X-ray or gamma ray systems or devices – Specific application – Computerized tomography
Reexamination Certificate
1999-12-23
2002-01-15
Bruce, David V. (Department: 2882)
X-ray or gamma ray systems or devices
Specific application
Computerized tomography
C378S901000
Reexamination Certificate
active
06339632
ABSTRACT:
CROSS-REFERENCE TO RELATED APPLICATIONS
Not applicable.
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT
Not applicable.
BACKGROUND OF THE INVENTION
The present invention relates to multislice helical computerized tomography and more particularly to an algorithm, method and apparatus for using the same which reduces the data processing time required to generate an image.
In computerized tomography (CT) x-ray photon rays are directed through a patient toward a detector array. Attenuated rays are detected by the array, the amount of attenuation indicative of the make up (e.g. bone, flesh, air pocket, etc.) of the patient through which the rays traversed. The attenuation data is then backprojected to generate an image of the patient's internal anatomy.
Early CT systems used a pencil beam photon source consisting essentially of a single ray and a single detector. To collect a complete projection from a single angle about the patient the pencil beam was directed at the patient consecutively from adjacent locations along a line thereby generating parallel ray data for the projection. Other parallel ray projections through the same patient slice from different angles about the slice were generated in the same manner. After multiple (e.g., 500 or more) parallel projection data sets were generated for a slice, the data was backprojected to form a slice image. Because early CT systems generated parallel projection data sets, most CT reconstruction algorithms have been developed assuming parallel data sets.
Unfortunately, while pencil beam systems generate data in a form readily useful with conventional reconstruction algorithms, such systems have a number of shortcomings. One primary shortcoming is that data acquisition periods using such a system are excessive. This is particularly true where images in many slice planes are required. Not only do long acquisition periods reduce system throughput but long periods also often result in relatively poor images. This is because patient movement likelihood increases as the time required for data acquisition increases and patient movement results in blurred images and undesirable artifacts.
Various CT system features and procedures have been developed to increase data acquisition speed including fan beam acquisition, simultaneous multiple slice acquisition and helical scanning. In fan beam systems, instead of using a pencil beam source, the source is collimated into a thin fan beam which is directed at a detector array on a side opposite a patient. In this manner, a complete fan beam projection data set is instantaneously generated for the angle defined by the source during a single data acquisition period and data collection is expedited.
In multiple slice systems, a relatively thick fan beam is collimated and directed at a multi-row detector with a patient therebetween, each detector row in effect gathering data for a separate slice of the thick fan beam along a Z axis perpendicular to the direction of the fan beam.
In a helical scanning system, the source and detector array are mounted on opposing surfaces of an annular gantry and are rotated therearound as a patient is transported at constant speed through the gantry, the x-ray beam sweeps a helical path through the patient, hence the nomenclature “helical scanning system”. Data acquisition can be sped up by increasing the pitch or table translation speed/gantry rotation ratio. Increased pitch typically results in less detailed imaging.
Various combinations of the fan-beam, multislice and helical scanning features have been combined to realize synergies and have been somewhat successful. By combining all three speed enhancing features data acquisition periods are appreciably reduced thereby increasing system throughput and increasing image quality by minimizing the likelihood of patient movement.
While the features described above speed up data acquisition, the resulting data is not in a form which is readily useable with the conventional image reconstruction algorithms. Whereas the conventional algorithms require parallel constant-Z data for reconstruction, data generated using the optimal fast hardware configuration and generation methods generate fan beam (i.e., non-parallel) data for many projections which are not in the same slice (i.e. are multi-Z). Thus, for example, data for two projections will include two separate fan beam projection data sets, a first set at one Z-location and a second set at another Z-location where Z is the axis of gantry rotation.
Not surprisingly, because of data acquisition speed advantages, various algorithms and methods have been developed to generate constant-Z slice images from helical multi-slice fan beam data. To this end, exemplary algorithms require a processor to solve complex and computationally detailed weighting and filtering equations to generate data suitable for backprojection algorithms. Exemplary weighting algorithms are described in an article entitled “
Multi-Slice Helical CT: Scan and Reconstruction
” by Hui Hu which was published in the January 1999 issue of Medical Physics, vol. 26, No. 1, pages 1 through 14. In operation, after imaging data has been collected and archived for a specific patient volume (i.e. 3 dimensional section) of interest, an imaging system operator can select a specific slice and slice thickness through the volume of interest for image reconstruction and display. When a slice is selected, the processor applies the weighting and filtering function to the data to generate the intended image. The weighting function is dependent upon which slice is selected for reconstruction and viewing. Therefore, each time a new slice is selected, a completely different weighting function which is pitch and slice dependent, has to be accessed and applied to the acquired data and the weighted projection data has to be refiltered again to generate the desired image.
Because the filtering and weighting algorithms are extremely complex, data processing is not fast enough to support instantaneous imaging. Thus, after a slice to be imaged is selected, processing requirements cause a delay. The delay is repeated each time a new slice to be imaged is selected. While this process of selection, weighting, evaluation and reselection may not be objectionable where a system user generally knows the slice or slices which should be examined and therefore may only need to be repeated a few times, in some cases the user will not know which images are important and will therefore have to go on a “fishing” expedition requiring many iterative image reconstruction sequences. Moreover, where three-dimensional imaging or fluoroscopy techniques are employed most systems require reconstruction of two or more (e.g., some times 6, 12, etc) images per source rotation to generate images having diagnostic quality Z-resolution and temporal resolution. In these cases required reconstruction time is excessive.
Other relatively fast acquisition/processing systems/methods have been developed which include other combinations of fan-beam, multi-slice and helical scanning features. For example, one such system described in an article entitled “New Classes of Helical Weighting Algorythms With Applications to Fast CT Reconstruction” by Guy Besson which was published in Med. Phys. 25(8), August 1998 by Am. Assoc. Phys. Med. combines single slice fan beam data acquisition and helical scanning. As taught in the Besson article such a system is typically used to generate fan beam projections during a single 2 &pgr; rotation about a patient. Thereafter, the fan beam data is filtered, weighted and backprojected to generate one or more images in various constant Z planes.
Unfortunately, weighting algorithms used with these single slice systems include a fan beam angle dependency and do not lend themselves to fast image reconstruction. This is because, as known in the art, weight distributions present a line of discontinuity across the space of projections which defines two separate sinogram regions. The weighting function expressions differ for the two separa
Bruce David V.
Cabou Christian G.
GE Medical Systems Global Technology Company LLC
Quarles & Brady LLP
LandOfFree
Multi slice single filtering helical weighting method and... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Multi slice single filtering helical weighting method and..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Multi slice single filtering helical weighting method and... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2861037