SUMMARY Biomedical flow computations in patient-specific geometries require integrating image acquisition and processing with fluid flow solvers. Typically, image-based modeling processes involve several steps, such as image segmentation, surface mesh generation, volumetric flow mesh generation, and finally computational simulation. These steps are performed separately, often using separate pieces of software, and each step requires considerable expertise and investment of time on the part of the user. In this paper an alternative framework is presented in which the entire image-based modeling process is performed on a Cartesian domain where the image is embedded within the domain as an implicit surface. Thus the framework circumvents the need for generating surface meshes to fit complex geometries and subsequent creation of body-fitted flow meshes. Cartesian mesh pruning, local mesh refinement, and massive parallelization provide computational efficiency; the image-to-computation techniques adopted are chosen to be suitable for distributed memory architectures. The complete framework is demonstrated with flow calculations computed in two 3D image reconstructions of geometrically dissimilar intracranial aneurysms. The flow calculations are performed on multiprocessor computer architectures and are compared against calculations performed with a standard multi-step route.

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Studies using simulated calcifications can be performed to measure the effect of different imaging factors on calcification detection in digital mammography. The simulated calcifications must be inserted into clinical images with realistic contrast and sharpness. MoCa is a program which modifies the contrast and sharpness of simulated calcification clusters extracted from images of mastectomy specimens acquired on a digital specimen cabinet at high magnification for insertion into clinical mammography images. This work determines whether the use of MoCa results in simulated calcifications with the correct contrast and sharpness. Aluminium foils (thickness 0.1-0.4 mm) and 1.60 µm thick gold discs (diameter 0.13-0.8 mm) on 0.5 mm aluminium were imaged with a range of thicknesses of polymethyl methacrylate (PMMA) using an amorphous selenium direct digital (DR) system and a powder phosphor computed radiography (CR) system (real images). Simulated images of the tests objects were also generated using MoCa. The contrast of the aluminium squares and the degradation of the contrast of the gold discs as a function of disc diameter were compared in the real and simulated images. The average ratios of the simulated-to-real aluminium contrasts over all aluminium and PMMA thicknesses were 1.03 ± 0.04 (two standard errors in the mean) and 0.99 ± 0.03 for the DR and CR systems, respectively. The ratio of the simulated-to-real degradations of contrast averaged over all disc diameters and PMMA thicknesses were 1.007 ± 0.008 and 1.002 ± 0.013 for DR and CR, respectively. The use of MoCa was accurate within the experimental errors.