ArticleInternational journal of computer assisted radiology and surgery2016
Precise 3D/2D calibration between a RGB-D sensor and a C-arm fluoroscope.
Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 7 citations in OpenAlex.
- Toward an End-to-End Calibration for Mobile C-Arm in Combination with a Depth Sensor for Surgical Augmented Reality Applications.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeCalibration and registration are the first steps for augmented reality and mixed reality applications. In the medical field, the calibration between an RGB-D camera and a C-arm fluoroscope is a new topic which introduces challenges.
methodA convenient and efficient calibration phantom is designed by combining the traditional calibration object of X-ray images with a checkerboard plane. After the localization of the 2D marker points in the X-ray images and the corresponding 3D points from the RGB-D images, we calculate the projection matrix from the RGB-D sensor coordinates to the X-ray, instead of estimating the extrinsic and intrinsic parameters simultaneously. VALIDATION: In order to evaluate the effect of every step of our calibration process, we performed five experiments by combining different steps leading to the calibration. We also compared our calibration method to Tsai's method to evaluate the advancement of our solution. At last, we simulated the process of estimating the rotation movement of the RGB-D camera using MATLAB and demonstrate that calculating the projection matrix can reduce the angle error of the rotation.
resultsA RMS reprojection error of 0.5 mm is achieved using our calibration method which is promising for surgical applications. Our calibration method is more accurate when compared to Tsai's method. Lastly, the simulation result shows that using a projection matrix has a lower error than using intrinsic and extrinsic parameters in the rotation estimation.
conclusionsWe designed and evaluated a 3D/2D calibration method for the combination of a RGB-D camera and a C-arm fluoroscope.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.