In vitro experiment was performed on a stented bovine jugular vein valve (VV, 14 mm I.D. x 2 cm long) and a stentless bovine jugular vein valve conduit (10 mm I.D. x 6 cm long) in a hydraulic flow loop with a downstream oscillatory pressure source to mimic respiratory changes. Simultaneous measurements were made on the valve opening area, conduit and sinus diameter changes using a specially designed laser optic system. Visualization of flow fields both proximal and distal to the venous valve, and the valve opening area were simultaneously recorded by using two video cameras. Laser Doppler anemometer surveys were made at three cross sections: the valve inlet, the valve exist, and 2 cm downstream of the venous valve to quantity flow reflux at valve closure. The experiment confirmed that the VV is a pressure-operated rather than a flow-driven device and that little or no reflux is needed to close the valve completely. The experiment further demonstrated that the VV sinus expands rapidly against back pressure, a critical character to consider in venous prosthesis design.

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The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

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