{'fraction_non_alphanumeric': 0.01662049861495845, 'fraction_numerical': 0.0, 'mean_word_length': 5.3023255813953485, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Epicardial boundary detection using fuzzy reasoning.

A fully automated system for detecting the endocardial and epicardial boundaries in a two-dimensional echocardiography by using fuzzy reasoning techniques is proposed. The image is first enhanced by applying the Laplacian-of-Gaussian edge detector. Second, the center of the left ventricle is determined automatically by analyzing the original image. Next, a search process radiated from the estimated center is performed to locate the endocardial boundary by using the zero-crossing points. After this step, the estimation of the range of radius of a possible epicardial boundary is carried out by comparing the high-level knowledge of intensity changes along all directions with the actual image intensity changes. The high-level knowledge of global intensity change in the image is acquired from experts in advance, and is represented in the form of fuzzy linguistic descriptions and relations. Knowledge of local intensity change can therefore be deduced from the knowledge of global intensity change through fuzzy reasoning.