Literature DB >> 26854687

Extended ellipse-line-ellipse trajectory for long-object cone-beam imaging with a mounted C-arm system.

Zhicong Yu1, Günter Lauritsch, Frank Dennerlein, Yanfei Mao, Joachim Hornegger, Frédéric Noo.   

Abstract

Recent reports show that three-dimensional cone-beam (CB) imaging with a floor-mounted (or ceiling-mounted) C-arm system has become a valuable tool in interventional radiology. Currently, a circular short scan is used for data acquisition, which inevitably yields CB artifacts and a short coverage in the direction of the patient table. To overcome these two limitations, a more sophisticated data acquisition geometry is needed. This geometry should be complete in terms of Tuy's condition and should allow continuous scanning, while being compatible with the mechanical constraints of mounted C-arm systems. Additionally, the geometry should allow accurate image reconstruction from truncated data. One way to ensure such a feature is to adopt a trajectory that provides full R-line coverage within the field-of-view (FOV). An R-line is any segment of line that connects two points on a source trajectory, and the R-line coverage is the set of points that belong to an R-line. In this work, we propose a novel geometry called the extended ellipse-line-ellipse (ELE) for long-object imaging with a mounted C-arm system. This trajectory is built from modules consisting of two elliptical arcs connected by a line. We demonstrate that the extended ELE can be configured in many ways so that full R-line coverage is guaranteed. Both tight and relaxed parametric settings are presented. All results are supported by extensive mathematical proofs provided in appendices. Our findings make the extended ELE trajectory attractive for axially-extended FOV imaging in interventional radiology.

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Year:  2016        PMID: 26854687     DOI: 10.1088/0031-9155/61/4/1829

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  2 in total

1.  Task-driven source-detector trajectories in cone-beam computed tomography: I. Theory and methods.

Authors:  J Webster Stayman; Sarah Capostagno; Grace J Gang; Jeffrey H Siewerdsen
Journal:  J Med Imaging (Bellingham)       Date:  2019-05-02

2.  Fast CBCT Reconstruction using Convolutional Neural Networks for Arbitrary Robotic C-arm Orbits.

Authors:  Tom Russ; Yiqun Q Ma; Alena-Kathrin Golla; Dominik F Bauer; Tess Reynolds; Christian Tönnes; Sepideh Hatamikia; Lothar R Schad; Frank G Zöllner; Grace J Gang; Wenying Wang; J Webster Stayman
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04
  2 in total

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