FIELD OF THE INVENTION

Aspects of the disclosed technology relate to estimating scatter in projection data, and, more particularly, to utilizing a narrow aperture scan to estimate scatter in a wider aperture scan during various imaging techniques, including x-ray, computed tomography (CT), and cone-beam computed tomography (CBCT) scans.

BACKGROUND

Scatter in cone-beam CT can account for a significant portion of the detected photons, especially when no anti-scatter grids are used with a wide collimation opening. Scatter can negatively impact image quality, including contrast and quantitative accuracy. Consequently, scatter measurement, estimation, and correction are applicable to cone-beam CT data processing and image reconstruction, including in the context of image-guided radiation treatment (IGRT). IGRT can make use of medical imaging technology, such as CT, to collect images of a patient before, during, and/or after treatment.

For cone-beam computed tomography (CBCT) using flat panels, a pair of high attenuation blades as part of a collimator can be used to form an aperture that limits the axial range that the x-ray beam illuminates in the patient/panel. A large aperture allows for a large axial coverage of the patient during the scan. Hence, by using a wider aperture, the total scanning time can be reduced if a large axial range of the patient needs to be imaged. The tradeoff, however, is that the amount of scatter also increases with the aperture, while the primary data stays the same. Without scatter correction, the increased scatter will negatively impact the image quality and quantitation.

Hardware-based scatter reduction includes the use of anti-scatter grids on the detector panel surface, the use of very narrow apertures, bow-tie filters, air separation between patient and detector, etc. A conventional anti-scatter grid can reduce the amount of x-ray scatter significantly. The main drawbacks are that the system is more complex, and a significant amount of primary data is also reduced. Using a very narrow aperture, the scatter can be reduced significantly (and to effectively a negligible level), however, the axial coverage is so small that the overall scanning time becomes impractical.

Software-based scatter reduction/correction can use physical models to estimate the scatter in the acquired data. These methods can model both a data acquisition system and the interaction process between x-rays and materials. The former requires detailed knowledge of the major components of the entire imaging chain as well as information of the patient, which may be obtained from a planning CT or a first-pass reconstruction without scatter correction. These methods can either be realized stochastically (e.g., Monte-Carlo-simulation based approaches) or deterministically (e.g., radiative-transfer-equation based approaches). The former is computationally costly, and the latter is generally considered as an open problem in the field. Model-based methods are typically patient specific and can be more accurate. However, these methods require a considerable amount of prior information on the data acquisition system and the patient, such that the effectiveness of these methods is highly dependent on the modeling accuracy. Furthermore, they are also highly demanding in terms of computational power and time resulting in a significant negative impact on workflow and throughput. The estimated scatter is then used to correct the data prior to image reconstruction or during image reconstruction.

Among software-based scatter correction approaches is kernel-based scatter estimation and correction. In the kernel-based approaches, a scatter kernel is determined through physical measurements or Monte Carlo simulation assuming a composite of materials. For example, one typical technique measures the scatter kernels with different thicknesses of water layers at given x-ray spectrum and apertures. The apertures, projected to the detector plane, can be as large as the panel's axial dimension. Once the kernels at different water layers are measured/determined, they are used for scatter correction in patient scans, assuming that the patient tissues are equivalent to the different thickness layers of water. The application of the kernels for scatter estimation and correction can include scatter deconvolution using the kernels, either in the space domain or in the frequency domain, and can be adaptive to local variation of the object. For example, measured scatter data can be considered a convolution result of the primary and the scatter kernels. A deconvolution process can be performed to separate the primary and scatter by using the appropriate kernels that are established ahead of time.

Kernel-based scatter estimation/correction is widely used for CBCT due to its simplicity. A fundamental challenge of this type of approach, however, is that the accuracy can degrade when the patient tissue distribution is highly non-uniform, especially in chest and pelvic regions. Furthermore, when the aperture size is large, the performance of the approach can also degrade based on the elevated scatter associated with the large aperture.

BRIEF SUMMARY

In one embodiment, an imaging apparatus includes a rotating imaging source for emitting a radiation beam, a detector positioned to receive radiation from the imaging source, and a beamformer configured to adjust a shape of the radiation beam emitted by the imaging source, such that the shape of the radiation beam is configured for a wide aperture scan of a wide axial region and a narrow aperture scan of a narrow axial region within the wide axial region, where an estimated scatter in the wide axial region is based on the projection data from the narrow axial region.

Features that are described and/or illustrated with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments.

The descriptions of the invention do not limit the words used in the claims in any way or the scope of the claims or invention. The words used in the claims have all of their full ordinary meanings.

