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Biomedical subjects

James F Brinkley

Publications and source records attributed to James F Brinkley.

12 recordsLinked to original sources
PubMed2005

Knowledge-based, interactive, custom anatomical scene creation for medical education: the Biolucida system.

Few biomedical subjects of study are as resource-intensive to teach as gross anatomy. Medical education stands to benefit greatly from applications which deliver virtual representations of human anatomical structures. While many applications have been created to achieve this goal, their utility to the student is limited because of a lack of interactivity or customizability by expert authors. Here we describe the first version of the Biolucida system, which allows an expert anatomist author to create knowledge-based, customized, and fully interactive scenes and lessons for students of human macroscopic anatomy. Implemented in Java and VRML, Biolucida allows the sharing of these instructional 3D environments over the internet. The system simplifies the process of authoring immersive content while preserving its flexibility and expressivity.

Anatomy↗
PubMed2004

Server-based approach to web visualization of integrated three-dimensional brain imaging data.

The authors describe a client-server approach to three-dimensional (3-D) visualization of neuroimaging data, which enables researchers to visualize, manipulate, and analyze large brain imaging datasets over the Internet. All computationally intensive tasks are done by a graphics server that loads and processes image volumes and 3-D models, renders 3-D scenes, and sends the renderings back to the client. The authors discuss the system architecture and implementation and give several examples of client applications that allow visualization and analysis of integrated language map data from single and multiple patients.

Anatomy, Cross-Sectional↗
PubMed2004

Processes and problems in the formative evaluation of an interface to the Foundational Model of Anatomy knowledge base.

The Digital Anatomist Foundational Model of Anatomy (FMA) is a large semantic network of more than 100,000 terms that refer to the anatomical entities, which together with 1.6 million structural relationships symbolically represent the physical organization of the human body. Evaluation of such a large knowledge base by domain experts is challenging because of the sheer size of the resource and the need to evaluate not just classes but also relationships. To meet this challenge, the authors have developed a relation-centric query interface, called Emily, that is able to query the entire range of classes and relationships in the FMA, yet is simple to use by a domain expert. Formative evaluation of this interface considered the ability of Emily to formulate queries based on standard anatomy examination questions, as well as the processing speed of the query engine. Results show that Emily is able to express 90% of the examination questions submitted to it and that processing time is generally 1 second or less, but can be much longer for complex queries. These results suggest that Emily will be a very useful tool, not only for evaluating the FMA, but also for querying and evaluating other large semantic networks.

Anatomy↗
PubMed2003

OQAFMA Querying agent for the Foundational Model of Anatomy: a prototype for providing flexible and efficient access to large semantic networks.

The development of large semantic networks, such as the UMLS, which are intended to support a variety of applications, requires a flexible and efficient query interface for the extraction of information. Using one of the source vocabularies of UMLS as a test bed, we have developed such a prototype query interface. We first identify common classes of queries needed by applications that access these semantic networks. Next, we survey StruQL, an existing query language that we adopted, which supports all of these classes of queries. We then describe the OQAFMA Querying Agent for the Foundational Model of Anatomy (OQAFMA), which provides an efficient implementation of a subset of StruQL by pre-computing a variety of indices. We describe how OQAFMA leverages database optimization by converting StruQL queries to SQL. We evaluate the flexibility and efficiency of our implementation using English queries written by anatomists. This evaluation verifies that OQAFMA provides flexible, efficient access to one such large semantic network, the Foundational Model of Anatomy, and suggests that OQAFMA could be an efficient query interface to other large biomedical knowledge bases, such as the Unified Medical Language System.

Abstracting and Indexing↗
PubMed2003

A prototype natural language interface to a large complex knowledge base, the Foundational Model of Anatomy.

We describe a constrained natural language interface to a large knowledge base, the Foundational Model of Anatomy (FMA). The interface, called GAPP, handles simple or nested questions that can be parsed to the form, subject-relation-object, where subject or object is unknown. With the aid of domain-specific dictionaries the parsed sentence is converted to queries in the StruQL graph-searching query language, then sent to a server we developed, called OQAFMA, that queries the FMA and returns output as XML. Preliminary evaluation shows that GAPP has the potential to be used in the evaluation of the FMA by domain experts in anatomy.

Anatomy↗
PubMed2003

Dynamic XML-based exchange of relational data: application to the Human Brain Project.

This paper discusses an approach to exporting relational data in XML format for data exchange over the web. We describe the first real-world application of SilkRoute, a middleware program that dynamically converts existing relational data to a user-defined XML DTD. The application, called XBrain, wraps SilkRoute in a Java Server Pages framework, thus permitting a web-based XQuery interface to a legacy relational database. The application is demonstrated as a query interface to the University of Washington Brain Project's Language Map Experiment Management System, which is used to manage data about language organization in the brain.

Brain↗
PubMed2003

Efficient web-based navigation of the Foundational Model of Anatomy.

The University of Washington's Foundational Model of Anatomy (FMA)1 is a complex, frame-based model composed of over 170,000 frames collectively specified by more than 1.4 million slot values. The Foundational Model Explorer (FME) was designed to provide simple and intuitive web access to this complex knowledge base. The Foundational Model Explorer (FME) (Figure 1) is built upon the Protégé 2000 knowledge base access library [http://protege.stanford.edu/]. The FME application, associated libraries, and the FMA database all reside on remote servers. Users of the FME are not required to download, install, or set-up any of these components. The FME application, in response to a query, retrieves the appropriate information from the FMA, formats these data into html documents, and transmits them, via the Internet, back to the client where they can be viewed from any standard web browser

Anatomy↗
PubMed2003

The evolving neuroanatomical component of the Foundational Model of Anatomy.

In order to meet the need for an expressive ontology in neuroinformatics, we have integrated the extensive terminologies of NeuroNames and Terminologia Anatomica into the Foundational Model of Anatomy (FMA). We have enhanced the FMA to accommodate information unique to neuronal structures, such as axonal input/output relationships.

Anatomy↗
PubMed2002

Shape-based cortical surface segmentation for visualization brain mapping.

We describe a knowledge-based approach to cortical surface segmentation that uses learned knowledge of the overall shape and range of variation of the cortex (excluding the detailed gyri and sulci) to guide the search for the grey-CSF boundary in a structural MRI image volume. The shape knowledge is represented by a radial surface model, which is a type of geometric constraint network (GCN) that we hypothesize can represent shape by networks of locally interacting constraints. The shape model is used in a protocol for visualization-based mapping of cortical stimulation mapping (CSM) sites onto the brain surface, prior to integration with other mapping modalities or as input to existing surface analysis and reconfiguration programs. Example results are presented for CSM data related to language organization in the cortex, but the methods should be applicable to other situations where a realistic visualization of the brain surface, as seen at neurosurgery, is desired.

Brain Mapping↗
PubMedDate not supplied

WIRM: an open source toolkit for building biomedical web applications.

This article describes an innovative software toolkit that allows the creation of web applications that facilitate the acquisition, integration, and dissemination of multimedia biomedical data over the web, thereby reducing the cost of knowledge sharing. There is a lack of high-level web application development tools suitable for use by researchers, clinicians, and educators who are not skilled programmers. Our Web Interfacing Repository Manager (WIRM) is a software toolkit that reduces the complexity of building custom biomedical web applications. WIRM's visual modeling tools enable domain experts to describe the structure of their knowledge, from which WIRM automatically generates full-featured, customizable content management systems.

Anatomy↗