysis techniques to be used in several areas of biomedicine, with the aim to use clinical data in remote condition and in clinical practice and, also, to improve the effectiveness and efficiency of health care.
The research activity will investigate new reliable software tools supporting health professionals in taking promptly the best possible decision. Specific focus will be given to research on user-friendly, fast and reliable browsing tools providing access to heterogeneous health information sources, and also new methods for decision support. Particular attention will be also devoted to the modalities of networking of researchers in the areas of medical informatics and bioinformatics aimed to lead to new health knowledge.
The activity will be focused on:
- Development and application of advanced techniques of pattern and image analysis for the extraction of parameters of diagnostic interest;
- Development and application of advanced techniques in order to exchange in real time biomedical information (texts >>>

First Results

Delivery of this phase:
Tecnhical reports, publications, a reference data base, a collection of available software toolsExpected results:
Technical reports, publications, prototype software for image denoising, multimodal image matching, reconstruction of functional imaging modalities, geometric segmentation and unsupervised classification.Expected results:
Technical reports, publications, beta release of integrated software modules, a web page of the project where data, tools and experiments can be easily share among the scientific community.

Timescale

24 months

National and international background

Medical imaging is an important source of anatomical and functional information and is indispensable for the diagnosis and treatment of disease. However, huge amounts of high-resolution three-dimensional spatial and temporal data cannot be effectively processed and utilized with traditional visualization techniques. It is generally insufficient or inefficient for physicians to only visually inspect the medical image data collected from standard and emerging imaging modalities. The role of medical imaging is continuously expanding and the medical image analysis community has become faced with the challenging problem of creating quantification algorithms that make full use of the information in the flood of image data.
Among the primary tasks of medical image analysis there are image segmentation, registration, and motion analysis (Duncan et al. 2000). Medical image analysis directly involves different fields such as image data fusion, quantitative and time series analysis, biomechanical modelling, generating anatomical atlases, visualization, virtual and augmented reality, instrument and patient localization and tracking, etc.
Medical images, for example, are analyzed to ascertain the detailed shape and organization of anatomic structures, in an effort to enable a surgeon to preoperatively plan an optimal approach to some target structure (eg. Breuwer et al. 1998). Medical images can also be analyzed for examining relationships between structural abnormalities >>>