Marker-less real-time intra-operative camera and hand-eye calibration procedure for surgical augmented reality.

augmented reality augmented reality rendering average target registration error biomedical optical imaging calibration camera calibration camera intrinsic matrix estimation cameras da Vinci robot endoscope endoscopes hand-eye calibration procedure hand-eye transformation high visual error image registration marker-less real-time intra-operative camera medical image processing medical robotics phantoms pre-operative medical data prostate phantom rendering (computer graphics) robot vision subsequent gradient descent steps surgery surgical augmented reality virtual rendered tool tip

Journal

Healthcare technology letters
ISSN: 2053-3713
Titre abrégé: Healthc Technol Lett
Pays: England
ID NLM: 101646459

Informations de publication

Date de publication:
Dec 2019
Historique:
received: 25 09 2019
accepted: 02 10 2019
entrez: 11 2 2020
pubmed: 11 2 2020
medline: 11 2 2020
Statut: epublish

Résumé

Accurate medical Augmented Reality (AR) rendering requires two calibrations, a camera intrinsic matrix estimation and a hand-eye transformation. We present a unified, practical, marker-less, real-time system to estimate both these transformations during surgery. For camera calibration we perform calibrations at multiple distances from the endoscope, pre-operatively, to parametrize the camera intrinsic matrix as a function of distance from the endoscope. Then, we retrieve the camera parameters intra-operatively by estimating the distance of the surgical site from the endoscope in less than 1 s. Unlike in prior work, our method does not require the endoscope to be taken out of the patient; for the hand-eye calibration, as opposed to conventional methods that require the identification of a marker, we make use of a rendered tool-tip in 3D. As the surgeon moves the instrument and observes the offset between the actual and the rendered tool-tip, they can select points of high visual error and manually bring the instrument tip to match the virtual rendered tool tip. To evaluate the hand-eye calibration, 5 subjects carried out the hand-eye calibration procedure on a da Vinci robot. Average Target Registration Error of approximately 7mm was achieved with just three data points.

Identifiants

pubmed: 32038867
doi: 10.1049/htl.2019.0094
pii: HTL.2019.0094
pmc: PMC6952262
doi:

Types de publication

Journal Article

Langues

eng

Pagination

255-260

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Auteurs

Megha Kalia (M)

Robotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.
Computer Aided Medical Procedures, Technical University of Munich, Boltzmannstraße 15, 85748 Garching bei Múnchen, Germany.

Prateek Mathur (P)

Robotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.

Nassir Navab (N)

Computer Aided Medical Procedures, Technical University of Munich, Boltzmannstraße 15, 85748 Garching bei Múnchen, Germany.

Septimiu E Salcudean (SE)

Robotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.

Classifications MeSH