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.
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
Augmented Reality (AR) is a convenient way of porting information from medical images into the surgical field of
view and can deliver valuable assistance to the surgeon, especially in laparoscopic procedures. In addition, high
definition (HD) laparoscopic video devices are a great improvement over the previously used low resolution
equipment. However, in AR applications that rely on real-time detection of fiducials from video streams, the demand
for efficient image processing has increased due to the introduction of HD devices. We present an algorithm based on
the well-known Conditional Density Propagation (CONDENSATION) algorithm which can satisfy these new
demands. By incorporating a prediction around an already existing and robust segmentation algorithm, we can speed
up the whole procedure while leaving the robustness of the fiducial segmentation untouched. For evaluation purposes
we tested the algorithm on recordings from real interventions, allowing for a meaningful interpretation of the results.
Our results show that we can accelerate the segmentation by a factor of 3.5 on average. Moreover, the prediction
information can be used to compensate for fiducials that are temporarily occluded or out of scope, providing greater
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.
Vessel tree tracking is an important and challenging task for many medical applications. This paper presents
a novel bifurcation detection algorithm for Bayesian tracking of vessel trees. Based on a cylindrical model, we
introduce a bifurcation metric that yields minimal values at potential branching points. This approach avoids
searching for bifurcations in every iteration of the tracking process (as proposed by prior works) and is therefore
computationally more efficient. We use the same geometric model for the bifurcation metric as for the tracking;
no specific bifurcation model is needed. In a preliminary evaluation of our method on 8 CTA datasets of coronary
arteries, all side branches and 95.8% of the main branches were detected correctly.
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.
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.
For exact orientation inside the tracheobronchial tree, clinicians would greatly profit from a soft tissue navigation
system for bronchoscopy. Such an image guided system which gives the ability to show the current position of
a bronchoscope (an instrument to inspect the inside of the lung) or a catheter within the tracheobronchial tree,
significantly improves orientation inside the complex airway structure and the depth of insertion into it. A major
challenge for a bronchoscopy navigation system is respiratory motion. Recently, more and more developments of
navigated bronchoscopy systems use the tracheobronchial centerline in order to develop a compensation for respiratory
motion. The implementation and evaluation of the compensation algorithms are assisted by a simulation
environment, that provides tracking data similar to the data that has to be processed during a bronchoscopic
intervention. Thus we developed an evaluation environment which simulates a random insertion of a tracking
sensor into a tracheobronchial tree, adding electromagnetic noise and distortion similar to an operating table,
and harmonic respiratory motion to the tracked position. With this environment, a high number of insertion
tracks can be created and used to optimize methods for minimizing the electromagnetic tracking error and compensating
respiratory movement. The authors encourage other researchers to use this evaluation environment to
test different correction and estimation algorithms for navigated bronchoscopy.
For exact orientation inside the tracheobronchial tree, clinicians are in urgent need of a navigation system for
bronchoscopy. Such an image guided system has the ability to show the current position of a bronchoscope
(instrument to inspect the inside of the lung) within the tracheobronchial tree. Thus orientation inside the
complex tree structure is improved. Our approach of navigated bronchoscopy considers the problem of using a
static image to navigate inside a constantly moving soft tissue. It offers a direct guidance to a preinterventionally
defined target inside the bronchial tree to save intervention time spent on searching the right path and to minimize
the duration of anesthesia. It is designed to adapt to the breathing cycle of the patient, so no further intervention
to minimize the movement of the lung has to stress the patient. We present a newly developed navigation sensor
with allows to display a virtual bronchoscopy in real time and we demonstrate an evaluation on the accuracy
within a non moving ex vivo lung phantom.
The endoluminal brachytherapy of peripherally located bronchial carcinoma is difficult because of the complexity to position an irradiation catheter led by a bronchoscope to a desired spot inside a human lung. Furthermore the size of the bronchoscope permits only rarely the insertion of a catheter into the fine segment bronchi. We are developing an image-guided navigation system which indicates a path for guidance to the desired bronchus. Thereby a thin catheter with an enclosed navigation probe can be led up directly to the target bronchus, either by the use of the video of the bronchoscope or by the use of virtual bronchoscopy. Because of the thin bronchi and their moving soft tissue, the navigation system has to be very precise. This accuracy is reached by a gradually registering navigation component which improves the accuracy in the course of the intervention through mapping the already covered path to the preoperatively generated graph based bronchial tree description. The system includes components for navigation, segmentation, preoperative planning, and intraoperative guidance. Furthermore the visualization of the path can be adapted to the lung specialist's habits (video of bronchoscope, 2D, 3D, virtual bronchoscopy etc.).
The paper presents a new method for the semiautomatic segmentation of anatomical or pathological structures in MRI, CT or ultrasound images. The concept of bounding-object segmentation is based on an efficient combination of a new interactive approach with well known automatic segmentation algorithms. The efficiency of this new method is based on the transparent interaction between a 3D scene as well arbitrary 2D views of the scene. Bounding-object segmentation can also be described as a combination of interactive 3D segmentation with region-based, level-set-based, and/or texture based 3D-segmentation algorithms.
Modern systems for visualization, image guided procedures and display allow not only one type of visualization, but a variety of different visualization options. Only a combination of two-dimensional image display and three-dimensional rendering provides enough information for many tasks. Multiplanar orthogonal and oblique reformations of image data are standard features of medical imaging software packages today. Additionally, curved reformations are useful. For example, diagnosis of stenotic vessels can be supported by curved reformations along the centerline of the vessel, showing the complete vessel in one two-dimensional view. In this paper, we present how the open-source Medical Imaging Interaction Toolkit (MITK, www.mitk.org), which is based on the Insight Toolkit (ITK) and the Visualization Toolkit (VTK), can be used to rapidly build interactive systems that provide curved reformations. MITK supports curved reformations not only for images, but also for other data types (e.g., surfaces). Besides visualizations of curved reformations, which can be combined and are kept consistent with other two- and three-dimensional views of the data, interactions on such non-planar manifolds are supported. The developer only has to define the curved manifold, everything else is dealt with by the toolkit. We demonstrate these capabilities by means of a tool for mapping of coronary vessel trees.
The aim of the Medical Imaging Interaction Toolkit (MITK) is to facilitate the creation of clinically usable
image-based software. Clinically usable software for image-guided procedures and image analysis require a high
degree of interaction to verify and, if necessary, correct results from (semi-)automatic algorithms. MITK is
a class library basing on and extending the Insight Toolkit (ITK) and the Visualization Toolkit (VTK). ITK
provides leading-edge registration and segmentation algorithms and forms the algorithmic basis. VTK has
powerful visualization capabilities, but only low-level support for interaction (like picking methods, rotation,
movement and scaling of objects). MITK adds support for high level interactions with data like, for example, the
interactive construction and modification of data objects. This includes concepts for interactions with multiple
states as well as undo-capabilities. Furthermore, VTK is designed to create one kind of view on the data
(either one 2D visualization or a 3D visualization). MITK facilitates the realization of multiple, different views
on the same data (like multiple, multiplanar reconstructions and a 3D rendering). Hierarchically structured
combinations of any number and type of data objects (image, surface, vessels, etc.) are possible. MITK can
handle 3D+t data, which are required for several important medical applications, whereas VTK alone supports
only 2D and 3D data. The benefit of MITK is that it supplements those features to ITK and VTK that are
required for convenient to use, interactive and by that clinically usable image-based software, and that are
outside the scope of both. MITK will be made open-source (http://www.mitk.org).