A methodology based on wavelet transform to identify the cardiac region in images of electrical impedance tomography José Pedro de Oliveira 1 Harki Tanaka 2 Neli Regina Siqueira Ortega 1 1 Informática Médica, Faculdade de Medicina, USP 05405-000, São Paulo, SP 2 Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas, UFABC 09090-400, Santo André, SP E-mail: jpolive@gmail.com , harkit@usp.br , neli@dim.fm.usp.br RESUMO Electrical Impedance Tomography (EIT) is an imaging technique, still in development, in which an image of the conductivity of a transversal section of an object is inferred from electrical measurements using a series of electrodes placed on its surface [1]. Despite the benefits presented by this technique, it has some limitations, amongst which we detach the low spatial resolution. Although the EIT method presents a high time resolution, the low spatial resolution hinders the characterization of the activity of regions according to their physiological origin in a dynamic image. These difficulties in interpreting the images, both in the anatomical and in the functional points of view, can be translated as an uncertainty of identification of the pixels. One of the most important EIT studies concerns to the images of the thorax, aiming to monitor the cardio-respiratory functions. In that sense, Tanaka et al. [2] proposed the use of fuzzy sets theory to deal with the pixels identification uncertainty through fuzzy linguistic models, aiming for a segmented image of the cardiac and pulmonary maps. Despite the good results presented, this model showed some limitations in identifying the heart in more complex situations, such as PEEP (Positive End-Expiratory Pressure) variation. Therefore, it is realized that a tool that could extract more information from EIT signal could be capable to separate with more clearness the pulmonary and cardiac regions. One of the tools capable to extract information of signals in the time and frequency domains is the Wavelet Transform. The image generated by the EIT system used is formed by 1024 pixels, where each pixel corresponds to a certain area of the body of the object under analysis. These pixels have variations in their impedances due to the blood flow during the cardiac cycle. In order to develop a methodology to identify the heart region in the EIT images of the thorax, a qualitative analysis of the time varying information contained in these signals is necessary. Firstly, this qualitative analysis was based on the wave patterns analysis and after each pattern was discussed with the cardio-respiratory expert panel, considering the physiological knowledge. This analysis was of fundamental importance in the model development, because it provided the knowledge about the standard behavior for each region of chest (lungs, ventricle, atrium, aorta, etc.). EIT raw data were collected in an animal experiment (pig) which was submitted to different values of PEEP: 18cmH2O (PEEP18), 12cmH2O (PEEP12) and 0cmH2O (ZEEP). This is important to evaluate the robustness of the system developed in different clinical conditions. For — 157 — Anais do CNMAC v.2 ISSN 1984-820X