Fiber-Optic Fabry-Pérot Interferometers for Axial Force Sensing on the Tip of a Needle

Beekmans, Steven V.; Lembrechts, Thomas; Dobbelsteen, John J. van den; Gerwen, Dennis van

doi:10.3390/s17010038

Cited by 15 publications

(14 citation statements)

References 24 publications

(28 reference statements)

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“…In contrast, fiber optical force sensors are small, largely biocompatible, and not affected by electromagnetic interference, i.e., they are MRI-compatible [2]. Therefore, sensors based on Fabry-Pérot interferometry [2] or Fiber Bragg Gratings [8] have been proposed. Although these approaches have shown promising calibration results, they are rarely validated with tissue experiments [9] and manufacturing and signal processing can be difficult, e.g., when the fibers are subjected to varying temperatures or lateral forces.…”

Section: Introductionmentioning

confidence: 99%

“…The axial force acting on the tip is inferred from the epoxy layer's deformation observed in a series of A-scans. We can tailor our method to specific application scenarios by using softer epoxy resin for higher sensitivity, as required for microsurgery, or stiffer epoxy resin for larger forces, e.g., as occurring during biopsies [2]. Generally, our approach is flexible and easy to manufacture as the epoxy material is interchangeable, the cone shape can be varied, and no accurate fiber placement is required.…”

Section: Introductionmentioning

confidence: 99%

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Needle Tip Force Estimation Using an OCT Fiber and a Fused convGRU-CNN Architecture

Gessert

Priegnitz

Saathoff

et al. 2018

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

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Needle insertion is common during minimally invasive interventions such as biopsy or brachytherapy. During soft tissue needle insertion, forces acting at the needle tip cause tissue deformation and needle deflection. Accurate needle tip force measurement provides information on needle-tissue interaction and helps detecting and compensating potential misplacement. For this purpose we introduce an image-based needle tip force estimation method using an optical fiber imaging the deformation of an epoxy layer below the needle tip over time. For calibration and force estimation, we introduce a novel deep learning-based fused convolutional GRU-CNN model which effectively exploits the spatio-temporal data structure. The needle is easy to manufacture and our model achieves a mean absolute error of 1.76 ± 1.50 mN with a cross-correlation coefficient of 0.9996, clearly outperforming other methods. We test needles with different materials to demonstrate that the approach can be adapted for different sensitivities and force ranges. Furthermore, we validate our approach in an ex-vivo prostate needle insertion scenario.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Needle Tip Force Estimation Using an OCT Fiber and a Fused convGRU-CNN Architecture

Gessert

Priegnitz

Saathoff

et al. 2018

Medical Image Computing and Computer Assisted Intervention – MICCAI 2018

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show abstract

“…Su et al presented a miniature fiber-optic force sensor that is compatible with magnetic resonance imaging using FPI [31]. Beekmans et al presented a force sensing needle that is integrated with a fiber-optic FPI on the tip [32]. Szczerska and Majchrowicz presented an FPI with thin ZnO layers deposited on on the end faces of the fiber-optic to form a cavity, and demonstrated its feasibility as a temperature sensor [33,34].…”

Section: Fabry-perot Interferometer (Fpi)mentioning

confidence: 99%

Modular Optic Force Sensor for a Surgical Device Using a Fabry–Perot Interferometer

et al. 2019

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The ability to sense force in surgery is in high demand in many applications such asforce feedback in surgical robots and remote palpation (e.g., tumor detection in endoscopic surgery).In addition, recording and analyzing surgical data is of substantial value in terms of evidence-basedmedicine. However, force sensing in surgery remains challenging because of the specific requirementsof surgical instruments, namely, they must be small, bio-compatible, sterilizable, and tolerant tonoise. In this study, we propose a modular optic force sensor using a Fabry–Perot interferometer thatcan be used on surgical devices. The the proposed sensor can be implemented like a strain gauge,which is widely used in industrial applications but not compatible with surgery. The proposed sensorincludes two key elements, a fiber-optic pressure sensor using a Fabry–Perot interferometer thatwas previously developed by one of the authors and a structure that includes a carbide pin thatcontacts the pressure sensor along the long axis. These two elements are fixed in a guide channelfabricated in a 3 × 2 × 0.5 mm sensor housing. The experimental results are promising, revealinga linear relationship between the output and the applied load while showing a linear temperaturecharacteristic that suggests temperature compensation will be needed in use.

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“…For these reasons, fiber optical force sensors have been developed which are often smaller, biocompatible and MRI-compatible [7]. In particular, sensor concepts using Fabry-Pérot interferometry [8,7] or Fiber Bragg Gratings [9,10,11] have been proposed. These methods have shown promising calibration results, however, manufacturing and signal processing can be difficult when different temperature ranges and lateral forces need to be taken into account.…”

Section: Introductionmentioning

confidence: 99%

“…In general, this needle design is easy to manufacture and flexible as no precise fiber placement is required, the needle tip's shape can be changed and the epoxy layer's thickness and composition can be varied. Thus, softer epoxy resin could be used for application scenarios which require a high sensitivity such as microsurgery and stiffer epoxy resin could be used for large forces which occur, e.g., during biopsy [7]. However, this approach comes with challenges for calibration and force estimation.…”

Section: Introductionmentioning

confidence: 99%

Spatio-temporal deep learning models for tip force estimation during needle insertion

et al. 2019

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PurposePrecise placement of needles is a challenge in a number of clinical applications such as brachytherapy or biopsy. Forces acting at the needle cause tissue deformation and needle deflection which in turn may lead to misplacement or injury. Hence, a number of approaches to estimate the forces at the needle have been proposed. Yet, integrating sensors into the needle tip is challenging and a careful calibration is required to obtain good force estimates.MethodsWe describe a fiber-optic needle tip force sensor design using a single OCT fiber for measurement. The fiber images the deformation of an epoxy layer placed below the needle tip which results in a stream of 1D depth profiles. We study different deep learning approaches to facilitate calibration between this spatio-temporal image data and the related forces. In particular, we propose a novel convGRU-CNN architecture for simultaneous spatial and temporal data processing.ResultsThe needle can be adapted to different operating ranges by changing the stiffness of the epoxy layer. Likewise, calibration can be adapted by training the deep learning models. Our novel convGRU-CNN architecture results in the lowest mean absolute error of and a cross-correlation coefficient of 0.9997 and clearly outperforms the other methods. Ex vivo experiments in human prostate tissue demonstrate the needle’s application.ConclusionsOur OCT-based fiber-optic sensor presents a viable alternative for needle tip force estimation. The results indicate that the rich spatio-temporal information included in the stream of images showing the deformation throughout the epoxy layer can be effectively used by deep learning models. Particularly, we demonstrate that the convGRU-CNN architecture performs favorably, making it a promising approach for other spatio-temporal learning problems.Electronic supplementary materialThe online version of this article (10.1007/s11548-019-02006-z) contains supplementary material, which is available to authorized users.

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Fiber-Optic Fabry-Pérot Interferometers for Axial Force Sensing on the Tip of a Needle

Cited by 15 publications

References 24 publications

Needle Tip Force Estimation Using an OCT Fiber and a Fused convGRU-CNN Architecture

Needle Tip Force Estimation Using an OCT Fiber and a Fused convGRU-CNN Architecture

Modular Optic Force Sensor for a Surgical Device Using a Fabry–Perot Interferometer

Spatio-temporal deep learning models for tip force estimation during needle insertion

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