GridCAD: Grid-based Computer-aided Detection System

The application of use case modeling in designing medical imaging information systems

Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control.

Dicoogle - an open source peer-to-peer PACS

Picture Archiving and Communication Systems (PACS) have been widely deployed in healthcare institutions, and they now constitute a normal commodity for practitioners. However, its installation, maintenance, and utilization are still a burden due to their heavy structures, typically supported by centralized computational solutions. In this paper, we present Dicoogle, a PACS archive supported by a document-based indexing system and by peer-to-peer (P2P) protocols. Replacing the traditional database storage (RDBMS) by a documental organization permits gathering and indexing data from file-based repositories, which allows searching the archive through free text queries. As a direct result of this strategy, more information can be extracted from medical imaging repositories, which clearly increases flexibility when compared with current query and retrieval DICOM services. The inclusion of P2P features allows PACS internetworking without the need for a central management framework. Moreover, Dicoogle is easy to install, manage, and use, and it maintains full interoperability with standard DICOM services.

Design of and technical challenges involved in a framework for multicentric radiotherapy treatment planning studies

This report introduces a framework for comparing radiotherapy treatment planning in multicentric in silico clinical trials. Quality assurance, data incompatibility, transfer and storage issues, and uniform analysis of results are discussed. The solutions that are given provide a useful guide for the set-up of future multicentric planning studies or public repositories of high quality data.

The future of PACS in healthcare enterprises

Picture Archiving and Communication System (PACS), which was originally designed as a tool for facilitating radiologists in interpreting images more efficiently, is evolving into a hospital-integrated system storing diagnostic imaging information that often reaches far beyond Radiology. The continuous evolution of PACS technology has led to a gradual broadening of its applications, ranging from teleradiology to CAD (Computer-Assisted Diagnosis) and multidimensional imaging, and is moving into the direction of providing access to image data outside the Radiology department, so to reach all the branches of the healthcare enterprise. New perspectives have been created thanks to new technologies (such as holographic media and GRID computing) that are likely due to expand PACS-based applications even further, improving patient care and enhancing overall productivity.

A virtual laboratory for medical image analysis

This paper presents the design, implementation, and usage of a virtual laboratory for medical image analysis. It is fully based on the Dutch grid, which is part of the Enabling Grids for E-sciencE (EGEE) production infrastructure and driven by the gLite middleware. The adopted service-oriented architecture enables decoupling the user-friendly clients running on the user's workstation from the complexity of the grid applications and infrastructure. Data are stored on grid resources and can be browsed/viewed interactively by the user with the Virtual Resource Browser (VBrowser). Data analysis pipelines are described as Scufl workflows and enacted on the grid infrastructure transparently using the MOTEUR workflow management system. VBrowser plug-ins allow for easy experiment monitoring and error detection. Because of the strict compliance to the grid authentication model, all operations are performed on behalf of the user, ensuring basic security and facilitating collaboration across organizations. The system has been operational and in daily use for eight months (December 2008), with six users, leading to the submission of 9000 jobs/month in average and the production of several terabytes of data.

Large-scale biomedical image analysis in grid environments

This paper presents the application of a component-based Grid middleware system for processing extremely large images obtained from digital microscopy devices. We have developed parallel, out-of-core techniques for different classes of data processing operations employed on images from confocal microscopy scanners. These techniques are combined into a data preprocessing and analysis pipeline using the component-based middleware system. The experimental results show that: 1) our implementation achieves good performance and can handle very large datasets on high-performance Grid nodes, consisting of computation and/or storage clusters and 2) it can take advantage of Grid nodes connected over high-bandwidth wide-area networks by combining task and data parallelism.

caGrid 1.0: an enterprise Grid infrastructure for biomedical research

OBJECTIVE

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research.

DESIGN

An enterprise Grid software infrastructure, called caGrid version 1.0 (caGrid 1.0), has been developed as the core Grid architecture of the NCI-sponsored cancer Biomedical Informatics Grid (caBIG) program. It is designed to support a wide range of use cases in basic, translational, and clinical research, including 1) discovery, 2) integrated and large-scale data analysis, and 3) coordinated study.

MEASUREMENTS

The caGrid is built as a Grid software infrastructure and leverages Grid computing technologies and the Web Services Resource Framework standards. It provides a set of core services, toolkits for the development and deployment of new community provided services, and application programming interfaces for building client applications.

RESULTS

The caGrid 1.0 was released to the caBIG community in December 2006. It is built on open source components and caGrid source code is publicly and freely available under a liberal open source license. The core software, associated tools, and documentation can be downloaded from the following URL: https://cabig.nci.nih.gov/workspaces/Architecture/caGrid.

CONCLUSIONS

While caGrid 1.0 is designed to address use cases in cancer research, the requirements associated with discovery, analysis and integration of large scale data, and coordinated studies are common in other biomedical fields. In this respect, caGrid 1.0 is the realization of a framework that can benefit the entire biomedical community.

How to implement grid technology in tissue-based diagnosis: diagnostic surgical pathology

BACKGROUND

Tissue-based diagnosis or diagnostic surgical pathology is a highly accurate, sensitive and specific medical diagnostic technique that has expanded rapidly in using both molecular biology and computer technology.

OBJECTIVE

The objective is to analyze the present stage and potential influence of distributed data acquisition, analysis and presentation in tissue-based diagnosis by using recently developed standardized network systems such as grids.

METHODS

Interpretation of medical data is often based upon specialized examination, visual information acquisition and transfer as well as upon data collected from various sources. Efficient and accurate diagnostics require standardized data and transfer modes, which can be provided by a grid environment. The medical requirements, construction of an adequate grid environment, practical experiences in various medical disciplines and potential use in tissue-based diagnosis are described.

CONCLUSIONS

Grid technology is probably a useful tool to meet the conditions of tissue-based diagnosis in the near future, and will probably play a significant role in its further development.

Sharing data and analytical resources securely in a biomedical research Grid environment

OBJECTIVES

To develop a security infrastructure to support controlled and secure access to data and analytical resources in a biomedical research Grid environment, while facilitating resource sharing among collaborators.

DESIGN

A Grid security infrastructure, called Grid Authentication and Authorization with Reliably Distributed Services (GAARDS), is developed as a key architecture component of the NCI-funded cancer Biomedical Informatics Grid (caBIG). The GAARDS is designed to support in a distributed environment 1) efficient provisioning and federation of user identities and credentials; 2) group-based access control support with which resource providers can enforce policies based on community accepted groups and local groups; and 3) management of a trust fabric so that policies can be enforced based on required levels of assurance.

MEASUREMENTS

GAARDS is implemented as a suite of Grid services and administrative tools. It provides three core services: Dorian for management and federation of user identities, Grid Trust Service for maintaining and provisioning a federated trust fabric within the Grid environment, and Grid Grouper for enforcing authorization policies based on both local and Grid-level groups.

RESULTS

The GAARDS infrastructure is available as a stand-alone system and as a component of the caGrid infrastructure. More information about GAARDS can be accessed at http://www.cagrid.org.

CONCLUSIONS

GAARDS provides a comprehensive system to address the security challenges associated with environments in which resources may be located at different sites, requests to access the resources may cross institutional boundaries, and user credentials are created, managed, revoked dynamically in a de-centralized manner.