Multisensor Data Fusion in an Integrated Tracking System for Endoscopic Surgery

Ren, Hongliang; Rank, Denis; Merdes, Martin; Stallkamp, Jan; Kazanzides, Peter

doi:10.1109/titb.2011.2164088

Cited by 78 publications

(17 citation statements)

References 11 publications

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“…Similar works are mainly reported by Ren in [11,19,20]. In his research, Ren combines a custom EMT subsystem designed in [32,33]—which contains a generator array bearing 48 coils and a receiving array bearing three coils—with a typical MARG sensor.…”

Section: Resultssupporting

confidence: 55%

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An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

Chen

Wang

et al. 2014

Sensors

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In this paper, a novel hybrid sensing method for tracking an ultrasonic endoscope within the gastrointestinal (GI) track is presented, and the prototype of the tracking system is also developed. We implement 6-DOF localization by sensing integration and information fusion. On the hardware level, a tri-axis gyroscope and accelerometer, and a magnetic angular rate and gravity (MARG) sensor array are attached at the end of endoscopes, and three symmetric cylindrical coils are placed around patients' abdomens. On the algorithm level, an adaptive fast quaternion convergence (AFQC) algorithm is introduced to determine the orientation by fusing inertial/magnetic measurements, in which the effects of magnetic disturbance and acceleration are estimated to gain an adaptive convergence output. A simplified electro-magnetic tracking (SEMT) algorithm for dimensional position is also implemented, which can easily integrate the AFQC's results and magnetic measurements. Subsequently, the average position error is under 0.3 cm by reasonable setting, and the average orientation error is 1° without noise. If magnetic disturbance or acceleration exists, the average orientation error can be controlled to less than 3.5°.

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Section: Resultssupporting

confidence: 55%

“…Commonly, an optical tracking [17,18] or inertial navigation system (INS) [19,20] can be adopted to assist EMT. However, restricted by the line-of-sight conditions [21], integrating EMT and INS becomes the most feasible solution for us, so in our solution, an INS is applied.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

Chen

Wang

et al. 2014

Sensors

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“…This error decreased significantly when the gyrosensor and accelerometer were used simultaneously. Use of accelerometer and gyrosensor in endoscopic guidance have been reported already [ 15 , 16 ]. Behrens and colleagues used accelerometer and gyrosensor for endoscope navigating system.…”

Section: Discussionmentioning

confidence: 99%

“…In the report, the mean error of the position measurement was between 1 and 4 degrees [ 15 ]. Ren, et al reported that accelerometer and gyrosensor can improve the accuracy of existing electromagnetic tracking system [ 16 ]. However, relatively little effort has been made to evaluate the clinical usefulness of this technology.…”

Section: Discussionmentioning

confidence: 99%

Real-time endoscopic image orientation correction system using an accelerometer and gyrosensor

2017

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The discrepancy between spatial orientations of an endoscopic image and a physician’s working environment can make it difficult to interpret endoscopic images. In this study, we developed and evaluated a device that corrects the endoscopic image orientation using an accelerometer and gyrosensor. The acceleration of gravity and angular velocity were retrieved from the accelerometer and gyrosensor attached to the handle of the endoscope. The rotational angle of the endoscope handle was calculated using a Kalman filter with transmission delay compensation. Technical evaluation of the orientation correction system was performed using a camera by comparing the optical rotational angle from the captured image with the rotational angle calculated from the sensor outputs. For the clinical utility test, fifteen anesthesiology residents performed a video endoscopic examination of an airway model with and without using the orientation correction system. The participants reported numbers written on papers placed at the left main, right main, and right upper bronchi of the airway model. The correctness and the total time it took participants to report the numbers were recorded. During the technical evaluation, errors in the calculated rotational angle were less than 5 degrees. In the clinical utility test, there was a significant time reduction when using the orientation correction system compared with not using the system (median, 52 vs. 76 seconds; P = .012). In this study, we developed a real-time endoscopic image orientation correction system, which significantly improved physician performance during a video endoscopic exam.

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“…The possible clinical applications of the registration problem to be dealt with in this article are summarized as follows. (1) Pre-operative to intra-operative space alignment in CAS [2], [17], [23], [24]. (2) Statistical shape modelling (SSM).…”

Section: Introductionmentioning

confidence: 99%

Joint Rigid Registration of Multiple Generalized Point Sets With Anisotropic Positional Uncertainties in Image-Guided Surgery

Min

Wang

Meng

2022

IEEE Trans. Automat. Sci. Eng.

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In medical image analysis (MIA) and computerassisted surgery (CAS), aligning two multiple point sets (PSs) together is an essential but also a challenging problem. For example, rigidly aligning multiple point sets into one common coordinate frame is a prerequisite for statistical shape modelling (SSM). Accurately aligning the pre-operative space with the intraoperative space in CAS is very crucial to successful interventions. In this article, we formally formulate the multiple generalized point set registration problem (MGPSR) in a probabilistic manner, where both the positional and the normal vectors are used. The six-dimensional vectors consisting of both positional and normal vectors are called as generalized points. In the formulated model, all the generalized PSs to be registered are considered to be the realizations of underlying unknown hybrid mixture models (HMMs). By assuming the independence of the positional and orientational vectors (i.e., the normal vectors), the probability density function (PDF) of an observed generalized point is computed as the product of Gaussian and Fisher distributions. Furthermore, to consider the anisotropic noise in surgical navigation, the positional error is assumed to obey a multi-variate Gaussian distribution. Finally, registering PSs is formulated as a maximum likelihood (ML) problem, and solved under the expectation maximization (EM) technique. By using more enriched information (i.e., the normal vectors), our algorithm is more robust to outliers. By treating all PSs equally, our algorithm does not bias towards any PS. To validate the Manuscript

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Multisensor Data Fusion in an Integrated Tracking System for Endoscopic Surgery

Cited by 78 publications

References 11 publications

An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

An Adaptive 6-DOF Tracking Method by Hybrid Sensing for Ultrasonic Endoscopes

Real-time endoscopic image orientation correction system using an accelerometer and gyrosensor

Joint Rigid Registration of Multiple Generalized Point Sets With Anisotropic Positional Uncertainties in Image-Guided Surgery

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