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Advances in 3-D data acquisition require better image reconstruction methods Conventional 2-D fan-beam reconstruction methods are no longer suf cient to properly reconstruct 3-D data sets acquired by 3-D cone-beam or multi-ring technologies The main characteristic of 3-D data is that each voxel is contributed not only by a single sectional data set but also by farther away sectional data adjacent to the section Therefore the image reconstruction algorithm needs to be augmented with certain mathematical models derived from scanner geometry, global and local human anatomical structures, and physiological phenomena in order to optimally reconstruct 3-D voxels In some cases the 3-D data set may also need to be reconstituted, for example, by data interpolation, recombination, and rearrangement, before the reconstruction The goals of a good 3-D reconstruction algorithm are very fast speed and better image quality.

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The trends in 3-D image reconstruction methods center in two main classes, analytic and iterative Analytic approach is favored for X-ray cone-beam reconstruction, whereas iterative approach is more suitable for SPECT and PET data There are two general analytic approaches The rst method is to use 3-D mathematical models and general strategies for exact and numerical inversion of the 3-D object from its 3-D dataset obtained from cone-beam detectors Equation (43) can be extended to 3-D to reconstruct a three-dimensional image f (x, y, z) from a 3-D data set The second method is to factorize the 3-D problem into a set of independent 2-D sectional tasks for more ef cient data and reconstruction management The iterative approach takes advantages of a priori knowledge of the objects being reconstructed, including the patient s anatomy, physiology, and pathology Speed of reconstruction is the key in iterative approach.

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In this chapter, you learned about making selections in many ways. You learned special tricks that work with only the marquee tools, and found out how to gain greater control over your fine selections with the Polygonal and Magnetic Lasso tools, as well as the new Refine Edge dialog box, which is available with all of CS3 s selection tools. You also learned to select based on pixels with the Magic Wand, and to create paths and selections with the Pen tool. Because selections are often in need of a tweak, you learned manual and automatic methods for editing selection outlines, and how to use the Feather command. You also learned to move and clone selections and selection outlines, and to fill and stroke your selections and paths.

For further discussion of 3-D reconstruction algorithms development, refer to Fully 3-D Reconstruction of Medical Imaging, a special issue of IEEE Transactions of Medical Imaging In this chapter many 3-D medical images are shown, including CT, MRI, and PET to illustrate the quality and ne details of the 3-D anatomy, physiology, and pathology 43 431 TRANSMISSION X-RAY COMPUTED TOMOGRAPHY (CT) Convention X-ray CT.

The team applies the knowledge they have gained through step 1: identify, matching this knowledge to the rating statements, from 1 to 4 for power and proximity (where 4 is the highest) and from 1 to 5 for the two parts of urgency: value and action (where 5 is the highest rating). Figure 7.8 lists the ratings for power and proximity, and Figure 7.9 lists the ratings for value and action. The index number An index number is calculated for each stakeholder from the four sets of ratings developed by the team. Calculations are inbuilt in the Stakeholder Circle software; however, for a paper-based use of the methodology, the arithmetic addition of all four ratings will be suf cient. This emphasis on ratings for urgency will ensure visibility of stakeholders who may not be considered as important to the project (Mitchell et al., 1997; Bourne, 2005)11. After the index number is calculated, the list can be sorted, with the stakeholder with the highest index number being rated as the most important, the second highest next most important and so on. Figure 7.10 shows the section of the stakeholder-on-a-page that collects the data from step 2: prioritise. Once the index number has been obtained, it is then possible to sort the pages into order from highest number to lowest, thus showing which stakeholders have more relative importance than others.

Figure 1-11: The warning message is presented when a Computer Administrator attempts to set another user s password in Computer Management.

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