Gerd Häusler

Gerd Häusler, Aleksandra Milczarek, Markus Schreiter et al.

This document contains the results obtained by the Innovation Management Seminar in winter term 2017. In total 11 ideas have been developed by the team. In the document all 11 ideas show improvements for future applications in ophthalmology. The 11 ideas are AR/VR Glasses with Medical Applications, Augmented Reality Eye Surgery, Game Diagnosis, Intelligent Adapting Glasses, MD Facebook, Medical Crowd Segmentation, Personalized 3D Model of the Human Eye, Photoacoustic Contact Lens, Power Supply Smart Contact Lens, VR-Cornea and Head Mount for Fundus Imaging

Oliver Arold, Svenja Ettl, Florian Willomitzer et al.

Precise 3D measurements of rigid surfaces are desired in many fields of application like quality control or surgery. Often, views from all around the object have to be acquired for a full 3D description of the object surface. We present a sensor principle called "Flying Triangulation" which avoids an elaborate "stop-and-go" procedure. It combines a low-cost classical light-section sensor with an algorithmic pipeline. A hand-guided sensor captures a continuous movie of 3D views while being moved around the object. The views are automatically aligned and the acquired 3D model is displayed in real time. In contrast to most existing sensors no bandwidth is wasted for spatial or temporal encoding of the projected lines. Nor is an expensive color camera necessary for 3D acquisition. The achievable measurement uncertainty and lateral resolution of the generated 3D data is merely limited by physics. An alternating projection of vertical and horizontal lines guarantees the existence of corresponding points in successive 3D views. This enables a precise registration without surface interpolation. For registration, a variant of the iterative closest point algorithm - adapted to the specific nature of our 3D views - is introduced. Furthermore, data reduction and smoothing without losing lateral resolution as well as the acquisition and mapping of a color texture is presented. The precision and applicability of the sensor is demonstrated by simulation and measurement results.

Florian Willomitzer, Svenja Ettl, Christian Faber et al.

Flying Triangulation sensors enable a free-hand and motion-robust 3D data acquisition of complex shaped objects. The measurement principle is based on a multi-line light-sectioning approach and uses sophisticated algorithms for real-time registration (S. Ettl et al., Appl. Opt. 51 (2012) 281-289). As "single-shot principle", light sectioning enables the option to get surface data from one single camera exposure. But there is a drawback: A pixel-dense measurement is not possible because of fundamental information-theoretical reasons. By "pixel-dense" we understand that each pixel displays individually measured distance information, neither interpolated from its neighbour pixels nor using lateral context information. Hence, for monomodal single-shot principles, the 3D data generated from one 2D raw image display a significantly lower space-bandwidth than the camera permits. This is the price one must pay for motion robustness. Currently, our sensors project about 10 lines (each with 1000 pixels), reaching an considerable lower data efficiency than theoretically possible for a single-shot sensor. Our aim is to push Flying Triangulation to its information-theoretical limits. Therefore, the line density as well as the measurement depth needs to be significantly increased. This causes serious indexing ambiguities. On the road to a single-shot 3D movie camera, we are working on solutions to overcome the problem of false line indexing by utilizing yet unexploited information. We will present several approaches and will discuss profound information-theoretical questions about the information efficiency of 3D sensors.