Evaluation of a novel multi-articulated endoscope: proof of concept through a virtual simulation.

PURPOSE: In endoscopic surgery such as video-assisted thoracoscopic surgery and laparoscopic surgery, providing the surgeon a good view of the target is important. Rigid endoscope has for years been the go-to tool for this purpose, but it has certain limitations like the inability to work around obstacles. To improve on current tools, a novel multi-articulated endoscope (MAE) is currently under development. To investigate its feasibility and possible value, we performed a user test using virtual prototype of the MAE with the intent to show that it outperforms the conventional endoscope while bringing minimal additional burden to the operator. METHODS: To evaluate the prototype, we built a virtual model of the MAE and a rigid oblique-viewing endoscope. Through a comparative user study we evaluate the ability of each device to visualize certain targets placed inside the virtual chest cavity by the angle between the visual axis of the scope and the normal of the plane of the target, while accounting for the usability of each endoscope by recording the time taken for each task. In addition, we collected a questionnaire from each participant to obtain feedback. RESULTS: The angles obtained using the MAE were smaller on average ([Formula: see text]), indicating that better visualization can be achieved through the proposed method. A nonsignificant difference in mean time taken for each task in favor of the rigid endoscope was also found ([Formula: see text]). CONCLUSIONS: We have demonstrated that better visualization for endoscopic surgery can be achieved through our novel MAE. The scope may bring about a paradigm shift in the field of minimally invasive surgery by providing more freedom in viewpoint selection, enabling surgeons to perform more elaborate procedures in minimally invasive settings.

Generation of openEHR Test Datasets for Benchmarking.

openEHR is a widely used EHR specification. Given its technology-independent nature, different approaches for implementing openEHR data repositories exist. Public openEHR datasets are needed to conduct benchmark analyses over different implementations. To address their current unavailability, we propose a method for generating openEHR test datasets that can be publicly shared and used.

3D reconstruction of cochlea using optical coherence tomography.

Recently, in vivo visualization of the cochlea and the smaller structures inside of it has been achieved by optical coherence tomography (OCT). This makes it possible to use OCT imaging for diagnosis of diseases such as Meniere's disease through measuring the degree of endolymphatic hydrops. To this end, we present a novel method for 3D segmentation of these cochlear OCT images that is based on superpixels and diffusion maps. The method takes as input grayscale volumetric OCT images and outputs a binary image with the segmented cochlea. We show that the proposed method is suitable for segmenting the data for visualization as well as for preprocessing the data for future automated grading of endolymphatic hydrops.