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Development of elastography as a non-invasive method for hard spots detection of packaged beef rations
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A system of finite element modeling combined with graphics. elastogram generation was used to study the detection of hard spots in beef rations. Finite element was used to model the structural deformation of beef steaks under compression while elastogram was generated using cross-correlation techniques on congruent compression RF echo sequences. The system was first used to determine the optimal elastography conditions for segments of pro-and post-detection of hard spots in packaged beef rations. Three different models, halogenous model, non-homogenous model and orthotropic model were established for beef steaks and the elastograms with different sizes and ratios of moduli of elasticity (modulus ratios) of hard spots to surrounding tissue were generated under the selected conditions. The elastograms were segmented using an automatic thresholding algorithm and the results were used to analyze the detection of hard spots. The optimal conditions determined for elastography were an applied strain of 1.0%, a sampling frequency of 35 MHz, a signal-to-noise ratio of 10, and a transducer frequency of 5 MHz. There were significant differences among three models for hard spots detection. The orthotropic model described the structure of beef steaks most precisely and had the smallest detected error for hard spot detection among the three models. Sizes of hard spot, modulus ratios of hard spot versus background, and relative positions of hard spots are factors affecting the detection of hard spots for elastography. The larger the size of hard spot, or the higher the modulus ratio, the smaller the relative error of the hard spot detection. In order for spots to be detected, they must have at least 4 mm of diameter with 5.0 modulus ratio or 2.5 modulus ratio with 6 mm of diameter. The relative positions of hard spots also was a factor affecting the individual detection of hard spots when more than one hard spot existed in the sample. Interference between hard spots may cause noise in elastogram. Three automatic thresholding segmentation algorithms were also developed in this study. They selected the threshold value for segmentation based on the contour lines, the local minima of the histogram of the elastogram, and the magnitude of gradient of the Image.
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Includes bibliographical references: 98-105.
Wang, Wei-wei (1998). Development of elastography as a non-invasive method for hard spots detection of packaged beef rations. Master's thesis, Texas A&M University. Available electronically from
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