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We propose a voxel-based nonrigid registration algorithm for temporal subtraction of two-dimensional thorax X-ray computed radiography images of the same subject. The deformation field is represented by a B-spline with a limited number of degrees of freedom, that allows global rib alignment to minimize subtraction artifacts within the lung field without obliterating interval changes of clinically relevant soft-tissue abnormalities. The spline parameters are constrained by a statistical deformation model that is learned from a training set of manually aligned image pairs using principal component analysis. Optimization proceeds along the transformation components rather then along the individual spline coefficients, using pattern intensity of the subtraction image within the automatically segmented lung field region as the criterion to be minimized and applying a simulated annealing strategy for global optimization in the presence of multiple local optima. The impact of different transformation models with varying number of deformation modes is evaluated on a training set of 26 images using a leave-one-out strategy and compared to the manual registration result in terms of criterion value and deformation error. Registration quality is assessed on a second set of validation images by a human expert rating each subtraction image on screen. In 85% of the cases, the registration is subjectively rated to be adequate for clinical use. Index Terms--Image registration, image segmentation, temporal subtraction, thorax.

The study presented in this paper tests the hypothesis that the combination of a global similarity transformation and local free-form deformations can be used for the accurate segmentation of internal structures in MR images of the brain. To quantitatively evaluate our approach, the entire brain, the cerebellum, and the head of the caudate have been segmented manually by two raters on one of the volumes (the reference volume) and mapped back onto all the other volumes, using the computed transformations. The contours so obtained have been compared to contours drawn manually around the structures of interest in each individual brain. Manual delineation was performed twice by the same two raters to test inter- and intrarater variability. For the brain and the cerebellum, results indicate that for each rater, contours obtained manually and contours obtained automatically by deforming his own atlas are virtually indistinguishable. Furthermore, contours obtained manually by one rater and contours obtained automatically by deforming this rater's own atlas are more similar than contours obtained manually by two raters. For the caudate, manual intra- and interrater similarity indexes remain slightly better than manual versus automatic indexes, mainly because of the spatial resolution of the images used in this study. Qualitative results also suggest that this method can be used for the segmentation of more complex structures, such as the hippocampus. Index Terms--Atlas-based segmentation, deformation, registration.

The goal of this study was to determine the acquisition parameters for a low-dose multi-slice CT protocol and to compare the effective dose and the image quality of this low-dose protocol with the image quality of a clinical multi-slice CT protocol, routinely used for visualisation of the head. The low-dose protocol was derived from a clinical multi-slice CT protocol by lowering mA s and kV and increasing the pitch. The low-dose protocol yielded a dose reduction from 1.5 to 0.18 mSv for a multi-slice CT scan of the whole head, whereas noise in the low-dose CT images was increased. For bone segmentation, noise could be reduced by use of a non-linear edge preserving smoothing filter. Tests on ESP and skull phantom indicated that the accuracy of the measurements on low-dose CT is acceptable for image-based planning of maxillofacial and oral implant surgery, reducing the dose by a factor of 8. [ABSTRACT FROM AUTHOR]

The purpose of the study was to investigate whether visual inspection of maximum intensity projection (MIP) images is a reliable method for assessment of the severity of renal artery stenoses (RAS). Therefore, 20 RAS were investigated with helical CT. Native axial images and MIP images were analysed separately or in combination ('two-step method'). A phanton study was performed to investigate the influence of window setting on apparent stenosis severity. Accuracy for diagnosis of 50-69% and 70-99% RAS and the mean inter-observer agreement were 82.5%, 77.5% and 82.5% respectively, using study of MIP images alone, and 100%, 97.5% and 95% using the 'two-step method'. The phantom study showed that the apparent severity of vascular stenoses on MIP images depends on the selected window centre values. It is concluded that combined evaluation of both MIP images and native axial images is more reliable than study of MIP images alone for assessing the severity of RAS. [ABSTRACT FROM AUTHOR]