The identification of cerebral volume changes in treated growth hormone-deficient adults using serial 3D MR image processing

A pilot study to detect volume changes of cerebral structures in growth hormone (GH)-deficient adults treated with GH using serial 3D MR image processing and to assess need for segmentation prior to registration was conducted.

Evaluation of Binocular Eye Trackers and Algorithms for 3D Gaze Interaction in Virtual Reality Environments

Tracking user’s visual attention is a fundamental aspect in novel human-computer interaction paradigms found in Virtual Reality. For example, multimodal interfaces or dialogue-based communications with virtual and real agents greatly benefit from the analysis of the user’s visual attention as a vital source for deictic references or turn-taking signals. Current approaches to determine visual attention rely primarily on monocular eye trackers. Hence they are restricted to the interpretation of two-dimensional fixations relative to a defined area of projection. The study presented in this article compares precision, accuracy and application performance of two binocular eye tracking devices. Two algorithms are compared which derive depth information as required for visual attention-based 3D interfaces. This information is further applied to an improved VR selection task in which a binocular eye tracker and an adaptive neural network algorithm is used during the disambiguation of partly occluded objects.

Efficient Bimanual Symmetric 3D Manipulation for Bare-Handed Interaction

Recently, stable markerless 6 DOF video based handtracking devices became available. These devices simultaneously track the positions and orientations of both user hands in different postures with at least 25 frames per second. Such hand-tracking allows for using the human hands as natural input devices. However, the absence of physical buttons for performing click actions and state changes poses severe challenges in designing an efficient and easy to use 3D interface on top of such a device. In particular, for coupling and decoupling a virtual object’s movements to the user’s hand (i.e. grabbing and releasing) a solution has to be found. In this paper, we introduce a novel technique for efficient two-handed grabbing and releasing objects and intuitively manipulating them in the virtual space. This technique is integrated in a novel 3D interface for virtual manipulations. A user experiment shows the superior applicability of this new technique. Last but not least, we describe how this technique can be exploited in practice to improve interaction by integrating it with RTT DeltaGen, a professional CAD/CAS visualization and editing tool.

3D-Druck von Kunststoff-Medizinprodukten

Das Additive Manufacturing gewinnt im Bereich der Medizintechnik zur Herstellung von Prototypen bis hin zu Endprodukten zunehmend an Bedeutung. Ein großes Hemmnis stellen allerdings die relativ hohen Fertigungskosten dar. Hier bietet der verstärkte Einsatz der 3D-Drucktechnologie (3D Printing) ein erhebliches Potential zur Reduktion der Kosten. Aus dieser Motivation heraus wurde ein 3D-Druckverfahren zur Herstellung biokompatibler, sterilisierbarer Kunststoffmodelle entwickelt. Beim 3D-Druck-Verfahren handelt es sich um einen pulverbasierten Prozess zur schichtweisen Herstellung von Modellen direkt aus Computerdaten. Dabei werden dünne Schichten eines Pulvers auf eine Grundplatte aufgebracht, die dann durch gezielte Binderzugabe entsprechend des aktuellen Bauteilquerschnitts verfestigt werden. Ausgangsmaterial für diesen Prozess ist ein Granulatgemisch auf Basis von PMMA (Polymethylmethacrylat). Als Binderflüssigkeit wird ein Lösungsmittel eingesetzt. Die 3D gedruckten Modelle werden nach einer entsprechenden Trocknungszeit im Pulverbett entpackt und warmgelagert, um das Abdampfen des Lösungsmittels zu beschleunigen. Der Nachweis der Biokompatibilität der hergestellten Modelle erfolgte durch einen Test nach DIN EN ISO 10993-5. In Kooperation mit Anwendern wurden verschiedene Anwendungsbeispiele wie Bohrschablonen, Otoplastiken, Gebissmodelle und Modelle für die präoperative Planung realisiert und charakterisiert.

3D Conversion using Vanishing Points and Image Warping

We describe a user assisted technique for 3D stereo conversion from 2D images. Our approach exploits the geometric structure of perspective images including vanishing points. We allow a user to indicate lines, planes, and vanishing points in the input image, and directly employ these as constraints in an image warping framework to produce a stereo pair. By sidestepping explicit construction of a depth map, our approach is applicable to more general scenes and avoids potential artifacts of depth-image-based rendering. Our method is most suitable for scenes with large scale structures such as buildings.

Hand-held 3D light field photography and applications

We propose a method to acquire 3D light fields using a hand-held camera, and describe several computational photography applications facilitated by our approach. As our input we take an image sequence from a camera translating along an approximately linear path with limited camera rotations. Users can acquire such data easily in a few seconds by moving a hand-held camera. We include a novel approach to resample the input into regularly sampled 3D light fields by aligning them in the spatio-temporal domain, and a technique for high-quality disparity estimation from light fields. We show applications including digital refocusing and synthetic aperture blur, foreground removal, selective colorization, and others.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

3D Intervertebral Disc Localization and Segmentation from MR Images by Data-Driven Regression and Classification

In this paper we propose a new fully-automatic method for localizing and segmenting 3D intervertebral discs from MR images, where the two problems are solved in a unified data-driven regression and classification framework. We estimate the output (image displacements for localization, or fg/bg labels for segmentation) of image points by exploiting both training data and geometric constraints simultaneously. The problem is formulated in a unified objective function which is then solved globally and efficiently. We validate our method on MR images of 25 patients. Taking manually labeled data as the ground truth, our method achieves a mean localization error of 1.3 mm, a mean Dice metric of 87%, and a mean surface distance of 1.3 mm. Our method can be applied to other localization and segmentation tasks.