PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Colantonio S., Moroni D., Pieri G., Salvetti O. Image processing for decision support in the heart failure. Contribution to Deliverable D30 "Models and Methods for Signals and Images Processing" of the EU STREP Project HEARTFAID (IST-2005-027107). Technical report, 2008.
 
 
Abstract
(English)
This technical report details the activity carried out within the European Project HEARTFAID, a knowledge based platform of services for supporting medical-clinical management of the heart failure within the elderly population. Since signal and imaging investigations are a basic step of the diagnostic, prognostic and follow-up processes of heart diseases, the development of methods for computer-aided analysis of such diagnostic data has been included in the goals of HEARTFAID project. The basic idea is to improve the accuracy and consistency in the clinical interpretation of the diagnostic images and signals inherent to the management of heart failure, thus reducing the subjectivity in the findings of diagnostic examinations and improving the reproducibility of the results. In addition computer-aided methods are able to process in a more complete manner the huge datasets produced by some diagnostic resources. As it is obvious that we all already beneficiate of such automated methods (just think how much time is saved with the automatic generation of an Holter report or about the refined algorithms involved in the generation of tomographic images), it is also clear that computer-aided methods will have in general an increasingly important role in health care. This technical report is intended to cover the activity on the development of methods for image processing carried out during the project. In particular, after some recall of the diagnostic resources relevant to the management of heart failure, the prototypical algorithms developed for image processing are described in great detail. Then, deployment of these algorithms for the extraction of clinical significant parameters is explained. In parallel, the IT infrastructure needed for the seamless integration of an Image Processing Toolkit is introduced into a platform of services is described. A discussion about the value added to the foreseen Clinical Decision Support System (along with some illustrative use-cases) ends the document, clarifying the possible role of image and signal processing in the management of heart failure.
Subject Cardiac Imaging
Image Segmentation
Decision Support
PACS
I.4.6 Segmentation
I.4.7 Feature Measurement
I.3.5 Computational Geometry and Object Modeling
I.5.3 Clustering
J.3 Life and Medical Sciences


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