Automated Diagnosis for Cardiac Diseases Based on ECG Signals Image Processing and Artificial Intelligence Techniques


Abstract in English

The entry of computer to many areas, such as medical field, led to develop new technique that has led to the prosperity of these areas, and helped doctors to detect and diagnose diseases accurately and credibility, where the experience of the doctor in addition to the accuracy of computer lead to access to the credibility of high patient and save human lives. A new approach for cardiac diseases detection and classification in ECG signals images is proposed using Adaptive Neuro Fuzzy Inference System ANFIS. The proposed approach is applied on database containing (147) ECG images, each of them accompanied with its medical report. The medical reports were used to validate the detection and classification. The proposed method achieved a relatively high accuracy (97%) in detection and classification processes. The proposed approach is developed using MATLAB, and based on its libraries, image processing, neural network and fuzzy logic.

References used

JANG,J. ANFIS: Adaptive – Network- Based – Fuzzy Inference System. California Univ, Berkeley, CA, USA. Vol 23, No.3, 2002, 665-685
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