This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

Medical augmented reality (AR) has been widely discussed within the medical imaging as well as computer aided surgery communities. Different systems for exemplary medical applications have been proposed. Some of them produced promising results. One major issue still hindering AR technology to be regularly used in medical applications is the interaction between physician and the superimposed 3-D virtual data. Classical interaction paradigms, for instance with keyboard and mouse, to interact with visualized medical 3-D imaging data are not adequate for an AR environment. This paper introduces the concept of a tangible/controllable Virtual Mirror for medical AR applications. This concept intuitively augments the direct view of the surgeon with all desired views on volumetric medical imaging data registered with the operation site without moving around the operating table or displacing the patient. We selected two medical procedures to demonstrate and evaluate the potentials of the Virtual Mirror for the surgical workflow. Results confirm the intuitiveness of this new paradigm and its perceptive advantages for AR-based computer aided interventions.

Electromagnetic tracking is currently one of the most promising means of localizing flexible endoscopic instruments such as flexible laparoscopic ultrasound transducers. However, electromagnetic tracking is also susceptible to interference from ferromagnetic material, which distorts the magnetic field and leads to tracking errors. This paper presents new methods for real-time online detection and reduction of dynamic electromagnetic tracking errors when localizing a flexible laparoscopic ultrasound transducer. We use a hybrid tracking setup to combine optical tracking of the transducer shaft and electromagnetic tracking of the flexible transducer tip. A novel approach of modeling the poses of the transducer tip in relation to the transducer shaft allows us to reliably detect and significantly reduce electromagnetic tracking errors. For detecting errors of more than 5 mm, we achieved a sensitivity and specificity of 91% and 93%, respectively. Initial 3-D rms error of 6.91 mm were reduced to 3.15 mm.

In recent years, an increasing number of liver tumor indications were treated by minimally invasive laparoscopic resection. Besides the restricted view, two major intraoperative issues in laparoscopic liver resection are the optimal planning of ports as well as the enhanced visualization of (hidden) vessels, which supply the tumorous liver segment and thus need to be divided (e.g., clipped) prior to the resection. We propose an intuitive and precise method to plan the placement of ports. Preoperatively, self-adhesive fiducials are affixed to the patient's skin and a computed tomography (CT) data set is acquired while contrasting the liver vessels. Immediately prior to the intervention, the laparoscope is moved around these fiducials, which are automatically reconstructed to register the patient to its preoperative imaging data set. This enables the simulation of a camera flight through the patient's interior along the laparoscope's or instruments' axes to easily validate potential ports. Intraoperatively, surgeons need to update their surgical planning based on actual patient data after organ deformations mainly caused by application of carbon dioxide pneumoperitoneum. Therefore, preoperative imaging data can hardly be used. Instead, we propose to use an optically tracked mobile C-arm providing cone-beam CT imaging capability intraoperatively. After patient positioning, port placement, and carbon dioxide insufflation, the liver vessels are contrasted and a 3-D volume is reconstructed during patient exhalation. Without any further need for patient registration, the reconstructed volume can be directly augmented on the live laparoscope video, since prior calibration enables both the volume and the laparoscope to be positioned and oriented in the tracking coordinate frame. The augmentation provides the surgeon with advanced visual aid for the localization of veins, arteries, and bile ducts to be divided or sealed.

A major roadblock for using augmented reality in many medical and industrial applications is the fact that the user cannot take full advantage of the 3D virtual data. This usually requires the user to move the virtual object, which disturbs the real/virtual alignment, or to move his head around the real objects, which is not always possible and/or practical. This problem becomes more dramatic when a single camera is used for monitor based augmentation, such as in augmented laparoscopic surgery. In this paper we introduce an interaction and 3D visualization paradigm, which presents a new solution to this old problem. The interaction paradigm uses an interactive virtual mirror positioned into the augmented scene, which allows easy and complete interactive visualization of 3D virtual data. This paper focuses on the exemplary application of such visualization techniques to laparoscopic interventions. A large number of such interventions aims at regions inside a specific organ, e.g. blood vessels to be clipped for tumor resection. We use high-resolution intra-operative imaging data generated by a mobile C-arm with cone-beam CT imaging capability. Both the C-arm and the laparoscope are optically tracked and registered in a common world coordinate frame. After patient positioning, port placement, and carbon dioxide insufflation, a C-arm volume is reconstructed during patient exhalation and superimposed in real time on the laparoscopic live video without any need for an additional patient registration procedure. To overcome the missing perception of 3D depth and shape when rendering virtual volume data directly on top of the organ's surface view, we introduce the concept of a laparoscopic virtual mirror: A virtual reflection plane within the live laparoscopic video, which is able to visualize a reflected side view of the organ and its interior. This enables the surgeon to observe the 3D structure of, for example, blood vessels by moving the virtual mirror within the augmented monocular view of the laparoscope.