Showing papers by "Heinz-Otto Peitgen published in 2006"

Numerical simulation of radio frequency ablation with state dependent material parameters in three space dimensions

Abstract: We present a model for the numerical simulation of radio frequency (RF) ablation of tumors with mono- or bipolar probes. This model includes the electrostatic equation and a variant of the well-known bio-heat transfer equation for the distribution of the electric potential and the induced heat. The equations are nonlinearly coupled by material parameters that change with temperature, dehydration and damage of the tissue. A fixed point iteration scheme for the nonlinear model and the spatial discretization with finite elements are presented. Moreover, we incorporate the effect of evaporation of water from the cells at high temperatures using a predictor-corrector like approach. The comparison of the approach to a real ablation concludes the paper.

GPU Accelerated Image Registration in Two and Three Dimensions

Abstract: Medical image registration tasks of large volume datasets, especially in the non-rigid case, often put a heavy burden on computing resources. GPUs are a promising new approach to address computational intensive image processing tasks. We investigate recently introduced GPU hardware features that accelerate 2D and 3D rigid and nonrigid registration tasks. Our implementation is entirely GPU based.

Embedding VTK and ITK into a visual programming and rapid prototyping platform

Abstract: Visualization and image processing of medical datasets has become an essential task for clinical diagnosis support as well as for treatment planning. In order to enable a physician to use and evaluate algorithms within a clinical setting, easily applicable software prototypes with a dedicated user interface are essential. However, substantial programming knowledge is still required today when using powerful open source libraries such as the Visualization Toolkit (VTK) or the Insight Toolkit (ITK). Moreover, these toolkits provide only limited graphical user interface functionality. In this paper, we present the visual programming and rapid prototyping platform MeVisLab which provides flexible and simple handling of visualization and image processing algorithms of VTK/ITK, Open Inventor and the MeVis Image Library by modular visual programming. No programming knowledge is required to set up image processing and visualization pipelines. Complete applications including user interfaces can be easily built within a general framework. In addition to the VTK/ITK features, MeVisLab provides a full integration of the Open Inventor library and offers a state-of-the-art integrated volume renderer. The integration of VTK/ITK algorithms is performed automatically: an XML structure is created from the toolkits' source code followed by an automatic module generation from this XML description. Thus, MeVisLab offers a one stop solution integrating VTK/ITK as modules and is suited for rapid prototyping as well as for teaching medical visualization and image analysis. The VTK/ITK integration is available as package of the free version of MeVisLab.

Towards optimization of probe placement for radio-frequency ablation

Abstract: We present a model for the optimal placement of mono- and bipolar probes in radio-frequency (RF) ablation. The model is based on a numerical computation of the probe’s electric potential and of the steady state of the heat distribution during RF ablation. The optimization is performed by minimizing a temperature based objective functional under these constraining equations. The paper discusses the discretization and implementation of the approach. Finally, applications of the optimization to artificial data and a comparison to a real RF ablation are presented.

Uncertainty in diffusion tensor based fibre tracking

Abstract: Background. diffusion tensor imaging and related fibre tracking techniques have the potential to identify major white matter tracts afflicted by an individual pathology or tracts at risk for a given surgical approach. However, the reliability of these techniques is known to be limited by image distortions, image noise, low spatial resolution, and the problem of identifying crossing fibres. This paper intends to bridge the gap between the requirements of neurosurgical applications and basic research on fibre tracking uncertainty.

Preoperative volume calculation of the hepatic venous draining areas with multi-detector row CT in adult living donor liver transplantation: Impact on surgical procedure.

Abstract: Objective The purpose was to assess the volumes of the different hepatic territories and especially the drainage of the right paramedian sector in adult living donor liver transplantation (ALDLT).

An Application Framework for Rapid Prototyping of Clinically Applicable Software Assistants.

Abstract: Computer assistance for clinical diagnosis support and treatment planning are continuously growing fields that have gained importance in several medical disciplines. Although a variety of algorithms are available today, only few are routinely applied for diagnosis support and treatment planning. We propose a hierarchical framework that allows for flexible and efficient development of clinically valuable software prototypes and for systematic evaluation of image processing methods in a research setting. A modular plug-in concept separates algorithmic and framework developments. Several basic components for data-, user-, and workflow-management provide a skeleton that can be customized by both application developer and user. Standardized interfaces allow the communication between both frame and application. Dedicated assistance is provided for an efficient radiological workflow integration. A flexible and simple handling of image processing and visualization algorithms within a modular programming interface is offered through an integration into a visual programming and rapid prototyping platform (MeVisLab). The capabilities of our framework are presented by means of exemplary prototypes, that are currently used in clinical practice.

A minimally-interactive watershed algorithm designed for efficient CTA bone removal

Abstract: We introduce a novel minimally-interactive watershed algorithm that needs no initial parameterization, but lets the user refine the automatic segmentation close to real-time. In contrast to previous proposals, our algorithm encapsulates all time consuming calculation in a processing step executed only once. Thereby, a hierarchical subdivision of the incoming image data is generated. This subdivision serves as a basis for computing automatic segmentation results according to a given multi-dimensional classification scheme as well as for interactive refinement according to local markers. We have successfully applied our algorithm to efficiently removing bone structures from computed tomography angiography data, which is among the very challenging segmentation problems in medical image analysis.

Brain structure visualization using spectral fiber clustering

Abstract: The visualization of human brain structure is an important new challenge in the area of computer graphics We present a novel algorithm that allows for visualizing white matter fiber tracts in realtime Related structure is grouped by our spectral clustering method very efficiently and curvature and spatial depth of the fibers are accentuated by new GPU-based illustrative rendering techniques Our fiber clustering results are much more accurate and comprehensible than that obtained by previous feature space methods

New Software Assistants for Cardiovascular Diagnosis.

Abstract: An important design criterion for current application development in cardiac image analysis is the applicability in clinical routine as well as in research environments. We present two novel applications dedicated to diagnosis support of the coronary heart disease. CT data of coronary arteries and cardiac function as well as MR data of myocardial perfusion are processed for quantitative anatomical and functional analysis. Semi-automatic segmentation methods are provided for a reliable representation of the coronary arteries and the left ventricular myocardium. Furthermore, quantitative parameters of the coronary vessels and the myocardium are computed. The novel approach is a standardization of the multi-parameter representation using advanced visualization techniques, that reveals possible correlations between vascular morphometry, ventricular function, and myocardial perfusion. Both prototypical applications are based on the visual programming and prototyping platform MeVisLab.

Towards a Workflow Oriented Software Assistance for the Radiofrequency Ablation .

Abstract: In recent years, radiofrequency ablation of liver tumors has become a serious alternative to surgical resection for unresectable colorectal metastases. The treatment success highly depends on an effective placement of the radiofrequency applicators into the tumor to get a sufficient coagulative necrosis. Therefore, several software tools have been developed for the support and planning of a good treatment strategy. The software solution proposed in this paper aims at the assistance of the radiologist at each stage of the ablation workflow, including the tasks of planning, intervention and treatment assessment.

Evaluation of Active Appearance Models for Cardiac MRI

Abstract: Robust delineation of short-axis cardiac magnetic resonance images (MRI) is a fundamental precondition for functional heart diagnostics. Segmentation of the myocardium and the left ventricular blood pool allows for the analysis of important quantitative parameters. Model-based segmentation methods based on representative image data provide an inherently stable tool for this task. We present an implementation and evaluation of 3-D Active Appearance Models for the segmentation of the left ventricle using actual clinical case images. Models created from varying random data sets have been evaluated and compared with manual segmentations.

Web-based Support of Time-critical Services for Image-based Intervention Planning.

Abstract: Preoperative risk assessment for image based surgery planning often requires considerable technical and personnel resources especially for certain complex interventions, such as liver surgery. The purpose of the project SIMPL was to establish a remote service for specialized tasks in medical image analysis and the visualization of results. In this context we developed a web-based system to support the service process. Requirements included an adaption to the existing clinical infrastructure, time constraints, and quality management support. The software design is based on a process modelling concept and modern web technologies are used for an implementation that fulfills the demands regarding security and independence of special software. The prototypical system has been tested during the SIMPL project with international clinical partners and is now used in optimized form on a regular basis.