Frans A. Gerritsen

A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations

This work presents a framework for non-rigid registration which extends and generalizes a previously developed technique by Rueckert et al. [1]. We combine multi-resolution optimization with free-form deformations (FFDs) based on multi-level B-splines to simulate a non-uniform control point distribution. We have applied this to a number of different medical registration tasks to demonstrate its wide applicability, including interventional MRI brain tissue deformation compensation, breathing motion compensation in liver MRI, intra-modality inter-modality registration of pre-operative brain MRI to CT electrode implant data, and inter-subject registration of brain MRI. Our results demonstrate that the new algorithm can successfully register images with an improved performance, while achieving a significant reduction in run-time.

Visualization of boundaries in volumetric data sets using LH histograms

A crucial step in volume rendering is the design of transfer functions that highlights those aspects of the volume data that are of interest to the user. For many applications, boundaries carry most of the relevant information. Reliable detection of boundaries is often hampered by limitations of the imaging process, such as blurring and noise. We present a method to identify the materials that form the boundaries. These materials are then used in a new domain that facilitates interactive and semiautomatic design of appropriate transfer functions. We also show how the obtained boundary information can be used in region-growing-based segmentation.

Automatic Contour Propagation in Cine Cardiac Magnetic Resonance Images

We have developed a method for automatic contour propagation in cine cardiac magnetic resonance images. The method consists of a new active contour model that tries to maintain a constant contour environment by matching gray values in profiles perpendicular to the contour. Consequently, the contours should maintain a constant position with respect to neighboring anatomical structures, such that the resulting contours reflect the preferences of the user. This is particularly important in cine cardiac magnetic resonance images because local image features do not describe the desired contours near the papillary muscle. The accuracy of the propagation result is influenced by several parameters. Because the optimal setting of these parameters is application dependent, we describe how to use full factorial experiments to optimize the parameter setting. We have applied our method to cine cardiac magnetic resonance image sequences from the long axis two-chamber view, the long axis four-chamber view, and the short axis view. We performed our optimization procedure for each contour in each view. Next, we performed an extensive clinical validation of our method on 69 short axis data sets and 38 long axis data sets. In the optimal parameter setting, our propagation method proved to be fast, robust, and accurate. The resulting cardiac contours are positioned within the interobserver ranges of manual segmentation. Consequently, the resulting contours can be used to accurately determine physiological parameters such as stroke volume and ejection fraction

CoViCAD: Comprehensive Visualization of Coronary Artery Disease

We present novel, comprehensive visualization techniques for the diagnosis of patients with coronary artery disease using segmented cardiac MRI data. We extent an accepted medical visualization technique called the bulls eye plot by removing discontinuities, preserving the volumetric nature of the left ventricular wall and adding anatomical context. The resulting volumetric bulls eye plot can be used for the assessment of transmurality. We link these visualizations to a 3D view that presents viability information in a detailed anatomical context. We combine multiple MRI scans (whole heart anatomical data, late enhancement data) and multiple segmentations (polygonal heart model, late enhancement contours, coronary artery tree). By selectively combining different rendering techniques we obtain comprehensive yet intuitive visualizations of the various data sources.

Automating transfer function design for volume rendering using hierarchical clustering of material boundaries

Transfer function design plays a crucial role in direct volume rendering. Furthermore, it has a major influence on the efficiency of the visualization process. We have developed a framework that facilitates the semi-automatic design of transfer functions. Similarly to other approaches we generate clusters in the transfer function domain. We created a real-time interaction with a hierarchy of clusters. This interaction effectively substitutes cumbersome settings of clustering thresholds. Our framework is also able to easily combine different clustering criteria. We have developed two similarity measures for clustering of material boundaries. One is based on the similarity of the boundaries in the transfer function domain and the other on their spatial relation. We use the LH space as the transfer function domain. This space facilitates the clustering of material boundaries. We demonstrate our approach on several examples.

Automatic Detection of Pulmonary Embolism in CTA Images

Pulmonary embolism (PE) is a common life-threatening disorder for which an early diagnosis is desirable. We propose a new system for the automatic detection of PE in contrast-enhanced CT images. The system consists of candidate detection, feature computation and classification. Candidate detection focusses on the inclusion of PE-even complete occlusions-and the exclusion of false detections, such as tissue and parenchymal diseases. Feature computation does not only focus on the intensity, shape and size of an embolus, but also on locations and the shape of the pulmonary vascular tree. Several classifiers have been tested and the results show that the performance is optimized by using a bagged tree classifier with two features based on the shape of a blood vessel and the distance to the vessel boundary. The system was trained on 38 CT data sets. Evaluation on 19 other data sets showed that the system generalizes well. The sensitivity of our system on the evaluation data is 63% at 4.9 false positives per data set, which allowed the radiologist to improve the number of detected PE by 22%.

Myocardial delineation via registration in a polar coordinate system1

Rationale and Objectives. Cardiovascular disease is the number one cause of premature death in the western world. Analysis of cardiac function provides clinically useful diagnostic and prognostic information; however, manual analysis of function via delineation is prohibitively time consuming. This article describes a technique for analysis of dynamic magnetic resonance images of the left ventricle using a non-rigid registration algorithm. A manually delineated contour of a single phase was propagated through the dynamic sequence. Materials and Methods. Short-axis cine magnetic resonance images were resampled into polar coordinates before all the time frames were aligned using a non-rigid registration algorithm. The technique was tested on 10 patient data sets, a total of 1,052 images were analyzed. Results. Results of this approach were investigated and compared with manual delineation at all phases in the cardiac cycle, and with registration performed in a Cartesian coordinate system. The results correlated very well with manually delineated contours. Conclusion. A novel approach to the registration and subsequent delineation of cardiac magnetic resonance images has been introduced. For the endocardium, the polar resampling technique correlated well with manual delineation, and better than for images registered without radial resampling in a Cartesian coordinate system. For the epicardium, the difference was not as apparent with both techniques correlating well.

Improved visualization in virtual colonoscopy using image-based rendering

Virtual colonoscopy (VC) is a patient-friendly alternative for colorectal endoscopic examination. We explore visualization aspects of VC such as surface in view, navigation and communication of a diagnosis. A series of unfolded cubes presents an animated full 360-degree omnidirectional field-of-view to the physician, to facilitate thorough and rapid inspection. For communication between physicians a tool has been designed that uses image-based rendering. Clinical evaluation has shown a reduction in inspection time from 19 minutes to 7 minutes without loss of sensitivity. With current virtual colonoscopy using a 2-sided view only 94% of the surface is available for exploration. In our approach the surface in view is increased to potentially 100%. Thus, the entire colon can be explored with better confidence that no regions are missed.

Computer Assisted Quantitative Analysis of Deformities of the Human Spine

Nowadays, conventional X-ray radiographs are still the images of choice for evaluating spinal deformaties such as scoliosis. However, digital translation reconstruction gives easy access to high quality, digital overview images of the entire spine. This work aims at improving the description of the scoliotic deformity by developing semi-automated tools to assist the extraction of anatomical landmarks (on vertebral bodies and pedicles) and the calculation of deformity quantifying parameters. These tools are currently validated in a clinical setting.

Computational Mesh Generation for Vascular Structures with Deformable Surfaces

Computational blood flow and vessel wall mechanics simulations for vascular structures are becoming an important research tool for patient-specific surgical planning and intervention. An important step in the modelling process for patient-specific simulations is the creation of the computational mesh based on the segmented geometry. Most known solutions either require a large amount of manual processing or lead to a substantial difference between the segmented object and the actual computational domain. We have developed a chain of algorithms that lead to a closely related implementation of image segmentation with deformable models and 3D mesh generation. The resulting processing chain is very robust and leads both to an accurate geometrical representation of the vascular structure as well as high quality computational meshes. The chain of algorithms has been tested on a wide variety of shapes. A benchmark comparison of our mesh generation application with five other available meshing applications clearly indicates that the new approach outperforms the existing methods in the majority of cases.