Louise Hauge Matzen

Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study

Publikation: KonferencebidragKonferenceabstrakt til konferenceForskningpeer review

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Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study. / Spin-Neto, Rubens; Schropp, Lars; Matzen, Louise Hauge; Sørensen, T.S.; Wenzel, Ann.

2018. 22 Abstract fra European Congress of DentoMaxilloFacial Radiology 2018, Luzern, Schweiz.

Publikation: KonferencebidragKonferenceabstrakt til konferenceForskningpeer review

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Spin-Neto, R, Schropp, L, Matzen, LH, Sørensen, TS & Wenzel, A 2018, 'Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study', European Congress of DentoMaxilloFacial Radiology 2018, Luzern, Schweiz, 13/06/2018 - 16/06/2018 s. 22.

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MLA

Spin-Neto, Rubens o.a.. Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study. European Congress of DentoMaxilloFacial Radiology 2018, 13 jun. 2018, Luzern, Schweiz, Konferenceabstrakt til konference, 2018. 1 s.

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Bibtex

@conference{0f97d22d35fa48a8964932b07e7093ed,
title = "Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study",
abstract = "AimTo assess the impact of head motion artefacts and an automated artefact-correction system on CBCT image quality andinterpretability for simulated diagnostic tasks.Material and MethodsA partially dentate human skull was mounted on a robot simulating four types of head movement (antero-posteriortranslation/APT, nodding/NOD, lateral rotation/ROT, and tremor/TRM), at three distances (0.75, 1.5, and 3 mm) basedon two movement patterns (skull returning/not returning to the initial position). Two diagnostic tasks were simulated:dental implant planning/IP, and detection of a periapical lesion/AP. Three CBCT units were used to examine the skullduring the movements and no-motion (control): Cranex 3Dx/CRA, Orthophos SL 3D/ORT, and the X1 without (X1wo)and with (X1wi) an automated motion artefact-correction system. Eighty-eight examinations were performed for eachdiagnostic task. Three observers, blinded to unit and movement, scored image quality: presence of stripe artefacts(present/absent), overall unsharpness (present/absent), and image interpretability (interpretable/non-interpretable).Kappa statistics assessed interobserver agreement, and descriptive statistics summarized the findings.ResultsInterobserver agreement for image interpretability was good (average kappa=0.68). Regarding IP, X1wi images wereinterpretable by all observers, while for the other units mainly the cases with TRM were non-interpretable. RegardingAP, besides TRM, some cases with APT, NOD, and ROT at 3 mm distance and the “not returning” pattern were also noninterpretablefor CRA, ORT, and X1wo. For X1wi, two observers scored 1.5 mm TRM and one observer scored 3 mm TRMas non-interpretable.ConclusionThe automated motion artefact-correction system significantly enhanced CBCT image quality and interpretability.",
author = "Rubens Spin-Neto and Lars Schropp and Matzen, {Louise Hauge} and T.S. S{\o}rensen and Ann Wenzel",
year = "2018",
language = "English",
pages = "22",
note = "null ; Conference date: 13-06-2018 Through 16-06-2018",
url = "http://www.ecdmfr.eu",

}

RIS

TY - ABST

T1 - Automated Motion Artefact Correction and the Impact on Cone Beam Computed Tomography Image Quality and Interpretability. An Ex Vivo Study

AU - Spin-Neto, Rubens

AU - Schropp, Lars

AU - Matzen, Louise Hauge

AU - Sørensen, T.S.

AU - Wenzel, Ann

N1 - Conference code: XVI

PY - 2018

Y1 - 2018

N2 - AimTo assess the impact of head motion artefacts and an automated artefact-correction system on CBCT image quality andinterpretability for simulated diagnostic tasks.Material and MethodsA partially dentate human skull was mounted on a robot simulating four types of head movement (antero-posteriortranslation/APT, nodding/NOD, lateral rotation/ROT, and tremor/TRM), at three distances (0.75, 1.5, and 3 mm) basedon two movement patterns (skull returning/not returning to the initial position). Two diagnostic tasks were simulated:dental implant planning/IP, and detection of a periapical lesion/AP. Three CBCT units were used to examine the skullduring the movements and no-motion (control): Cranex 3Dx/CRA, Orthophos SL 3D/ORT, and the X1 without (X1wo)and with (X1wi) an automated motion artefact-correction system. Eighty-eight examinations were performed for eachdiagnostic task. Three observers, blinded to unit and movement, scored image quality: presence of stripe artefacts(present/absent), overall unsharpness (present/absent), and image interpretability (interpretable/non-interpretable).Kappa statistics assessed interobserver agreement, and descriptive statistics summarized the findings.ResultsInterobserver agreement for image interpretability was good (average kappa=0.68). Regarding IP, X1wi images wereinterpretable by all observers, while for the other units mainly the cases with TRM were non-interpretable. RegardingAP, besides TRM, some cases with APT, NOD, and ROT at 3 mm distance and the “not returning” pattern were also noninterpretablefor CRA, ORT, and X1wo. For X1wi, two observers scored 1.5 mm TRM and one observer scored 3 mm TRMas non-interpretable.ConclusionThe automated motion artefact-correction system significantly enhanced CBCT image quality and interpretability.

AB - AimTo assess the impact of head motion artefacts and an automated artefact-correction system on CBCT image quality andinterpretability for simulated diagnostic tasks.Material and MethodsA partially dentate human skull was mounted on a robot simulating four types of head movement (antero-posteriortranslation/APT, nodding/NOD, lateral rotation/ROT, and tremor/TRM), at three distances (0.75, 1.5, and 3 mm) basedon two movement patterns (skull returning/not returning to the initial position). Two diagnostic tasks were simulated:dental implant planning/IP, and detection of a periapical lesion/AP. Three CBCT units were used to examine the skullduring the movements and no-motion (control): Cranex 3Dx/CRA, Orthophos SL 3D/ORT, and the X1 without (X1wo)and with (X1wi) an automated motion artefact-correction system. Eighty-eight examinations were performed for eachdiagnostic task. Three observers, blinded to unit and movement, scored image quality: presence of stripe artefacts(present/absent), overall unsharpness (present/absent), and image interpretability (interpretable/non-interpretable).Kappa statistics assessed interobserver agreement, and descriptive statistics summarized the findings.ResultsInterobserver agreement for image interpretability was good (average kappa=0.68). Regarding IP, X1wi images wereinterpretable by all observers, while for the other units mainly the cases with TRM were non-interpretable. RegardingAP, besides TRM, some cases with APT, NOD, and ROT at 3 mm distance and the “not returning” pattern were also noninterpretablefor CRA, ORT, and X1wo. For X1wi, two observers scored 1.5 mm TRM and one observer scored 3 mm TRMas non-interpretable.ConclusionThe automated motion artefact-correction system significantly enhanced CBCT image quality and interpretability.

M3 - Conference abstract for conference

SP - 22

Y2 - 13 June 2018 through 16 June 2018

ER -