Evidence map›Paper›PMID 27434396›Full record

ArticlePloS one2016

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

Bartlomiej Pycinski, Joanna Czajkowska, Pawel Badura, Jan Juszczyk, Ewa Pietka

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Video-based postural alignment improves accuracy of breath hold treatment delivery in breast cancer patients.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2026
    Article
  2. Adaptive infrared patterns for microscopic surface reconstructions.International journal of computer assisted radiology and surgery · 2024
    Article
  3. Article
  4. Recent advanced in Surface Guided Radiation Therapy.Radiation oncology (London, England) · 2020
    Review
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

5 authors at 1 institution in 1 country.

Bartlomiej PycinskiFaculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.ORCID http://orcid.org/0000-0002-6634-4127
Joanna CzajkowskaFaculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.
Pawel BaduraFaculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.
Jan JuszczykFaculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.
Ewa PietkaFaculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland.
Silesian University of Technology · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeA growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed.

methodsWe present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm.

resultsThe experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera.

conclusionThe obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

Indexed as

Electronic Data ProcessingImage Processing, Computer-AssistedAlgorithmsCalibrationHumansImaging, Three-DimensionalPatient PositioningPhantoms, ImagingSurgery, Computer-AssistedTomography, X-Ray ComputedVideo-Assisted Surgery

Identifiers

PMID27434396
PMCPMC4951045
OpenAlexW2488831156

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.