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Objective: To compare the signals of pulse — diagnosis of healthy volunteer in different times in one day. Methods: After collecting the pulse waves of 42 healthy volunteers in 4 specific periods in one day, do pretreatment, parameter extracting basing on harmonic fitting, modeling, and identification by unsupervised learning and supervised learning with cross-validation step by step for analysis...
Objective: To compare the signals of pulse-diagnosis of 2 kinds of liver disease patients: Fatty Liver Disease (FLD) and Cirrhosis. Methods: After collecting the pulse waves of patients with Fatty Liver, Cirrhosis, we do pretreatment, parameter extracting basing on harmonic fitting, modeling, and identification by unsupervised learning and supervised learning with cross-validation step by step for...
A fast computer-aided liver segmentation plays a vital role in computer aided surgery (CAS), especially when using texture-based methods. Large amount of features yielded in supervised segmentation methods may result in slow segment processes. In order to reduce the time required in the segment stage, we applied principal component analysis (PCA), forward orthogonal search by maximizing the overall...
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