Evidence map›Paper›PMID 32038867›Full record

ArticleHealthcare technology letters2019

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

Megha Kalia, Prateek Mathur, Nassir Navab, Septimiu E Salcudean

Abstract read
In one paragraph

Article in Healthcare technology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Megha KaliaRobotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.
Prateek MathurRobotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.ORCID 0000-0001-9588-8521
Nassir NavabComputer Aided Medical Procedures, Technical University of Munich, Boltzmannstraße 15, 85748 Garching bei Múnchen, Germany.
Septimiu E SalcudeanRobotics and Control Lab, Electrical and Computer Engineering, University of British Columbia, 2329 West Mall, Vancouver, BC V6T 1Z4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

augmented realityaugmented reality renderingaverage target registration errorbiomedical optical imagingcalibrationcamera calibrationcamera intrinsic matrix estimationcamerasda Vinci robotendoscopeendoscopeshand-eye calibration procedurehand-eye transformationhigh visual errorimage registrationmarker-less real-time intra-operative cameramedical image processingmedical roboticsphantomspre-operative medical dataprostate phantomrendering (computer graphics)robot visionsubsequent gradient descent stepssurgerysurgical augmented realityvirtual rendered tool tip

Identifiers

PMID32038867
PMCPMC6952262

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.