In this paper we describe a quantitative evaluation of the performance of three dual-energy noise reduction algorithms: Kalender's correlated noise reduction (KCNR), noise clipping (NOC), and edge-predictive adaptive smoothing (EPAS). These algorithms were compared to a simple smoothing filter approach, using the variance and noise power spectrum measurements of the residual noise in dual-energy images acquired with an a-Si TFT flat-panel x-ray detector. An estimate of the true noise was made through a new method with subpixel accuracy by subtracting an individual image from an ensemble average image. The results indicate that in the lung regions of the tissue image, all three algorithms reduced the noise by similar percentages at high spatial frequencies (KCNR=88%, NOC=88%, EPAS=84%, NOC/KCNR=88%) and somewhat less at low spatial frequencies (KCNR=45%, NOC=54%, EPAS=52%, NOC/KCNR=55%). At low frequencies, the presence of edge artifacts from KCNR made the performance worse, thus NOC or NOC combined with KCNR performed best. At high frequencies, KCNR performed best in the bone image, yet NOC performed best in the tissue image. Noise reduction strategies in dual-energy imaging can be effective and should focus on blending various algorithms depending on anatomical locations.

The FPD provides radiographic images with excellent inherent physical image quality.

There is presently significant interest in cellular responses to physical forces, and numerous devices have been developed to apply stretch to cultured cells. Many of the early devices were limited by the heterogeneity of deformation of cells in different locations and by the high degree of anisotropy at a particular location. We have therefore developed a system to impose cyclic, large-strain, homogeneous stretch on a multiwell surface-treated silicone elastomer substrate plated with pulmonary epithelial cells. The pneumatically driven mechanism consists of four plates each with a clamp to fix one edge of the cruciform elastomer substrate. Four linear bearings set at predetermined angles between the plates ensure a constant ratio of principal strains throughout the stretch cycle. We present the design of the device and membrane shape, the surface modifications of the membrane to promote cell adhesion, predicted and experimental measurements of the strain field, and new data using cultured airway epithelial cells. We present for the first time the relationship between the magnitude of cyclic mechanical strain and the extent of wound closure and cell spreading.

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Digital tomosynthesis is a method for reconstructing arbitrary planes in an object from a series of projection radiographs, acquired with limited angle tube movement. Conventional 'shift and add' tomosynthesis suffers from the presence of blurring artifacts, created by objects located outside of each reconstructed plane. Matrix inversion tomosynthesis (MITS) uses known geometry, and a set of coupled linear algebra equations to solve for the blurring function in each reconstructed plane, enabling removal of the unwanted out-of-plane blur artifacts. For this paper, both MITS and conventional tomosynthesis reconstructions were generated for a simulated impulse located at varying distance from the detector, and also an anthropomorphic chest phantom. Exploration of the effects of total angular tube movement, number of projection radiographs acquired, and number of planes reconstructed via matrix inversion tomosynthesis, on residual out-of-plane blur ensued. We conclude that optimization of image acquisition and plane reconstruction parameters can improve slice image quality. In all examined scenarios, the MITS algorithm outperforms conventional tomosynthesis in removing out-of-plane blur.