{'fraction_non_alphanumeric': 0.007470651013874066, 'fraction_numerical': 0.0, 'mean_word_length': 5.652482269503546, '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}}
Identification of Carotid Asymptomatic Plaque Using Texture and Orientation Features for Health Care

The carotid artery asymptomatic plaque identification has been done using the texture features at various orientation scales and presented in this study. The plaque region has been segmented using cubic spline interpolation method for multiresolution analysis using discrete wavelet transform. The features have been extracted using various scale and orientation of detail sub images using Gabor filters. It has been found from the analysis that the horizontal detail images have significantly greater values of the features than vertical detail images for symptomatic subjects. However, the horizontal detail images have shown low values compared to the vertical detail images for asymptomatic subjects. The algorithm is found to be simple and accurate for identifying the asymptomatic plaque clinically using less number of features.