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The assessment of myocardinal infarction is a complex, information intensive process that involves the analysis and interpretation of cardiovascular nuclear medicine images. For a number of years, a knowledge-based approach has been under development jointly between Georgia-Tech and Emory University to assist in making this clinical assessment, using images obtained from Thallium-201 sigle-photon emission computed tomography (SPECT) images. This paper discusses recent attempts to extend this knowledge-based system to incorporate the concept of myocardial thickening as a possible measure of myocardial viability, using Tc-99m and connectionist methods. The implementation of neural networks, its linkage to the knowledge-based system, and the use Sestamibi TC-99 (instead of TI-201 imagery), introduce novel informatics methods to diagostic cardiology.
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.: SABIA :. Sistemas Adaptativos y Bioinspirados en Inteligencia Artificial