Viewpoints on Medical Image Processing: From Science to Application.

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics.

Image analysis and modeling in medical image computing. Recent developments and advances.

Background: Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g.

Advances in medical image computing.

Objectives: Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care.

Integration of decentralized clinical data in a data warehouse: a service-oriented design and realization.

Objectives: In this paper we present a general concept and describe the difficulties for the integration of data from various clinical partners in one data warehouse using the Open European Nephrology Science Center (OpEN.SC) as an example. This includes a requirements analysis of the data integration process and also the design according to these requirements.

Grid computing for detailed hemodynamics-simulation-based planning of endovascular interventions.

Detailed numerical simulations of blood flow in arteries with various malformations and its conjugate loads on the vessel walls have been a research topic for specialized medical and engineering communities over decades. The present state of computing resources and software allows access to these elaborate diagnostic and research tools to a broad user circle and even to integrate them into clinical workflows. To tap the full potential of hemodynamic simulations, a Grid-based "virtual vessel surgery" application has been developed and deployed as part of the image processing module of the MediGRID project of the German Federal Ministry of Education and Science (BMBF).

Classification models for early detection of prostate cancer.

We investigate the performance of different classification models and their ability to recognize prostate cancer in an early stage. We build ensembles of classification models in order to increase the classification performance. We measure the performance of our models in an extensive cross-validation procedure and compare different classification models.

DICOM image communication in globus-based medical grids.

Grid computing, the collaboration of distributed resources across institutional borders, is an emerging technology to meet the rising demand on computing power and storage capacity in fields such as high-energy physics, climate modeling, or more recently, life sciences. A secure, reliable, and highly efficient data transport plays an integral role in such grid environments and even more so in medical grids. Unfortunately, many grid middleware distributions, such as the well-known Globus Toolkit, lack the integration of the world-wide medical image communication standard Digital Imaging and Communication in Medicine (DICOM).

Automatic parameter optimization for de-noising MR data.

This paper describes an automatic parameter optimization method for anisotropic diffusion filters used to de-noise 2D and 3D MR images. The filtering process is integrated into a closed-loop system where image improvement is monitored indirectly by comparing the characteristics of the suppressed noise with those of the assumed noise model at the optimal point. In order to verify the performance of this approach, experimental results obtained with this method are presented together with the results obtained by median and k-nearest neighbor filters.

Advances in biomedical image analysis--past, present and future challenges.

Starting from raw data files coding eight bits of gray values per image pixel and identified with no more than eight characters to refer to the patient, the study, and technical parameters of the imaging modality, biomedical imaging has undergone manifold and rapid developments. Today, rather complex protocols such as Digital Imaging and Communications in Medicine (DICOM) are used to handle medical images. Most restrictions to image formation, visualization, storage and transfer have basically been solved and image interpretation now sets the focus of research.

3D reconstruction of organ surfaces using model-based snakes.

In this article a new segmentation approach is described that is based on case-based reasoning and a combination of various established image processing concepts described in the current literature. Previously segmented data sets are used as anatomical models that represent the cases, called reference models. They describe the expected surface shape and representation of the organ in the data material.

XML knowledge database of MRI-derived eye models.

In a model-based approach, MR images were used to build a database of individual eye models. In order to store the features of the specific eye morphology in an extensible, structured and Internet-accessible database, an appropriate XML structure was implemented. A document type definition was developed that managed the data of the correlated feature space and defined associations via training data sets.

Feature extraction and supervised classification of MR images to support proton radiation therapy of eye tumors.

Proton therapy has the potential for high-precision radiotherapy of retinal tumors. However, the standardized eye models currently used do not fully account for the patient's individual anatomy. To better exploit the data provided by MR images, a model-based approach was used based on a database of eye models.

Feature-based, automated segmentation of cerebral infarct patterns using T2- and diffusion-weighted imaging.

Diffusion-weighted imaging enables the diagnosis of cerebral ischemias very early, thus supporting therapies such as thrombolysis. However, morphology and tissue-characterizing parameters (e.g.

Simulation and analysis of magnetic resonance elastography wave images using coupled harmonic oscillators and Gaussian local frequency estimation.

New methods for simulating and analyzing Magnetic Resonance Elastography (MRE) images are introduced. To simulate a two-dimensional shear wave pattern, the wave equation is solved for a field of coupled harmonic oscillators with spatially varying coupling and damping coefficients in the presence of an external force. The spatial distribution of the coupling and the damping constants are derived from an MR image of the investigated object.

Volume-selective proton MR spectroscopy for in-vitro quantification of anticonvulsants.

Administration of anticonvulsant drugs is clinically monitored by checking seizure frequency and by determining the serum concentration of the drug. In a few reports, drug concentrations in brain parenchyma have been determined using ex vivo techniques. Little is known about the in vivo concentration in the brain parenchyma.

Implementation of a dynamic platform-independent DICOM-server.

Hospital-wide image and patient data transfer within heterogeneous hard- and software infrastructures can be facilitated by using standardized communication protocols and data formats such as digital imaging and communications in medicine (DICOM). Each DICOM application entity (AE) usually provides a static and fixed set of services according to its functionality. However, certain security concepts, changing demands of medical users, or restricted hardware capabilities may be more easily addressed by applications that dynamically provide variable subsets of DICOM services.

Realization of security concepts for DICOM-based distributed medical services.

Exploiting distributed hard- and software resources for telemedicine requires a fast, secure, and platform-independent data exchange. Standards without inherent security mechanisms such as DICOM may ease non-authorized data access. Therefore, exemplary telemedical data streams were analyzed within the Berlin metropolitan area network using specialized magnetic resonance imaging techniques and distributed resources for data postprocessing.

Prototype of a JAVA/DICOM image server with integrated findings and data security.

The transfer of medical data within heterogeneous hard- and software infrastructures requires platform-independent standardized protocols and data formats such as DICOM. To avoid costly vendor-specific solutions a DICOM server was implemented in JAVA thereby enabling the data access via internet browser technology. The most important patient and image acquisition information were extracted from the DICOM images and stored into a relational database.

Histogram-based characterization of healthy and ischemic brain tissues using multiparametric MR imaging including apparent diffusion coefficient maps and relaxometry.

Decreased, renormalized, or increased values of the calculated apparent diffusion coefficient (ADC) are observed in stroke models. A quantitative description of corresponding tissue states using ADC values may be extended to include true relaxation times. A histogram-based segmentation is well suited for characterizing tissues according to specific parameter combinations irrespective of the heterogeneity found for human healthy and ischemic brain tissues.

Virtual 3D cutting for bone segment extraction in maxillofacial surgery planning.

An important step toward our main goal of a completely computer-based maxillofacial surgical planning system is the availability of tools for the surgeon to define bone segments from skull and jaw bones. We have developed an easy-to-handle user interface that employs visual and force-feedback devices to define subvolumes of a patient's volume dataset. This interface is a main component of our maxillofacial surgical planning tool MeVisTo-Jaw [1].