Fusion of Biplane Fluoroscopy With Fiber Bragg Grating for 3D Catheter Shape Reconstruction

Ourak, Mouloud; Buck, Stijn De; Ha, Xuan Thao; Al-Ahmad, Omar; Bamps, Kobe; Ector, Joris; Poorten, Emmanuel Vander

doi:10.1109/lra.2021.3094238

Cited by 17 publications

(6 citation statements)

References 26 publications

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“…It is worth noting that owing to the fact that the catheter and its ground truth shapes were not aligned by using the Iterative Closest Point (ICP) approach, the reported catheter shape tracking accuracy in our paper might be larger than other works in the art which use ICP [10], [24], [25]. Using ICP is avoided in this work since this registration approach will actively reduce the error between the estimated and its ground truth shapes.…”

Section: Resultsmentioning

confidence: 96%

Fusion Framework for Coaxial Catheter Tracking

Ha,

Wu,

Trauzettel

et al. 2023

IEEE Sensors J.

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Minimally invasive catheter-based interventions normally take place under the guidance of fluoroscopy. However, fluoroscopy is harmful to both patients and clinicians. Moreover, it only offers 2D shape visualization of flexible devices. To solve the problem of harmful radiation and offer 3D pose and shape information, recent studies propose a combination of ElectromagneticTracking (EMT) sensors and multi-core Fiber Bragg Grating (FBG) fiber sensing. However, for robust localization, at least two EMT sensors are required to be attached to each multi-core fiber. This may make the catheter overly complex and fragile. Furthermore, the inability of multi-core FBG fibers to distinguish between twistinduced strain and bend-induced strain impacts shape sensing accuracy. This paper proposes a new approach offering a precise shape sensing method that is robust against torsional twists and exploits symmetry and geometry to compensate for limited sensing information. The proposed approach originates from the observation that many interventional procedures employ a plurality of concentric instruments. By distributing sensors over these instruments, the complexity per instrument can be kept acceptable. The proposed sensor fusion approach ensures robust and superior shape reconstruction. Experiments in 3D with ground truth generated by a stereo vision system have been done and yielded promising results. Compared to the state-of-the-art methods, the presented framework uses only half of the required EMT sensors per instrument resulting in significant spatial conservation while improving the catheter shape tracking accuracy by 57%.

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Section: Resultsmentioning

confidence: 96%

Fusion Framework for Coaxial Catheter Tracking

Ha,

Wu,

Trauzettel

et al. 2023

IEEE Sensors J.

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“…Different techniques using fluoroscopic system combined either with FBG sensing or with both position and FBG sensing can be proposed to include the twist information. There are few papers (Ourak et al, 2021), (Ha et al, 2021) that proposed these kinds of strategies. But further development is necessary to bring these systems into the medical scenarios.…”

Section: Discussionmentioning

confidence: 99%

Shape Reconstruction Processes for Interventional Application Devices: State of the Art, Progress, and Future Directions

et al. 2021

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Soft and continuum robots are transforming medical interventions thanks to their flexibility, miniaturization, and multidirectional movement abilities. Although flexibility enables reaching targets in unstructured and dynamic environments, it also creates challenges for control, especially due to interactions with the anatomy. Thus, in recent years lots of efforts have been devoted for the development of shape reconstruction methods, with the advancement of different kinematic models, sensors, and imaging techniques. These methods can increase the performance of the control action as well as provide the tip position of robotic manipulators relative to the anatomy. Each method, however, has its advantages and disadvantages and can be worthwhile in different situations. For example, electromagnetic (EM) and Fiber Bragg Grating (FBG) sensor-based shape reconstruction methods can be used in small-scale robots due to their advantages thanks to miniaturization, fast response, and high sensitivity. Yet, the problem of electromagnetic interference in the case of EM sensors, and poor response to high strains in the case of FBG sensors need to be considered. To help the reader make a suitable choice, this paper presents a review of recent progress on shape reconstruction methods, based on a systematic literature search, excluding pure kinematic models. Methods are classified into two categories. First, sensor-based techniques are presented that discuss the use of various sensors such as FBG, EM, and passive stretchable sensors for reconstructing the shape of the robots. Second, imaging-based methods are discussed that utilize images from different imaging systems such as fluoroscopy, endoscopy cameras, and ultrasound for the shape reconstruction process. The applicability, benefits, and limitations of each method are discussed. Finally, the paper draws some future promising directions for the enhancement of the shape reconstruction methods by discussing open questions and alternative methods.

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“…These algorithms have presented a data-driven learning-based approach [77], an updated shape reconstruction algorithm based on the error accumulation of a single-point recursive reconstruction algorithm [78], and an extended Kalman filter-based estimator that iteratively predicts and updates not only curvatures on the fiber but also the degree of its twist [79]. The fusion of fluoroscopy and FBG for 3-D shape reconstruction of a catheter has been proposed as well [206].…”

Section: Shape and Force Sensingmentioning

confidence: 99%