A method was proposed in order to process and classify CT slices representing funnel chest deformities. A manually chosen CT slice was processed to detect the inner curvature of the chest for characterization. Normali...
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A method was proposed in order to process and classify CT slices representing funnel chest deformities. A manually chosen CT slice was processed to detect the inner curvature of the chest for characterization. Normalized data from the detected inner curvature was gained and saved next to a manually-given deformity type for further classifications. Based on the multiple correlations of the values gained from the inner curvature, a hierarchical classification was performed on 199 patient data. Results have shown that the calculated values gained from the inner curvature can accurately characterize the deformity type of the chest. Since minimal user interaction was necessary to detect and characterize the inner curvature, our method is considered to be an effective automated procedure for funnel chest deformity classifications.
Electrooculography (EOG) is used in clinical ophthalmology to measure the time response of the corneoretinal potential (CRP) to changes in light intensity. A system for automatic data acquisition and model estimation ...
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Electrooculography (EOG) is used in clinical ophthalmology to measure the time response of the corneoretinal potential (CRP) to changes in light intensity. A system for automatic data acquisition and model estimation has been developed. The data acquisition is performed on a microprocessor based instrument, which supervises the EOG test, measures the potential and, after completion of the test, transfers the results to a mainframe computer. Nonlinear curve fitting is used for the estimation of the model parameters. Several models are considered.
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