Alexander Bornik

Liver Surgery Planning Using Virtual Reality

We have developed LiverPlanner, a virtual liver surgery planning system that uses high-level image analysis algorithms and virtual reality technology to help physicians find the best resection plan for each individual patient. Preliminary user studies of LiverPlanner show that the proposed tools are well accepted by doctors and lead to much shorter planning times

Ray casting of multiple volumetric datasets with polyhedral boundaries on manycore GPUs

We present a new GPU-based rendering system for ray casting of multiple volumes. Our approach supports a large number of volumes, complex translucent and concave polyhedral objects as well as CSG intersections of volumes and geometry in any combination. The system (including the rasterization stage) is implemented entirely in CUDA, which allows full control of the memory hierarchy, in particular access to high bandwidth and low latency shared memory. High depth complexity, which is problematic for conventional approaches based on depth peeling, can be handled successfully. As far as we know, our approach is the first framework for multivolume rendering which provides interactive frame rates when concurrently rendering more than 50 arbitrarily overlapping volumes on current graphics hardware.

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

PURPOSEnLiver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation.nnnMETHODSnA graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method.nnnRESULTSnCompared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, pu2009=u20090.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, pu2009=u20090.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction and resulted in statistically not significantly different segmentation error indices (ANOVA test, significance level of 0.05).nnnCONCLUSIONSnAll three experts were able to produce liver segmentations with low error rates. User interaction time savings of up to 71% compared to a 2D refinement approach demonstrate the utility and potential of our approach. The system offers a range of different tools to manipulate segmentation results, and some users might benefit from a longer learning phase to develop efficient segmentation refinement strategies. The presented approach represents a generally applicable segmentation approach that can be applied to many medical image segmentation problems.

A Hybrid User Interface for Manipulation of Volumetric Medical Data

This paper presents a novel system for interactive visualization and manipulation of medical datasets for surgery planning based on a hybrid VR / Tablet PC user interface. The goal of the system is to facilitate efficient visual inspection and correction of surface models generated by automated segmentation algorithms based on x-ray computed tomography scans, needed for planning surgical interventions. Factors like the quality of the visualization, nature of the dataset and interaction efficiency strongly influence system design decisions, in particular the design of the user interface, input devices and interaction techniques, leading to a hybrid setup. Finally, a user study is presented, which characterizes the system in terms of method efficiency and usability.

Computer-aided liver surgery planning: an augmented reality approach

Surgical resection of liver tumors requires a detailed three-dimensional understanding of a complex arrangement of vasculature, liver segments and tumors inside the liver. In most cases, surgeons need to develop this understanding by looking at sequences of axial images from modalities like X-ray computed tomography. A system for liver surgery planning is reported that enables physicians to visualize and refine segmented input liver data sets, as well as to simulate and evaluate different resections plans. The system supports surgeons in finding the optimal treatment strategy for each patient and eases the data preparation process. The use of augmented reality contributes to a user-friendly design and simplifies complex interaction with 3D objects. The main function blocks developed so far are: basic augmented reality environment, user interface, rendering, surface reconstruction from segmented volume data sets, surface manipulation and quantitative measurement toolkit. The flexible design allows to add functionality via plug-ins. First practical evaluation steps have shown a good acceptance. Evaluation of the system is ongoing and future feedback from surgeons will be collected and used for design refinements.

Tools for augmented-reality-based liver resection planning

Surgical resection has evolved to an accepted and widely-used method for the treatment of liver tumors. In order nto elaborate an optimal resection strategy, computer-aided planning tools are required. However, measurements nbased on 2D cross sectional images are difficult to perform. Moreover, resection planning with current desktopbased nsystems using 3D visualization is also a tedious task because of limited 3D interaction. For facilitating the nplanning process, different tools are presented allowing easy user interaction in an Augmented Reality environment. nMethods for quantitative analysis like volume calculation and distance measurements are discussed with nfocus on the user interaction aspect. In addition, a tool for automatically generating anatomical resection proposals nbased on knowledge about tumor locations and the portal vein tree is described. The presented methods nare part of an evolving liver surgery planning system which is currently evaluated by physicians.

High-quality texture reconstruction from multiple views†

This paper presents a method to automatically calculate texture maps for a given three-dimensional object out of a sequence of images. It is used in our image-based modeling approach after the registration of the images and the geometric modeling is done. We show that the presented method uses the information from all images by implicitly applying a weighting function. Using this approach the consideration of modeled occlusions as well as the detection and removal of non-modeled occlusions is accomplished. The final resolution of the texture maps can be adjusted on a pixel/cm basis. Copyright

Spatial Analysis Tools for Virtual Reality-based Surgical Planning

This paper presents a set of Virtual Reality-based interaction techniques for spatial analysis of medical datasets. Computer-aided medical planning tools often require precise and intuitive interaction for the quantitative inspection and analysis of anatomical and pathological structures. We claim that measurement tasks can be carried out more efficiently using Virtual Reality-based interaction tools rather than using common 2D input devices used for medical workstation. Due to the true direct manipulation of threedimensional virtual objects, measurement tools can be used easily in 3D. An evaluation performed with a group of 20 subjects provides evidence to back up our claims.

Forensic-Case Analysis: From 3D Imaging to Interactive Visualization

An interactive framework prepares raw computed-tomography and magnetic-resonance-imaging scans for courtroom presentations. The framework makes use of combined computer graphics and computer vision techniques to enable a forensic case analysis workflow.

Intuitive presentation of clinical forensic data using anonymous and person-specific 3D reference manikins

The increasing use of CT/MR devices in forensic analysis motivates the need to present forensic findings from different sources in an intuitive reference visualization, with the aim of combining 3D volumetric images along with digital photographs of external findings into a 3D computer graphics model. This model allows a comprehensive presentation of forensic findings in court and enables comparative evaluation studies correlating data sources. The goal of this work was to investigate different methods to generate anonymous and patient-specific 3D models which may be used as reference visualizations. The issue of registering 3D volumetric as well as 2D photographic data to such 3D models is addressed to provide an intuitive context for injury documentation from arbitrary modalities. We present an image processing and visualization work-flow, discuss the major parts of this work-flow, compare the different investigated reference models, and show a number of cases studies that underline the suitability of the proposed work-flow for presenting forensically relevant information in 3D visualizations.