Abstract-Intra-operative imaging techniques for obtaining the shape and morphology of soft-tissue surfaces in vivo are a key enabling technology for advanced surgical systems. Different optical techniques for 3D surface reconstruction in laparoscopy have been proposed, however, so far no quantitative and comparative validation has been performed. Furthermore, robustness of the methods to clinically important factors like smoke or bleeding has not yet been assessed. To address these issues, we have formed a joint international initiative with the aim of validating different state-of-the-art passive and active reconstruction methods in a comparative manner. In this comprehensive in vitro study, we investigated reconstruction accuracy using different organs with various shape and texture and also tested reconstruction robustness with respect to a number of factors like the pose of the endoscope as well as the amount of blood or smoke present in the scene. The study suggests complementary advantages of the different techniques with respect to accuracy, robustness, point density, hardware complexity and computation time. While reconstruction accuracy under ideal conditions was generally high, robustness is a remaining issue to be addressed. Future work should include sensor fusion and in vivo validation studies in a specific clinical context.

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The system is mobile, markerless, intuitive and real-time capable with sufficient accuracy. It can support the forensic pathologist during autopsy with augmented reality and textured surfaces. Furthermore, the system enables multimodal documentation for presentation in court. Despite its preliminary prototype status, it has high potential due to its low price and simplicity.

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Abstract. Despite considerable technical and algorithmic developments related to the fields of medical image acquisition and processing in the past decade, the devices used for visualization of medical images have undergone rather minor changes. As anatomical information is typically shown on monitors provided by a radiological work station, the physician has to mentally transfer internal structures shown on the screen to the patient. In this work, we present a new approach to on-patient visualization of 3D medical images, which combines the concept of augmented reality (AR) with an intuitive interaction scheme. The method requires mounting a Time-of-Flight (ToF) camera to a portable display (e.g., a tablet PC). During the visualization process, the pose of the camera and thus the viewing direction of the user is continuously determined with a surface matching algorithm. By moving the device along the body of the patient, the physician gets the impression of being able to look directly into the human body. The concept can be used for intervention planning, anatomy teaching and various other applications that require intuitive visualization of 3D data.

Although system performance remains to be improved for clinical use, expected advances in camera technology as well as consideration of respiratory motion and automation of the individual steps will make this approach an interesting alternative for guiding percutaneous needle insertions.

Abstract. 3-D Endoscopy is an evolving field of research and offers great benefits for minimally invasive procedures. Besides the pure topology, color texture is an inevitable feature to provide an optimal visualization. Therefore, in this paper, we propose a sensor fusion of a Time-of-Flight (ToF) and an RGB sensor. This requires an intrinsic and extrinsic calibration of both cameras. In particular, the low resolution of the ToF camera (64×50 px) and inhomogeneous illumination precludes the use of standard calibration techniques. By enhancing the image data the use of self-encoded markers for automatic checkerboard detection, a reprojection error of less than 0.23 px for the ToF camera was achieved. The relative transformation of both sensors for data fusion was calculated in an automatic manner.

With the increased popularity of time-of-flight cameras for intra-operative surface acquisition, integration of range data supports into medical image processing toolkits such as MITK is a necessary step. Handling acquisition of range data from different cameras and processing of the data requires the establishment and use of software design principles that emphasize flexibility, extendibility, robustness, performance, and portability. The open-source toolkit MITK-ToF satisfies these requirements for the image-guided therapy community and was already used in several research projects.