Navigated bronchoscopy provides benefits for endoscopists and patients, but accurate tracking information is
needed. We present a novel real-time approach for bronchoscope tracking combining electromagnetic (EM)
tracking, airway segmentation, and a continuous model of output. We augment a previously published approach
by including segmentation information in the tracking optimization instead of image similarity. Thus, the new
approach is feasible in real-time. Since the true bronchoscope trajectory is continuous, the output is modeled
using splines and the control points are optimized with respect to displacement from EM tracking measurements
and spatial relation to segmented airways. Accuracy of the proposed method and its components is evaluated
on a ventilated porcine ex-vivo lung with respect to ground truth data acquired from a human expert. We
demonstrate the robustness of the output of the proposed method against added artificial noise in the input
data. Smoothness in terms of inter-frame distance is shown to remain below 2 mm, even when up to 5 mm of
Gaussian noise are added to the input. The approach is shown to be easily extensible to include other measures
like image similarity.
A. Franz, A. Seitel, M. Servatius, C. Zöllner, I. Gergel, I. Wegner, J. Neuhaus, S. Zelzer, M. Nolden, J. Gaa, P. Mercea, K. Yung, C. Sommer, B. Radeleff, H.-P. Schlemmer, H.-U. Kauczor, H.-P. Meinzer, L. Maier-Hein
Due to rapid developments in the research areas of medical imaging, medical image processing and robotics,
computer assistance is no longer restricted to diagnostics and surgical planning but has been expanded to surgical
and radiological interventions. From a software engineering point of view, the systems for image-guided therapy
(IGT) are highly complex. To address this issue, we presented an open source extension to the well-known
Medical Imaging Interaction Toolkit (MITK) for developing IGT systems, called MITK-IGT. The contribution
of this paper is two-fold: Firstly, we extended MITK-IGT such that it (1) facilitates the handling of navigation
tools, (2) provides reusable graphical user interface (UI) components, and (3) features standardized exception
handling. Secondly, we developed a software prototype for computer-assisted needle insertions, using the new
features, and tested it with a new Tabletop field generator (FG) for the electromagnetic tracking system NDI
Aurora ®. To our knowledge, we are the first to have integrated this new FG into a complete navigation system
and have conducted tests under clinical conditions. In conclusion, we enabled simplified development of imageguided
therapy software and demonstrated the utilizability of applications developed with MITK-IGT in the
clinical workflow.
Electromagnetic tracking (EMT) systems are gaining increased attention in various fields of image-guided surgery. One of the main problems related to EMT systems is their vulnerability to distortion due to metallic objects. Several methods have been introduced to evaluate electromagnetic trackers, yet, the data acquisition has to be manually performed in a time consuming procedure, which often leads to a sparse volume coverage. The aim of this work is to present a fully automatic calibration system. It consists of a novel, parallel robotic arm and has the potential to collect a very large number of tracking data while scanning the entire tracking volume of a field generator. To prove the feasibility of our system, we evaluate two electromagnetic field generators (NDI Planar and Tabletop) in an ideal metal-free environment and in a clinical setup. Our proposed calibration robot successfully performed throughout the experiments and examined 1,000 positions in the tracking volume of each field generator (FG). According to the results both FGs are highly accurate in an ideal environment. However, in the examined clinical setup, the Planar FG is strongly distorted by metallic objects. Whereas the Tabletop FG provided very robust and accurate tracking, even if metallic objects where lying directly underneath the FG.
KEYWORDS: Lung, Biopsy, Electromagnetism, Diagnostics, Computed tomography, Medical imaging, Visualization, Visual process modeling, Current controlled current source, Tissues
Transbronchial needle aspiration (TBNA) is a common procedure to collect tissue samples from the inside of the lung for diagnostic use. However, the main drawback of the procedure is that it has to be blindly performed because the biopsy target region is behind the bronchial wall and hence not within the field of view of the bronchoscope. Thus, the diagnostic yield rate is low. To increase success rate of TBNA biopsy an electromagnetic trackable TBNA needle has been introduced. Nevertheless, the introduced prototype TBNA instrument was evaluated in a rigid rubber phantom without taking respiratory motion into account. The purpose of this study is to present a new TBNA needle where the electromagnetic sensor is directly integrated into a TBNA needle and to access its performance in a regularly ventilated lung. Using our previously presented navigation system, seven TBNA interventions were performed in a porcine lung during regular respiration lung movement; respectively a control computer tomography scan was acquired. We evaluated tracking accuracy of the electromagnetically tracked needle during the entire respiratory cycle for each intervention. The newly developed TBNA needle successfully operated throughout all seven interventions. According to the results, our electromagnetic TBNA tracking system is a promising approach to increase the TBNA biopsy success rate.
Registration of multiple medical images commonly comprises the steps feature extraction, correspondences search and transformation computation. In this paper, we present a new method for a fast and pose independent search of correspondences using as features anatomical trees such as the bronchial system in the lungs or the vessel system in the liver. Our approach scores the similarities between the trees' nodes (bifurcations) taking into account both, topological properties extracted from their graph representations and anatomical properties extracted from the trees themselves. The node assignment maximizes the global similarity (sum of the scores of each pair of assigned nodes), assuring that the matches are distributed throughout the trees. Furthermore, the proposed method is able to deal with distortions in the data, such as noise, motion, artifacts, and problems associated with the extraction method, such as missing or false branches. According to an evaluation on swine lung data sets, the method requires less than one second on average to compute the matching and yields a high rate of correct matches compared to state of the art work.
KEYWORDS: Particles, Bronchoscopy, Particle filters, Electromagnetism, Lung, Medical imaging, Visualization, Motion models, Visual process modeling, Current controlled current source
Although the field of a navigated bronchoscopy gains increasing attention in the literature, robust guidance in the presence of respiratory motion and electromagnetic noise remains challenging.
The robustness of a previously introduced motion compensation approach was increased by taking into account the already traveled trajectory of the instrument within the lung. To evaluate the performance of the method a virtual environment, which accounts for respiratory motion and electromagnetic noise was used. The simulation is based on a deformation field computed from human computed tomography data. According to the results, the proposed method outperforms the original method and is suitable for lung motion compensation during electromagnetically guided interventions.
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