A preliminary investigation of local tomography for megavoltage CT imaging

Anastasio, Mark A.; Shi, Daxin; Pan, Xiaochuan; Pelizzari, Charles A.; Munro, Peter

doi:10.1118/1.1619232

Cited by 22 publications

(20 citation statements)

References 34 publications

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“…Thus the 1 = m algorithm has less restrictive data requirements than the 0 = m case. In some cases therefore we might expect local tomography ( 1 = m ) to provide more useful information than the global ( 0 = m ) algorithm (Anastasio et al 2003).…”

Section: Global and Local Reconstruction For Vmat-ctmentioning

confidence: 99%

CT reconstruction from portal images acquired during volumetric-modulated arc therapy

Poludniowski¹,

Thomas²,

Evans³

et al. 2010

Phys. Med. Biol.

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Abstract. Volumetric Modulated Arc Therapy (VMAT), a form of Intensity Modulated Arc Therapy (IMAT), has become a topic of research and clinical activity in recent years. As a form of arc therapy, portal images acquired during the treatment fraction form a (partial) Radon transform of the patient. We show that these portal images, when used in a modified global cone-beam Filtered Back-Projection (FBP) algorithm, allow a surprisingly recognizable CT-volume to be reconstructed. The possibility of distinguishing anatomy in such VMAT-CT reconstructions, suggests that this could prove to be a valuable treatment position-verification tool. Further, some potential for local-tomography techniques to improve image quality is shown.

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Section: Global and Local Reconstruction For Vmat-ctmentioning

confidence: 99%

CT reconstruction from portal images acquired during volumetric-modulated arc therapy

Poludniowski¹,

Thomas²,

Evans³

et al. 2010

Phys. Med. Biol.

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“…As such, the two-dimensional Fourier transform of the Lambda tomographic image is equal to that of the conventional tomographic image with a radial ramp filtering. [35][36][37][38] It should be noted that a ramp filtered conventional tomographic image is actually equivalent to an Hilbert transform of the differentiated conventional tomographic image. 32 It should also be noted that another local tomography image reconstruction algorithm called local BPF algorithm 39 has been proposed in the literature, in which the projection data go through a 1st-order differentiation, backprojection onto chords and then another 1st-order differentiation along the chords.…”

Section: Discussionmentioning

confidence: 99%

“…[35][36][37][38][39][40] In general, the Lambda tomography is under the framework of local tomography, in which the algorithm for image reconstruction is in the fashion of FBP. Specifically, in the Lambda tomography, the projection data undergo a 2nd-order differentiation that is mathematically local and then are backprojected to form a tomographic image.…”

Section: Discussionmentioning

confidence: 99%

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Radial differential interior tomography and its image reconstruction with differentiated backprojection and projection onto convex sets

Tang

2013

Medical Physics

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Purpose: Interior tomography has been recognized as one of the most effective approaches in computed tomography (CT) to reduce radiation dose rendered to patients. In this work, the authors propose and evaluate an imaging method of radial differential interior tomography. Methods: In interior tomography, an x-ray beam is collimated to only irradiate the region of interest (ROI) with suspected lesions while the surrounding area/volume of normal tissues/organs is spared. In the proposed imaging method of radial differential interior tomography, the outcome is a ROI image that has gone through a radial differential filtering. The image reconstruction algorithm for the radial differential interior tomography is kept in the fashion of differentiated backprojection and projection onto convex sets, but the required a priori knowledge in a small round area becomes zero and may be more readily available in practice. Results: Using the projection data simulated by computer and acquired by CT scanner, the authors evaluate and verify the performance of the proposed radial differential interior tomography method and its associated image reconstruction algorithm. The preliminary results show that the proposed imaging method can generate an image that is the radial differentiation of a conventional tomographic image and is robust over noise that inevitably exist in practice. Conclusions: It is believed that the proposed imaging method may find its utility in advanced clinical applications wherein a ROI-based image processing and analysis is required for lesion visualization, characterization, and diagnosis.

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“…It is well known that an accurate and stable reconstruction of a 3D object function cannot be achieved from local data [1]. A number of Lambda tomography algorithms were previously developed to recover gradient-like information from local data [2][3][4][5][6][7][8][9][10]. In this paper, we present some novel ideas and formulas for skew lambda tomography (SLT).…”

Section: Introductionmentioning

confidence: 99%

Skew cone beam lambda tomography

Wang

2006

SPIE Proceedings

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In this paper, we for the first time define the concept of 3D skew lambda tomography (SLT) based on the 3D Calderon Operator, and formulate an approximate local reconstruction algorithm for cone beam data collected along an arbitrary scanning curve. The main idea is to rewrite the filtering operator in an exact filtered-backprojection reconstruction formula as a local projection. While the practical cone-beam lambda tomography works well for spirals with small pitches, the proposed SLT is more suitable to the spirals with large pitch. Simulation using the 3D differentiable SheppLogan phantom is performed to demonstrate the utility of this new technique.

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A preliminary investigation of local tomography for megavoltage CT imaging

Cited by 22 publications

References 34 publications

CT reconstruction from portal images acquired during volumetric-modulated arc therapy

CT reconstruction from portal images acquired during volumetric-modulated arc therapy

Radial differential interior tomography and its image reconstruction with differentiated backprojection and projection onto convex sets

Skew cone beam lambda tomography

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