Medical information systems based in different hospital departments face tremendous difficulty in information exchange and dissemination due to the multitudes of hardware and software platforms running these systems. In this paper, we describe a distributed information system for integrating various hospital systems in supporting clinical neuroimaging research and epilepsy surgical planning. Our distributed information system uses a three-tiered architecture consists of a user-interface tier, application logic tier and data store tier. Two system implementations based on this software architecture but using different integration technologies were developed and are discussed in this paper: the XML (extensible Mark Up Language)-based implementation and the CORBA (Common Object Request Broker Architecture)-based implementation. In the XML-based implementation, application logic tier communicates with user-interface tier and data store tier using HTTP and XML for data exchange. For the data exchange in CORBA-based implementation, the middleware uses IIOP (Internet inter-ORB protocol) to call CORBA objects in the data store tier then to return the results to the user-interface tier. For the user-interface tier of either implementation, the Web browsers are served as clients to invoke application components or agents in the middleware. The application of the proposed distributed system allows clinical users to access, search and retrieve the multimedia information in any underlying computer systems with commonly used Web browsers. Preliminary results show that the system is effective for information integration and data sharing among the different departmental systems in the hospital for neuroimaging applications.
The purpose of this paper is to demonstrate the importance of building a brain imaging registry (BIR) on top of existing medical information systems including Picture Archiving Communication Systems (PACS) environment. We describe the design framework for a cluster of data marts whose purpose is to provide clinicians and researchers efficient access to a large volume of raw and processed patient images and associated data originating from multiple operational systems over time and spread out across different hospital departments and laboratories. The framework is designed using object-oriented analysis and design methodology. The BIR data marts each contain complete image and textual data relating to patients with a particular disease.
KEYWORDS: Multimedia, Epilepsy, Analytical research, Image retrieval, Magnetic resonance imaging, Picture Archiving and Communication System, Data modeling, 3D image processing, Data archive systems, Positron emission tomography
We described a web-based data warehousing method for retrieving and analyzing neurological multimedia information. The web-based method supports convenient access, effective search and retrieval of clinical textual and image data, and on-line analysis. To improve the flexibility and efficiency of multimedia information query and analysis, a three-tier, multimedia data warehouse for epilepsy research has been built. The data warehouse integrates clinical multimedia data related to epilepsy from disparate sources and archives them into a well-defined data model.
KEYWORDS: Medical imaging, Picture Archiving and Communication System, Epilepsy, Magnetic resonance imaging, Composites, Visualization, Imaging systems, Systems modeling, Image visualization, Positron emission tomography
The purpose of this paper is to introduce a new and important conceptual framework of software design for the medical imaging community using design patterns. Use cases are created to summarize operational scenarios of clinicians using the system to complete certain tasks such as image segmentation. During design the Unified Modeling Language is used to translate the use cases into modeling diagrams that describe how the system functions. Next, design patterns are applied to build models that describe how software components interoperate to deliver that functionality. The software components are implemented using the Java language, CORBA architecture, and other web technologies. The biomedical image information system is used in epilepsy neurosurgical planning and diagnosis. This article proposes the use of proven software design models for solving medical imaging informatics design problems. Design patterns provide an excellent vehicle to leverage design solutions that have worked in the past to solve the problems we face in building user-friendly, reliable, and efficient information systems. This work introduces this new technology for building increasing complex medical image information systems. The rigorous application of software design techniques is essential in building information systems that are easy to use, rich in functionality, maintainable, reliable, and updatable.
KEYWORDS: Systems modeling, Picture Archiving and Communication System, Epilepsy, Visualization, Medical imaging, Analytical research, Image processing, Databases, Medical research, Brain-machine interfaces
Information system modeling has historically been relegated to a low priority among the designers of information systems. Often times, there is a rush to design and implement hardware and software solutions after only the briefest assessments of the domain requirements. Although this process results in a rapid development cycle, the system usually does not satisfy the needs of the users and the developers are forced to re-program certain aspects of the system. It would be much better to create an accurate model of the system based on the domain needs so that the implementation of the solution satisfies the needs of the users immediately. It would also be advantageous to build extensibility into the model so that updates to the system could be carried out in an organized fashion. The significance of this research is the development of a new formal framework for the construction of a multimedia medical information system. This formal framework is constructed using visual modeling which provides a way of thinking about problems using models organized around real- world ideas. These models provide an abstract way to view complex problems, making them easier for one to understand. The formal framework is the result of an object-oriented analysis and design process that translates the systems requirements and functionality into software models. The usefulness of this information framework is demonstrated with two different applications in epilepsy research and care, i.e., surgical planning of epilepsy and decision threshold determination.
Surgical treatment of patients suffering from complex partial seizures requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography (EEG), psychological tests, and various neuroimaging modalities together to determine the location of this zone. We investigate the use of positron emission tomography (PET), magnetic resonance imaging (MRI), and magnetic resonance spectroscopy (MRS) in the presurgical workup and analysis of patients with complex partial seizures. The results of imaging studies of 25 patients are compared for lateralization accuracy and relative concordance.
KEYWORDS: Picture Archiving and Communication System, Medical imaging, Digital libraries, Data modeling, Databases, Image segmentation, Data communications, Visualization, Digital imaging, 3D image processing
The purpose of this presentation is to point out the issues of incorporating digital libraries (DL) technologies into picture archiving and communication systems (PACS). The DL technologies can be used to increase the knowledge content and utilities of PACS and associated medical information systems in providing a broader range of medical services. We further illustrate certain potential application areas with examples from a research prototype developed on top of the hospital-integrated PACS of UCSF.
Surgical treatment of temporal lobe epilepsy requires the localization of the epileptogenic zone for surgical resection. Currently, clinicians utilize electroencephalography, various neuroimaging modalities, and psychological tests together to determine the location of this zone. We investigate how a multimedia neuroimaging workstation built on top of the UCSF Picture Archiving and Communication System can be used to aid surgical planning of epilepsy and related brain diseases. This usage demonstrates the ability of the workstation to retrieve image and textural data from PACS and other image sources, register multimodality images, visualize and render 3D data sets, analyze images, generate new image and text data from the analysis, and organize all data in a relational database management system.
KEYWORDS: 3D modeling, Data modeling, Databases, Brain, Neuroimaging, Human-machine interfaces, Picture Archiving and Communication System, Medical imaging, 3D image processing, Magnetic resonance imaging
The huge data archive of the UCSF Hospital Integrated Picture Archiving and Communication System gives healthcare providers access to diverse kinds of images and text for diagnosis and patient management. Given the mass of information accessible, however, conventional graphical user interface (GUI) approach overwhelms the user with forms, menus, fields, lists, and other widgets and causes 'information overloading.' This article describes a new approach that complements the conventional GUI with 3D anatomical atlases and presents the usefulness of this approach with a clinical neuroimaging application.
KEYWORDS: Picture Archiving and Communication System, Image visualization, Databases, Visualization, Medical imaging, 3D image processing, Imaging systems, Image retrieval, Magnetic resonance imaging, Multimedia
Current generation of picture archiving and communication systems (PACS) lacks the capabilities to permit content-based searches to be made on image data and to visualize and render 3D image data in a cost effective manner. The purpose of this research project is to investigate a framework that will combine the storage and communication components of PACS with the power of content-based image indexing and 3D visualization. This presentation will describe the integrated architecture and tools of our experimental system with examples taken from applications of neurological surgical planning and assessment of pediatric bone age.
The World Wide Web (WWW) is becoming the predominant force for global information dissemination. The Web browsers are originally designed for the client computers to navigate and display hypermedia documents and image bitmaps stored at the server machines. Their capabilities must be extended with database query and interactive visualization before the Web could be useful for the medical imaging community. This paper presents the system design and tools for interactive query and visualization of medical images on the Web. Examples from breast and brain imaging applications are used to illustrate the operations and capabilities of such tools.
The purpose of this presentation is to report our image registration and analysis experience with a large-array biomagnetometer for magnetoencephaography (MEG) and a high resolution positron emission tomography (PET) scanner in the presurgical localization of spike sources of intractable epilepsy patients and in studying the relationship between metabolic and physiologic abnormalities detected in regions of interest during the evaluation. Findings of 12 epilepsy patients who underwent MEG and PET studies at UCSF are discussed.
Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the brain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstation to aid the noninvasive presurgical evaluation of epilepsy patients. These techniques include online access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitation of structural and functional information contained in the registered images. For illustration, we describe the use of these techniques in a patient case of nonlesional neocortical epilepsy. We also present out future work based on preliminary studies.
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