Multi-target Attachment for Surgical Instrument Tracking

Benjumea, Eberto; Sierra, Juan S.; Meza, Jhacson; Marrugo, Andrés G.

doi:10.1007/978-3-030-77004-4_33

Cited by 2 publications

(1 citation statement)

References 16 publications

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“…To avoid this limitation, self-identifying markers are utilized, see Figure 1d. Eberto et al [15] fixed a cube to the instrument end, and each face of the cube is attached with an ARTag [16]. Wang et al [17] stacked similar tags into a composite marker field, which is used to code a handpiece surface.…”

Section: Introductionmentioning

confidence: 99%

Distributed visual positioning for surgical instrument tracking

Cai,

Zhu,

et al. 2024

Phys Eng Sci Med

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In clinical operations, it is crucial for surgeons to know the location of the surgical instrument. Traditional positioning systems have difficulty dealing with camera occlusion, marker occlusion, and environmental interference. To address these issues, we propose a distributed visual positioning system for surgical instrument tracking in surgery. First, we design the marker pattern with a black and white triangular grid and dot that can be adapted to various instrument surfaces and improve the marker location accuracy of the feature. The cross-points in the marker are the features that each feature has a unique ID. Furthermore, we proposed detection and identification for the position-sensing marker to realize the accurate location and identification of features. Second, we introduce mPnP (multi Perspective-n-Point) method, which fuses feature coordinates from all cameras to deduce the final result directly by the intrinsic and extrinsic parameters. This method provides a reliable initial value for the Bundle Adjustment algorithms. During instrument tracking, we assess the motion state of the instrument and select either dynamic or static Kalman filtering to mitigate any jitter in the instrument's movement. The core algorithms comparison experiment indicates our positioning algorithm has a lower reprojection error comparison to the mainstream algorithms. A series of quantitative experiments showed that the proposed system positioning error is below 0.207 mm, and the run time is below 118.842 ms. The results demonstrate 1 Manuscript the tremendous clinical application potential of our system providing accurate positioning of instruments promoting the efficiency and safety of clinical surgery.

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Section: Introductionmentioning

confidence: 99%

Distributed visual positioning for surgical instrument tracking

Cai,

Zhu,

et al. 2024

Phys Eng Sci Med

View full text Add to dashboard Cite

show abstract

Distributed Visual Positioning for Surgical Instrument Tracking

Yu,

Zhu,

et al. 2023

Preprint

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In clinical operations, it is crucial for surgeons to know the location of the surgical instrument. Traditional positioning systems have difficulty dealing with camera occlusion, marker occlusion, and environmental interference.To address these issues, we propose a distributed visual positioning system for surgical instrument tracking in surgery.First, we design the marker pattern with a black and white triangular grid and dot that can be adapted to various instrument surfaces and improve the marker location accuracy of the feature.The cross-points in the marker are the features that each feature has a unique ID.Furthermore, we proposed detection and identification for the position-sensing marker to realize the accurate location and identification of features.Second, we introduce mPnP (multi Perspective-n-Point) method, which fuses feature coordinates from all cameras to deduce the final result directly by the intrinsic and extrinsic parameters.This method provides a reliable initial value for the Bundle Adjustment algorithms.During instrument tracking, we assess the motion state of the instrument and select either dynamic or static Kalman filtering to mitigate any jitter in the instrument's movement.The core algorithms comparison experiment indicates our positioning algorithm has a lower reprojection error comparison to the mainstream algorithms.A series of quantitative experiments showed that the proposed system positioning error is below 0.207 mm, and the run time is below 118.842 ms.T he results demonstrate the tremendous clinical application potential of our system providing accurate positioning of instruments promoting the efficiency and safety of clinical surgery.

show abstract

Multi-target Attachment for Surgical Instrument Tracking

Cited by 2 publications

References 16 publications

Distributed visual positioning for surgical instrument tracking

Distributed visual positioning for surgical instrument tracking

Distributed Visual Positioning for Surgical Instrument Tracking

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