TU Darmstadt / ULB / TUbiblio

Patient Positioning with X-ray Detector Self-calibration for Image Guided Therapy

Selby, Peter ; Sakas, Georgios ; Groch, Wolfgang-Dieter ; Stilla, Uwe (2011)
Patient Positioning with X-ray Detector Self-calibration for Image Guided Therapy.
In: Australasian Physical & Engineering Sciences in Medicine, 34 (3)
doi: 10.1007/s13246-011-0090-4
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Automatic alignment estimation from projection images has a range of applications, but misaligned cameras induce inaccuracies. Calibration methods for optical cameras requiring calibration bodies or detectable features have been a matter of research for years. Not so for image guided therapy, although exact patient pose recovery is crucial. To image patient anatomy, X-ray instead of optical equipment is used. Feature detection is often infeasible. Furthermore, a method not requiring a calibration body, usable during treatment, would be desirable to improve accuracy of the patient alignment. We present a novel approach not relying on image features but combining intensity based calibration with 3D pose recovery. A stereoscopic X-ray camera model is proposed, and effects of erroneous parameters on the patient alignment are evaluated. The relevant camera parameters are automatically computed by comparison of X-ray to CT images and are incorporated in the patient alignment computation. The methods were tested with ground truth data of an anatomic phantom with artificially produced misalignments and available real-patient images from a particle therapy machine. We show that our approach can compensate patient alignment errors through mis-calibration of a camera from more than 5 mm to below 0.2 mm. Usage of images with artificial noise shows that the method is robust against image degradation of 2-5. X-ray camera selfcalibration improves accuracy when cameras are misaligned. We could show that rigid body alignment was computed more accurately and that self-calibration is possible, even if detection of corresponding image features is not.

Typ des Eintrags: Artikel
Erschienen: 2011
Autor(en): Selby, Peter ; Sakas, Georgios ; Groch, Wolfgang-Dieter ; Stilla, Uwe
Art des Eintrags: Bibliographie
Titel: Patient Positioning with X-ray Detector Self-calibration for Image Guided Therapy
Sprache: Englisch
Publikationsjahr: 2011
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Australasian Physical & Engineering Sciences in Medicine
Jahrgang/Volume einer Zeitschrift: 34
(Heft-)Nummer: 3
DOI: 10.1007/s13246-011-0090-4
Kurzbeschreibung (Abstract):

Automatic alignment estimation from projection images has a range of applications, but misaligned cameras induce inaccuracies. Calibration methods for optical cameras requiring calibration bodies or detectable features have been a matter of research for years. Not so for image guided therapy, although exact patient pose recovery is crucial. To image patient anatomy, X-ray instead of optical equipment is used. Feature detection is often infeasible. Furthermore, a method not requiring a calibration body, usable during treatment, would be desirable to improve accuracy of the patient alignment. We present a novel approach not relying on image features but combining intensity based calibration with 3D pose recovery. A stereoscopic X-ray camera model is proposed, and effects of erroneous parameters on the patient alignment are evaluated. The relevant camera parameters are automatically computed by comparison of X-ray to CT images and are incorporated in the patient alignment computation. The methods were tested with ground truth data of an anatomic phantom with artificially produced misalignments and available real-patient images from a particle therapy machine. We show that our approach can compensate patient alignment errors through mis-calibration of a camera from more than 5 mm to below 0.2 mm. Usage of images with artificial noise shows that the method is robust against image degradation of 2-5. X-ray camera selfcalibration improves accuracy when cameras are misaligned. We could show that rigid body alignment was computed more accurately and that self-calibration is possible, even if detection of corresponding image features is not.

Freie Schlagworte: Business Field: Virtual engineering, Research Area: Confluence of graphics and vision, Camera calibration, Patient positioning, Radiation therapies, X-ray, Computed tomography (CT)
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 12 Nov 2018 11:16
Letzte Änderung: 12 Nov 2018 11:16
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen