When analyzing ultrasound images, the processed data depends strongly on the settings of the equipment. So, the overall gain, Time-Gain-Compensation(TGC) , Diffraction and Focusing, pre-and post processing of the gray levels, all play a role in the estimation of the texture parameters. To correct for these dependencies, we used images from tissue mimicking phantom with the same settings of the ultrasound equipment as during the clinical procedure. The acoustic properties of the phantom have been estimated in the device developed for acoustic microscopy.
In this paper, an algorithm has been developed to extract the important features of the electrical activity of the stomach measured non invasively with placing electrodes on the abdomen of the human. The measured signal generated from stomach's muscle contraction, is called the Electrogastrogram (EGG), It is a mixture of action potentials with different amplitudes depending on position of the electrodes, direction of spread over stomach, and firing rate. The proposed algorithm is based on special structure of cascaded filters characterized with high selectivity. Parameters of individual section as well as the number of sections were estimated such that minimum mean squared spectral deviation between the measured and estimated EGG signal is achieved. The amplitudes of individual frequencies extracted by this algorithm are considered as features of EGG signal that can be used for studying stomach's physiological states. An example is given to illustrate the application of this algorithm for evaluating the stomach activity during Hunger or Digestion states. The percentage of success to discriminate between these two states was about 93.8 % for the Hunger state, and 98.9 % for the Digestion.
Introduction:Endoscopy is a well clinical tool to identify the presence of any abnormalities within the human stomach, but it is painful and the patient suffers from it, and needs special sterilization. On the other hand, electrophysiology of stomach is more reliable not only to detect the abnormalities, but also to predict the clinical state. The measured electrical potentials either invasively or non invasively reflect modes of stomach stimulation, contraction, and direction of propagation. Moreover, it shows the rhythmic variations of stomach potentials. Although, the first measurement of the Electrogastrogram (EGG) was started a 70 year ago by placing electrodes on the abdomen [2],[3], the progress in this field was very slow, due to some problems as : 1) difficulty in data acquisition and analysis because of the low Signal-to-Noise Ratio (SNR), 2) difficulty in interpreting EGG and extracting its useful features, and 3) lack of understanding the correlation between the EGG and the gastric motility [4].
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