Evidence map›Paper›PMID 39133431›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

A dual-instrument Kalman-based tracker to enhance robustness of microsurgical tools tracking.

Mattia Magro, Nicola Covallero, Elena Gambaro, Emanuele Ruffaldi, Elena De Momi

Abstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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.

Mattia MagroDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy. mattia.magro@polimi.it.ORCID http://orcid.org/0000-0003-4385-9416
Nicola CovalleroMedical Microinstruments, Inc., Wilmington, USA.
Elena GambaroMedical Microinstruments, Inc., Wilmington, USA.
Emanuele RuffaldiMedical Microinstruments, Inc., Wilmington, USA.
Elena De MomiDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe integration of a surgical robotic instrument tracking module within optical microscopes holds the potential to advance microsurgery practices, as it facilitates automated camera movements, thereby augmenting the surgeon's capability in executing surgical procedures.

methodsIn the present work, an innovative detection backbone based on spatial attention module is implemented to enhance the detection accuracy of small objects within the image. Additionally, we have introduced a robust data association technique, capable to re-track surgical instrument, mainly based on the knowledge of the dual-instrument robotics system, Intersection over Union metric and Kalman filter.

resultsThe effectiveness of this pipeline was evaluated through testing on a dataset comprising ten manually annotated videos of anastomosis procedures involving either animal or phantom vessels, exploiting the Symani®Surgical System-a dedicated robotic platform designed for microsurgery. The multiple object tracking precision (MOTP) and the multiple object tracking accuracy (MOTA) are used to evaluate the performance of the proposed approach, and a new metric is computed to demonstrate the efficacy in stabilizing the tracking result along the video frames. An average MOTP of 74±0.06% and a MOTA of 99±0.03% over the test videos were found.

conclusionThese results confirm the potential of the proposed approach in enhancing precision and reliability in microsurgical instrument tracking. Thus, the integration of attention mechanisms and a tailored data association module could be a solid base for automatizing the motion of optical microscopes.

Indexed as

MicrosurgeryAlgorithmsAnastomosis, SurgicalAnimalsHumansPhantoms, ImagingRobotic Surgical ProceduresDeep learningDetectionKalman filterMicrosurgeryTracking

Identifiers

PMID39133431
PMCPMC11607016

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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.