Computed tomography was one of the first imaging modalities to require a computerized solution of an inverse problem to produce a useful image from the data acquired by the sensor hardware. The computerized solutions, which are known as image reconstruction algorithms, have thus been a critical component of every CT scanner ever sold. We review the history of commercially deployed CT reconstruction algorithms and consider the forces that led, at various points, both to innovation and to convergence around certain broadly useful algorithms. The forces include the emergence of new hardware capabilities, competitive pressures, the availability of computational power, and regulatory considerations. We consider four major historical periods and turning points. The original EMI scanner was developed with an iterative reconstruction algorithm, but an explosion of innovation coupled with rediscovery of an older literature led to the development of alternative algorithms throughout the early 1970s. Most CT vendors quickly converged on the use of the filtered back-projection (FBP) algorithm, albeit layered with a variety of proprietary corrections in both projection data and image domains to improve image quality. Innovations such as helical scanning and multi-row detectors were both enabled by and drove the development of additional applications of FBP in the 1990s and 2000s. Finally, the last two decades have seen a return of iterative reconstruction and the introduction of artificial intelligence approaches that benefit from increased computational power to reduce radiation dose and improve image quality.
We present a 3-D electronic unpacking technique for airport security images based on volume rendering techniques
developed for medical applications. Two electronic unpacking techniques are presented: (1) object-based unpacking and
(2) unpacking by bag-slicing. Both techniques provide photo-realistic 3-D views of contents inside a packed bag with
clearly marked threats. For the object-based unpacking, the 3-D objects within packed bags are unpacked (or isolated)
though object selection tools that cut away undesired regions to isolates the 3-D object from the background clutter.
With this selection tool, the operator is able to electronically unpack various 3-D objects and manipulate (rotate and
zoom) the 3-D photo-realistic views for the immediate classification of the suspect object. The unpacking by bag-slicing technique places arbitrary cut planes to show the content beyond the cut plane that can be stepped forward or backward electronically. The methods may be used to reduce the need for manual unpacking of suitcases.
KEYWORDS: Data acquisition, Reconstruction algorithms, Scanners, Computer simulations, Computed tomography, Image quality, Medical imaging, Sensors, Signal to noise ratio, Collimators
This paper deals with methods of reducing the total time required to acquire the projection data for a set of contiguous CT images. Normally during the acquisition of a set of slices, the patient is held stationary during data collection and translated to the next axial location during an inter-scan delay. The authors will demonstrate, using computer simulations and scans of volunteers on a modified scanner, how acceptable image quality is achieved if the patient translation time is overlapped with data acquisition. If the concurrent patient translation is ignored, structured artifacts significantly degrade resulting reconstructions. A number of algorithms are presented to minimize the structured artifacts through the use of projection modulation using the data from individual and multiple slices. Comparison is made of the methods with respect to structured artifacts, noise, resolution and susceptibility to motion. Review of preliminary clinical feedback by a panel of radiologists has indicated that the residual image degradation is tolerable for selected applications when it is critical to acquire more slices in a patient breathing cycle than is possible with conventional scanning. The method is a useful protocol when some image quality can be traded for increased scan rate. Applications include increased contrast utilization and minimization of registration artifacts.
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