Analytic Calibration of Cone-Beam Scanners

Strubel, G.; Clackdoyle, Rolf; Mennessier, Catherine; Noo, Frédéric

doi:10.1109/nssmic.2005.1596901

Cited by 10 publications

(17 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The methods suggested in the literature range in their approaches and mathematical formulation, but they are founded in geometrical descriptions relating the 3D position of the physical phantom to the measured image of the phantom at the detector. They can be broadly classified into two approaches, those based on non‐linear optimization 65,66 and those based on a direct analytical solution 48,50–52,67,68 . Additionally, the suggested calibration phantoms are specific to the derived method and vary in shape, marker size, and number of markers.…”

Section: System Calibrationmentioning

confidence: 99%

AAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*

et al. 2023

View full text Add to dashboard Cite

This report reviews the image acquisition and reconstruction characteristics of C‐arm Cone Beam Computed Tomography (C‐arm CBCT) systems and provides guidance on quality control of C‐arm systems with this volumetric imaging capability. The concepts of 3D image reconstruction, geometric calibration, image quality, and dosimetry covered in this report are also pertinent to CBCT for Image‐Guided Radiation Therapy (IGRT). However, IGRT systems introduce a number of additional considerations, such as geometric alignment of the imaging at treatment isocenter, which are beyond the scope of the charge to the task group and the report.Section 1 provides an introduction to C‐arm CBCT systems and reviews a variety of clinical applications. Section 2 briefly presents nomenclature specific or unique to these systems. A short review of C‐arm fluoroscopy quality control (QC) in relation to 3D C‐arm imaging is given in Section 3. Section 4 discusses system calibration, including geometric calibration and uniformity calibration. A review of the unique approaches and challenges to 3D reconstruction of data sets acquired by C‐arm CBCT systems is give in Section 5. Sections 6 and 7 go in greater depth to address the performance assessment of C‐arm CBCT units. First, Section 6 describes testing approaches and phantoms that may be used to evaluate image quality (spatial resolution and image noise and artifacts) and identifies several factors that affect image quality. Section 7 describes both free‐in‐air and in‐phantom approaches to evaluating radiation dose indices.The methodologies described for assessing image quality and radiation dose may be used for annual constancy assessment and comparisons among different systems to help medical physicists determine when a system is not operating as expected. Baseline measurements taken either at installation or after a full preventative maintenance service call can also provide valuable data to help determine whether the performance of the system is acceptable. Collecting image quality and radiation dose data on existing phantoms used for CT image quality and radiation dose assessment, or on newly developed phantoms, will inform the development of performance criteria and standards. Phantom images are also useful for identifying and evaluating artifacts. In particular, comparing baseline data with those from current phantom images can reveal the need for system calibration before image artifacts are detected in clinical practice. Examples of artifacts are provided in Sections 4, 5, and 6.

show abstract

Section: System Calibrationmentioning

confidence: 99%

AAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*

et al. 2023

View full text Add to dashboard Cite

show abstract

“…In the second scenario, the geometry of the CT system is estimated directly from images for example as in references [8][9][10]. In this case, the presence of a physical misalignment is not necessarily a problem.…”

Section: Actual Ct System Geometrymentioning

confidence: 99%

Characterization of the effects of detector angular misalignments and accuracy enhancement of X-ray CT dimensional measurements

Aloisi¹,

Schlecht²,

Ferley³

et al. 2019

eJNDT

View full text Add to dashboard Cite

Fundamental requirements for using X-ray computed tomography (CT) systems as coordinate measuring systems (CMSs) for traceable coordinate metrology are the study of measurement accuracy and the establishment of traceability to the unit of length, the meter. Due to their complex nature, CT scanning technology and thus CT measurements are affected by multiple error sources that complexly interact in the measurement chain. The German guideline VDI/VDE 2630-part 1.2 [1] provides a detailed description of the factors influencing CT dimensional measurements. Examples of these influence factors are CT scanning parameters, work-piece properties (e.g. material, size, surface roughness), geometrical errors, software and data processing etc. Because of the multitude of these influencing quantities and the complexity and non-linearity of their interaction, CT measurements traceability is a major challenge for metrological applications. In particular, the assessment of measurement uncertainty, which is essential for traceability establishment, is one of the most critical tasks. Among the influence factors affecting CT measurement chain, the study and analysis of CT system geometrical errors is of primary importance [2-6]. As for most precision measuring instruments, the design of a CT system involves the assembly of several components, the most important of which are the X-ray source, the rotary table and the detector. The determination of the CT system geometry is a crucial step on which all the following steps in the measurement chain rely on. In fact, the system geometry provides the necessary information to fully describe the geometry of data acquisition and performing the tomographic reconstruction on which all the dimensional analyses are based. An error in the determination of the CT system geometry (i.e. geometric set-up) or the presence of geometrical errors not accounted for during the reconstruction affect all the subsequent steps in the measurement chain and could lead to artifacts, distortions and measurement errors in the reconstructed volume [2]. It is evident, therefore, that it is extremely important to investigate and quantify the influence of CT system geometrical errors on CT measurements. In general, no coordinate measuring system is constructed and aligned perfectly. In an ideal perfectly aligned CT system (see Figure 1), the X-ray focal spot center (the vertex of X-ray cone), the center of rotation and the detector center are positioned on a straight line. This line is perpendicular to the detector surface on its center and coincides with the central ray (i.e. the X-ray path on the central plane of the cone that goes perpendicularly from the focal spot center to the center of the detector). Moreover, the rotation axis is perpendicular to the line containing the center of rotation, the X-ray focal spot and the detector center, while its projection is parallel to the detector columns [2]. In real practice, however, it is not possible to reach the perfect alignment conditions described above and some residual errors between the three components will be present in the system geometry [2]. In a real CT system, the actual geometry therefore will be affected by the presence of geometrical misalignments. Any discrepancy between the actual system geometry and the geometry used in the reconstruction phase (i.e. the use of an incorrect CT system geometry for reconstruction) will lead to the presence of artifacts, distortions and measurement errors. Therefore, the presence of geometrical misalignments and/or the wrong estimation of the system geometry could have a strong impact on the reconstructed volume leading to artifacts and distortions, and to measurement errors for metrological applications [2, 6]. Thus, it is of fundamental importance to study the effects of geometrical misalignments on CT measurements and to determine the sensitivity of measurements to the different misalignments. In reference [4], Kumar et al. investigated the influence of specific geometrical errors on simulated ball bars showing that they can have significant impact on CT data. In reference [5], Ferrucci et al. studied different simulated detector angular misalignments of 1°, 2°, 5° and 10°, showing that – depending on the kind of misalignments – significant distortions might be present in the CT volume. In this work, different sets of CT experimental investigations, performed with CMM calibrated reference objects, were specifically designed to investigate the effects of CT system detector angular misalignments on CT measurement results. Different detector angular misalignments were purposefully induced on a flat panel detector in order to determine the effects of detector pitch, yaw and roll on CT measurements (i.e. respectively θ, γ, η in Figure 1). Repeated CT scans of CMM calibrated reference objects were acquired with a NSI metrological CT system in both the aligned and purposefully misaligned configurations. For each detector misalignment (i.e. pitch, yaw and roll), three amplitudes of the misalignment were physically induced on the flat-panel detector in order to study the sensitivity of CT measurement errors to the particular type of detector misalignment. For each of the nine misaligned configurations considered in the study, sphere center-to-center distance errors, sphere diameter errors and sphere form errors were calculated and compared to the reference CMM measurements. The influence of the object positioning and measurement direction on the CT measurement errors caused by a misaligned detector were also studied in order to fully characterize the measurement errors in presence of a purposefully misaligned detector. This is of primary importance to enhance CT measurement accuracy. After characterizing and providing a description of the effects produced by each detector angular misalignment on CT measurement results, the paper shows results from an automatic method that effectively corrects for detector misalignments physically present on the CT system hardware. NSI proprietary reconstruction software efX CT, featuring an in house developed algorithm capable of correcting for detector misalignments, was used for the reconstruction of CT scans and it is demonstrated how a significant enhancement of CT measurement accuracy is obtained.

show abstract

“…Only some take outof-plane rotations into account. [1][2][3][4][5][6][7][8] Common to all of these methods is the need for a priori information about the used calibration phantom. It has been demonstrated that very precisely fabricated phantoms allow for robust calibration even of in-lab C-arm devices yielding a high spatial resolution of the reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Auto calibration of a cone‐beam‐CT

et al. 2012

View full text Add to dashboard Cite

The method introduced here makes no requirements on the accuracy of the test object. In contrast to many previous autocalibration methods their approach also includes out-of-plane rotations of the detector. Although assuming a perfect rotation, the method seems to be sufficiently accurate for a commercial CBCT scanner. For devices which require higher dimensional geometry models, the method could be used as a initial calibration procedure.

show abstract

Analytic Calibration of Cone-Beam Scanners

Cited by 10 publications

References 11 publications

AAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*

AAPM Task Group Report 238: 3D C‐arms with volumetric imaging capability*

Characterization of the effects of detector angular misalignments and accuracy enhancement of X-ray CT dimensional measurements

Auto calibration of a cone‐beam‐CT

Contact Info

Product

Resources

About