Kirsten Meetz

A Radial Structure Tensor and Its Use for Shape-Encoding Medical Visualization of Tubular and Nodular Structures

The concept of curvature and shape-based rendering is beneficial for medical visualization of CT and MRI image volumes. Color-coding of local shape properties derived from the analysis of the local Hessian can implicitly highlight tubular structures such as vessels and airways, and guide the attention to potentially malignant nodular structures such as tumors, enlarged lymph nodes, or aneurysms. For some clinical applications, however, the evaluation of the Hessian matrix does not yield satisfactory renderings, in particular for hollow structures such as airways, and densely embedded low contrast structures such as lymph nodes. Therefore, as a complement to Hessian-based shape-encoding rendering, this paper introduces a combination of an efficient sparse radial gradient sampling scheme in conjunction with a novel representation, the radial structure tensor (RST). As an extension of the well-known general structure tensor, which has only positive definite eigenvalues, the radial structure tensor correlates position and direction of the gradient vectors in a local neighborhood, and thus yields positive and negative eigenvalues which can be used to discriminate between different shapes. As Hessian-based rendering, also RST-based rendering is ideally suited for GPU implementation. Feedback from clinicians indicates that shape-encoding rendering can be an effective image navigation tool to aid diagnostic workflow and quality assurance.

Coupled deformable models with spatially varying features for quantitative assessment of left ventricular function from cardiac MRI

Cardiac MRI has improved the diagnosis of cardiovascular diseases by enabling the quantitative assessment of functional parameters. This requires an accurate identification of the myocardium of the left ventricle. This paper describes a novel segmentation technique for automated delineation of the myocardium. We propose to use prior knowledge by integrating a statistical shape model and a spatially varying feature model into a deformable mesh adaptation framework. Our shape model consists of a coupled, layered triangular mesh of the epi- and endocardium. It is adapted to the image by iteratively carrying out i) a surface detection and ii) a mesh reconfiguration by energy minimization. For surface detection a feature search is performed to find the point with the best feature combination. To accommodate the different tissue types the triangles of the mesh are labeled, resulting in a spatially varying feature model. The energy function consists of two terms: an external energy term, which attracts the triangles towards the features, and an internal energy term, which preserves the shape of the mesh. We applied our method to 40 cardiac MRI data sets (FFE-EPI) and compared the results to manual segmentations. A mean distance of about 3 mm with a standard deviation of 2 mm to the manual segmentations was achieved.

Workflow Management Systems—A powerful means to integrate radiologic processes and application systems

This presentation describes a research project investigating the suitability of model-based Workflow Management Systems (WfMS) to support radiological process. The following aspects are covered: process modeling, process enactment, and architecture of workflow-enabled application systems.

Motion compensation and plane tracking for kinematic MR-Imaging

The acquisition of time series of 3D MR images is becoming feasible nowadays, which enables the assessment of bone and soft tissue in normal and abnormal joint motion. Fast two-dimensional (2D) scanning of moving joints may also provide high temporal resolution but is limited to a single, predefined slice. Acquiring 3D time series has the advantage that after the acquisition image processing and visualization techniques can be used to reformat the images to any orientation and to reduce the through-plane motion and undesired gross motion superimposed on the relevant joint movement. In this publication, we first review such post-processing techniques for retrospective tracking of viewing planes according to a single moving rigid body (e.g. bone). Then, we present new numerical schemes for optimally tracking viewing planes according to the movement of multiple structures to compensate for their through- as well as in-plane motion. These structures can be specified in an interactive viewing program, and the motion compensated movies can be updated and displayed in real-time. The post-processing algorithms require a 4D motion-field estimation which also can be utilized to interpolate intermediate images to present the final movies in smooth cine-loops and to significantly improve the visual perceptibility of complex joint movement.

Workflow management systems in radiology

In a situation of shrinking health care budgets, increasing cost pressure and growing demands to increase the efficiency and the quality of medical services, health care enterprises are forced to optimize or complete re-design their processes. Although information technology is agreed to potentially contribute to cost reduction and efficiency improvement, the real success factors are the re-definition and automation of processes: Business Process Re-engineering and Workflow Management. In this paper we discuss architectures for the use of workflow management systems in radiology. We propose to move forward from information systems in radiology (RIS, PACS) to Radiology Management Systems, in which workflow functionality (process definitions and process automation) is implemented through autonomous workflow management systems (WfMS). In a workflow oriented architecture, an autonomous workflow enactment service communicates with workflow client applications via standardized interfaces. In this paper, we discuss the need for and the benefits of such an approach. The separation of workflow management system and application systems is emphasized, and the consequences that arise for the architecture of workflow oriented information systems. This includes an appropriate workflow terminology, and the definition of standard interfaces for workflow aware application systems. Workflow studies in various institutions have shown that most of the processes in radiology are well structured and suited for a workflow management approach. Numerous commercially available Workflow Management Systems (WfMS) were investigated, and some of them, which are process- oriented and application independent, appear suitable for use in radiology.

Automatic assessment of the quality of patient positioning in mammography

Quality assurance has been recognized as crucial for the success of population-based breast cancer screening programs using x-ray mammography. Quality guidelines and criteria have been defined in the US as well as the European Union in order to ensure the quality of breast cancer screening. Taplin et al. report that incorrect positioning of the breast is the major image quality issue in screening mammography. Consequently, guidelines and criteria for correct positioning and for the assessment of the positioning quality in mammograms play an important role in the quality standards. In this paper we present a system for the automatic evaluation of positioning quality in mammography according to the existing standardized criteria. This involves the automatic detection of anatomic landmarks in medio- lateral oblique (MLO) and cranio-caudal (CC) mammograms, namely the pectoral muscle, the mammilla and the infra-mammary fold. Furthermore, the detected landmarks are assessed with respect to their proper presentation in the image. Finally, the geometric relations between the detected landmarks are investigated to assess the positioning quality. This includes the evaluation whether the pectoral muscle is imaged down to the mammilla level, and whether the posterior nipple line diameter of the breast is consistent between the different views (MLO and CC) of the same breast. Results of the computerized assessment are compared to ground truth collected from two expert readers.

Worklist handling in workflow-enabled radiological application systems

For the next generation integrated information systems for health care applications, more emphasis has to be put on systems which, by design, support the reduction of cost, the increase inefficiency and the improvement of the quality of services. A substantial contribution to this will be the modeling. optimization, automation and enactment of processes in health care institutions. One of the perceived key success factors for the system integration of processes will be the application of workflow management, with workflow management systems as key technology components. In this paper we address workflow management in radiology. We focus on an important aspect of workflow management, the generation and handling of worklists, which provide workflow participants automatically with work items that reflect tasks to be performed. The display of worklists and the functions associated with work items are the visible part for the end-users of an information system using a workflow management approach. Appropriate worklist design and implementation will influence user friendliness of a system and will largely influence work efficiency. Technically, in current imaging department information system environments (modality-PACS-RIS installations), a data-driven approach has been taken: Worklist -- if present at all -- are generated from filtered views on application data bases. In a future workflow-based approach, worklists will be generated by autonomous workflow services based on explicit process models and organizational models. This process-oriented approach will provide us with an integral view of entire health care processes or sub- processes. The paper describes the basic mechanisms of this approach and summarizes its benefits.

Breast Conserving Surgery Outcome Prediction: A Patient-Specific, Integrated Multi-modal Imaging and Mechano-Biological Modelling Framework

Patient-specific surgical predictions of Breast Conserving Therapy, through mechano-biological simulations, could inform the shared decision making process between clinicians and patients by enabling the impact of different surgical options to be visualised. We present an overview of our processing workflow that integrates MR images and three dimensional optical surface scans into a personalised model. Utilising an interactively generated surgical plan, a multi-scale open source finite element solver is employed to simulate breast deformity based on interrelated physiological and biomechanical processes that occur post surgery. Our outcome predictions, based on the pre-surgical imaging, were validated by comparing the simulated outcome with follow-up surface scans of four patients acquired 6 to 12 months post-surgery. A mean absolute surface distance of 3.3i¾?mm between the follow-up scan and the simulation was obtained.