Image Data Management Research Articles

Class-specific metrics for multidimensional data projection applied to CBIR

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

Informatics in Radiology: Use of CouchDB for Document-based Storage of DICOM Objects

Picture archiving and communication systems traditionally have depended on schema-based Structured Query Language (SQL) databases for imaging data management. To optimize database size and performance, many such systems store a reduced set of Digital Imaging and Communications in Medicine (DICOM) metadata, discarding informational content that might be needed in the future. As an alternative to traditional database systems, document-based key-value stores recently have gained popularity. These systems store documents containing key-value pairs that facilitate data searches without predefined schemas. Document-based key-value stores are especially suited to archive DICOM objects because DICOM metadata are highly heterogeneous collections of tag-value pairs conveying specific information about imaging modalities, acquisition protocols, and vendor-supported postprocessing options. The authors used an open-source document-based database management system (Apache CouchDB) to create and test two such databases; CouchDB was selected for its overall ease of use, capability for managing attachments, and reliance on HTTP and Representational State Transfer standards for accessing and retrieving data. A large database was created first in which the DICOM metadata from 5880 anonymized magnetic resonance imaging studies (1,949,753 images) were loaded by using a Ruby script. To provide the usual DICOM query functionality, several predefined "views" (standard queries) were created by using JavaScript. For performance comparison, the same queries were executed in both the CouchDB database and a SQL-based DICOM archive. The capabilities of CouchDB for attachment management and database replication were separately assessed in tests of a similar, smaller database. Results showed that CouchDB allowed efficient storage and interrogation of all DICOM objects; with the use of information retrieval algorithms such as map-reduce, all the DICOM metadata stored in the large database were searchable with only a minimal increase in retrieval time over that with the traditional database management system. Results also indicated possible uses for document-based databases in data mining applications such as dose monitoring, quality assurance, and protocol optimization.

The Design and Implementation of Intelligent Community Monitoring System

This paper designs a stable, efficient and intelligent video surveillance system, which is based on the review and analysis of the domestic and internation. And it is related research work on the basis of the intelligent security monitoring. The system is used by the Web server and database server model, and it can detect the moving object in scene of monitor. Firstly this paper analyzes the structure of server system, it uses B/S, database, ActiveX technology and is completed finally. Secondly this paper realizes the video image data in bulk storage, read, update and maintenance by using the database. The bmp format will be converted to JPG format effectively to realize the image database compression. It is valued to the video image data storage and management. Finally, the accuracy and response time can be improved in moving object detection, which is based on background subtraction method

Data ontology and an information system realization for web-based management of image measurements.

Image acquisition, processing, and quantification of objects (morphometry) require the integration of data inputs and outputs originating from heterogeneous sources. Management of the data exchange along this workflow in a systematic manner poses several challenges, notably the description of the heterogeneous meta-data and the interoperability between the software used. The use of integrated software solutions for morphometry and management of imaging data in combination with ontologies can reduce meta-data loss and greatly facilitate subsequent data analysis. This paper presents an integrated information system, called LabIS. The system has the objectives to automate (i) the process of storage, annotation, and querying of image measurements and (ii) to provide means for data sharing with third party applications consuming measurement data using open standard communication protocols. LabIS implements 3-tier architecture with a relational database back-end and an application logic middle tier realizing web-based user interface for reporting and annotation and a web-service communication layer. The image processing and morphometry functionality is backed by interoperability with ImageJ, a public domain image processing software, via integrated clients. Instrumental for the latter feat was the construction of a data ontology representing the common measurement data model. LabIS supports user profiling and can store arbitrary types of measurements, regions of interest, calibrations, and ImageJ settings. Interpretation of the stored measurements is facilitated by atlas mapping and ontology-based markup. The system can be used as an experimental workflow management tool allowing for description and reporting of the performed experiments. LabIS can be also used as a measurements repository that can be transparently accessed by computational environments, such as Matlab. Finally, the system can be used as a data sharing tool.

Patient and Image Data Management in Positron Emission Tomography-Computed Tomography for Radiation Therapy and Therapy Response Assessment

This article provides an overview of the primary considerations of positron emission tomography-computed tomographic (PET-CT) workflows specifically related to patient and image data management in radiation therapy (RT) planning and therapy response assessment. PET-CT has become increasingly integral to the RT planning and therapy response assessment. There are numerous workflow challenges related to integrating PET-CT in the framework of RT planning and therapy assessment. For PET-CT scan used for RT planning, accurate patient positioning and scan registration with the simulation is critical. For therapy assessment PET-CT scans, consistency in patient preparation, scanning and image reconstruction parameters, and image analysis are critical.

웹서비스 기반의 Grid-PACS 상호운용성 프레임워크

최근 증가하는 협업 연구는 원격 의료 데이터 공유 및 외부 기관의 데이터 접근을 요구하고 있다. 본 논문에서는 융통성 있고 효율적인 의료 데이터 관리를 위해 웹서비스를 이용하여 그리드와 PACS 간의 상호운용성 프레임워크를 제안하고 구현하였다. DICOM 표준은 PACS와 이미지 데이터베이스 사이에 의료 이미지 데이터의 교환과 전송을 정의한다. 그러나 병원들 간 의료 데이터 교환은 신뢰할 수 있는 기관들 사이에서만 제공된다. 더군다나 DICOM은 의료 데이터 관리 기능을 제공하지 않고 그리드 미들웨어는 DICOM 데이터에 접근 가능한 표준 툴킷을 제공하고 있지 않고 있다. 본 논문에서는 이러한 문제를 해결하기 위하여 PACS 간의 연동과 의료 데이터 관리를 가능하게 하는 웹 서비스기반의 그리드 서비스 중계자(Web Services-based Grid Service Mediator, WGSM)를 개발하였다. WGSM은 압축 중계자, GridFTP 중계자, RFT 중계자, MyProxy 중계자, MDS 중계자, RLS 중계자 등으로 구성된다. 제안한 웹서비스 기반의 프레임워크는 협업 환경에서 PACS 간 사용자 인증 및 안전한 데이터 접근을 제공한다. 특히, WGSM은 일반 사용자들이 그리드 미들웨어에 대한 어떠한 지식이 없어도 간단하고 효율적인 방법으로 원격 PACS를 접근할 수 있게 한다. Recently the increasing collaborative research requires the remote medical and clinical data sharing and access of external institutions. In this paper, an interoperability framework between Grid and PACS using Web services is proposed and implemented in order to provide flexible and efficient medical data management. The Digital Imaging and Communications in Medicine(DICOM) standard defines medical image data exchange and transfer between PACSs and image databases. However, medical data exchange between hospitals is limited within the trusted and static environments. Moreover, DICOM does not provide medical data management and the Grid middleware does not include standard toolkit to access DICOM data. To address this issue, a Web services-based Grid Service Mediator (WGSM) which provides PACS integration and medical image data management is developed. The WGSM consists of several service mediators such as compress mediator, GridFTP mediator, RFT mediator, MyProxy mediator, MDS mediator, and RLS mediator and others. The proposed Web services-based framework provides user authentication and secure data access between PACSs in collaborative environments. In particular, the WGSM allows ordinary users to access remote PACS data in a simple and efficient manner without any the knowledge about underlying Grid middleware.

MIDG-Emerging grid technologies for multi-site preclinical molecular imaging research communities

Molecular imaging is the visualization and identification of specific molecules in anatomy for insight into metabolic pathways, tissue consistency, and tracing of solute transport mechanisms. This paper presents the Molecular Imaging Data Grid (MIDG) which utilizes emerging grid technologies in preclinical molecular imaging to facilitate data sharing and discovery between preclinical molecular imaging facilities and their collaborating investigator institutions to expedite translational sciences research. Grid-enabled archiving, management, and distribution of animal-model imaging datasets help preclinical investigators to monitor, access and share their imaging data remotely, and promote preclinical imaging facilities to share published imaging datasets as resources for new investigators. The system architecture of the Molecular Imaging Data Grid is described in a four layer diagram. A data model for preclinical molecular imaging datasets is also presented based on imaging modalities currently used in a molecular imaging center. The MIDG system components and connectivity are presented. And finally, the workflow steps for grid-based archiving, management, and retrieval of preclincial molecular imaging data are described. Initial performance tests of the Molecular Imaging Data Grid system have been conducted at the USC IPILab using dedicated VMware servers. System connectivity, evaluated datasets, and preliminary results are presented. The results show the system's feasibility, limitations, direction of future research. Translational and interdisciplinary research in medicine is increasingly interested in cellular and molecular biology activity at the preclinical levels, utilizing molecular imaging methods on animal models. The task of integrated archiving, management, and distribution of these preclinical molecular imaging datasets at preclinical molecular imaging facilities is challenging due to disparate imaging systems and multiple off-site investigators. A Molecular Imaging Data Grid design, implementation, and initial evaluation is presented to demonstrate the secure and novel data grid solution for sharing preclinical molecular imaging data across the wide-area-network (WAN).

Automated gas bubble imaging at sea floor – a new method of in situ gas flux quantification

Abstract. Photo-optical systems are common in marine sciences and have been extensively used in coastal and deep-sea research. However, due to technical limitations in the past photo images had to be processed manually or semi-automatically. Recent advances in technology have rapidly improved image recording, storage and processing capabilities which are used in a new concept of automated in situ gas quantification by photo-optical detection. The design for an in situ high-speed image acquisition and automated data processing system is reported ("Bubblemeter"). New strategies have been followed with regards to back-light illumination, bubble extraction, automated image processing and data management. This paper presents the design of the novel method, its validation procedures and calibration experiments. The system will be positioned and recovered from the sea floor using a remotely operated vehicle (ROV). It is able to measure bubble flux rates up to 10 L/min with a maximum error of 33% for worst case conditions. The Bubblemeter has been successfully deployed at a water depth of 1023 m at the Makran accretionary prism offshore Pakistan during a research expedition with R/V Meteor in November 2007.

TH-A-BRA-03: TG-104: In-Room kV Imaging for IGRT

In-room kilovoltage (kV) x-ray imaging refers to radiographic imaging using kV x-ray sources in the radiation treatment room. It has been widely accepted for radiotherapy target localization and treatment intervention. Task Group 104 (TG 104) reports on the various in-room systems which are commercially available using one or more kV imaging modalities. Several distinct systems including rail-track-mounted systems ceiling/floor-mounted systems and gantry-mounted systems have been made commercially available each with unique capabilities limitations and levels of operational complexity. A hybrid system is also introduced which combines two different mounting systems. In this presentation we will provide 1) an overview of the principles and challenges for treatment verification; 2) an overview of system description image guidance applications and performance for in-room systems based on both projection and tomographic imaging; 3) brief description of future development. The TG-104 report also provides an overview of the issues related to effective implementation of these systems for routine clinical procedures. General guidance is made for appropriate acceptance testing and quality assurance of these systems for safety image quality and data management. Learning Objectives: 1. Understand the current existing kV x-ray systems used in the radiation treatment room including system configurations specifications operation principles and functionality. 2. Understand the principles and challenges for treatment verification. 3. Understand current clinical application methods about how these systems could be used to improve treatment accuracy and their lementationo. 4. Understand issues related to effective implementation of IGRT in the routine clinical procedures as well as quality assurance.

Abstract 99: The caBIG® life sciences distribution: Integrative tools to support translational research

Abstract The cancer Biomedical Informatics Grid® (caBIG®) is a collaborative network designed to accelerate the translation of discoveries from research to clinical care. This extensible informatics platform integrates diverse data types and supports interoperable software tools in the areas of clinical sciences, biospecimen management, imaging, and basic research. The Life Sciences Distribution (LSD) product bundle brings together a range of tools that support translational research, all connected via grid network technology. Tools included in the bundle support management and annotation of microarray data (caArray), biospecimens (caTissue Suite), imaging data (NBIA), clinical data (CTODS) and genome-wide association studies (caGWAS). LSD also includes integrative tools that allow scientist to search data across different data repositories connected to the grid, and analyze and integrate these data across different data types. geWorkbench supports integrative analysis and visualization of expression data, sequences, pathways and protein structures. cancer Bench-to-Bedside (caB2B) allows end-users to search biospecimens, images and array data across the grid and makes it possible to execute queries such as: “Are there any gene expression microarray data available from patients with Stage III lung cancer and are there corresponding in vivo images available for the affected patients?” Such a query would potentially span information federated across several instances of caArray, caTissue, and NBIA around the world. caIntegrator2 allows researchers to set up study specific custom web portals that bring together heterogeneous clinical, microarray and in vivo imaging data. This tool provides a graphical user interface to allow a study author to “point” to data of interest in systems on the grid and to then bring that data (or pointers to it, in the case of images) into the data warehouse. Once this information is in the caIntegrator2 environment, end user scientists can then run advanced queries, perform correlative outcomes analysis using Kaplan-Meier survival plots, and access analysis and visualization tools on and off the grid. All tools in the LSD are open source and community members are encouraged to participate and contribute. More information on the LSD suite of products, including installation packages, user and installation guides, and links to exemplar installations can be found at https://cabig.nci.nih.gov/adopt/LSD/ Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 99.

Complex cystic lesions of the breast on ultrasonography: Feature analysis and BI-RADS assessment

Purpose To analyze the features of breast complex cystic lesions at ultrasonography (US) and to determine appropriate Breast Imaging Reporting and Data System (BI-RADS) categories and management recommendations for these lesions based on US findings with pathologic correlation. Materials and methods From July 2001 to June 2007, 152 consecutive pathologically proven complex cystic lesions on US were retrospectively reviewed. All lesions at US were evaluated for size, lesion characteristics, margins, and presence of abnormal axillary nodes. US features of lesions were classified into four types, and positive predictive values (PPVs) were calculated for each type. Clinical, imaging, and histopathological findings were reviewed. Results Of the 152 lesions based on US appearance, 36 (24%) were classified as type I, 49 (32%) as type II, 28 (18%) as type III, and 39 (26%) as type IV. The PPVs for malignancy in each type were 14% for type I, 16% for type II, 14% for type III, and 41% for type IV. There was a significantly higher frequency of malignancy among lesions of type IV compared with the other three types (16/39 = 41% vs 5/36 = 14%, p = 0.0089; 16/39 = 41% vs 8/49 = 16%, p = 0.0098; and 16/39 = 41% vs 4/28 = 14%, p = 0.018 [Chi-squared test]). Lesions with maximum diameter equal to or larger than 20 mm, not circumscribed margins, or a mammographic finding of suspected malignancy had a high probability of malignancy ( p < 0.05 for each). Conclusion US is useful in evaluating the complex cystic lesions and in clarifying the indication for biopsy of these lesions. The four types of US classifications used in our study establish accepted benchmarks for these breast abnormalities when stratified according to BI-RADS categories.

Information management for high content live cell imaging.

BackgroundHigh content live cell imaging experiments are able to track the cellular localisation of labelled proteins in multiple live cells over a time course. Experiments using high content live cell imaging will generate multiple large datasets that are often stored in an ad-hoc manner. This hinders identification of previously gathered data that may be relevant to current analyses. Whilst solutions exist for managing image data, they are primarily concerned with storage and retrieval of the images themselves and not the data derived from the images. There is therefore a requirement for an information management solution that facilitates the indexing of experimental metadata and results of high content live cell imaging experiments.ResultsWe have designed and implemented a data model and information management solution for the data gathered through high content live cell imaging experiments. Many of the experiments to be stored measure the translocation of fluorescently labelled proteins from cytoplasm to nucleus in individual cells. The functionality of this database has been enhanced by the addition of an algorithm that automatically annotates results of these experiments with the timings of translocations and periods of any oscillatory translocations as they are uploaded to the repository. Testing has shown the algorithm to perform well with a variety of previously unseen data.ConclusionOur repository is a fully functional example of how high throughput imaging data may be effectively indexed and managed to address the requirements of end users. By implementing the automated analysis of experimental results, we have provided a clear impetus for individuals to ensure that their data forms part of that which is stored in the repository. Although focused on imaging, the solution provided is sufficiently generic to be applied to other functional proteomics and genomics experiments. The software is available from:

Integration of computer-aided diagnosis/detection (CAD) results in a PACS environment using CAD–PACS toolkit and DICOM SR

Picture Archiving and Communication System (PACS) is a mature technology in health care delivery for daily clinical imaging service and data management. Computer-aided detection and diagnosis (CAD) utilizes computer methods to obtain quantitative measurements from medical images and clinical information to assist clinicians to assess a patient's clinical state more objectively. CAD needs image input and related information from PACS to improve its accuracy; and PACS benefits from CAD results online and available at the PACS workstation as a second reader to assist physicians in the decision making process. Currently, these two technologies remain as two separate independent systems with only minimal system integration. This paper describes a universal method to integrate CAD results with PACS in its daily clinical environment. The method is based on Health Level 7 (HL7) and Digital imaging and communications in medicine (DICOM) standards, and Integrating the Healthcare Enterprise (IHE) workflow profiles. In addition, the integration method is Health Insurance Portability and Accountability Act (HIPAA) compliant. The paper presents (1) the clinical value and advantages of integrating CAD results in a PACS environment, (2) DICOM Structured Reporting formats and some important IHE workflow profiles utilized in the system integration, (3) the methodology using the CAD-PACS integration toolkit, and (4) clinical examples with step-by-step workflows of this integration.

4-D Imaging in Cerebrovascular Disorders by Using 320-Slice CT: Feasibility and Preliminary Clinical Experience

The authors report study protocols and initial clinical experience in assessing patients with acute and chronic cerebrovascular disorders using the recently introduced technique of volume computed tomography (VCT). Thirteen patients with presumptive cerebrovascular insufficiency underwent VCT using a 320-slice scanner (detector width, 160 mm), including time-resolved whole-brain perfusion and cerebral angiography (four-dimensional computed tomographic angiography [CTA] and computed tomographic perfusion [CTP]). Unenhanced cranial CT (cCT) and helical cervicocranial CT (three-dimensional CTA) were added according to clinical requirements. Study protocols are presented, and image quality, data management, and radiation exposure issues are discussed. In 12 of 13 patients, the procedure was performed successfully on admission; in the other patient, the study was aborted for clinical reasons and repeated. Total scan time amounted to about 5 minutes, and data reconstruction times were up to 10 minutes. About 9000 primary images were generated, partially in the enhanced Digital Imaging and Communications in Medicine format, thus requiring new data postprocessing and management strategies. Image artifacts restricted the use of single-rotation cCT and incremental VCT (three-dimensional CTA). Overall exposure figures (computed tomographic dose index and dose-length product) were increased by 65% on average when three-dimensional CTA was added to volume cCT and four-dimensional CTA and CTP (5.0 mSv and 2178 mGy . cm, respectively). Preliminary clinical experience indicates that whole-brain four-dimensional CTA and CTP is a robust technique that provides relevant clinical information with respect to whole-brain perfusion as well as cerebral hemodynamics. The exposure benefit of deriving time-resolved perfusion and vessel images from one source data set is compromised when adding three-dimensional CTA to the protocol. Other acquisition techniques specific to VCT, such as single-rotation cCT and incremental three-dimensional CTA, suffer from restrictions in terms of image quality at present.

Evading the annotation bottleneck: using sequence similarity to search non-sequence gene data.

BackgroundNon-sequence gene data (images, literature, etc.) can be found in many different public databases. Access to these data is mostly by text based methods using gene names; however, gene annotation is neither complete, nor fully systematic between organisms, and is also not generally stable over time. This provides some challenges for text based access, especially for cross-species searches. We propose a method for non-sequence data retrieval based on sequence similarity, which removes dependence on annotation and text searches. This work was motivated by the need to provide better access to large numbers of in situ images, and the observation that such image data were usually associated with a specific gene sequence. Sequence similarity searches are found in existing gene oriented databases, but mostly give indirect access to non-sequence data via navigational links.ResultsThree applications were built to explore the proposed method: accessing image data, literature and gene names. Searches are initiated with the sequence of the user's gene of interest, which is searched against a database of sequences associated with the target data. The matching (non-sequence) target data are returned directly to the user's browser, organised by sequence similarity. The method worked well for the intended application in image data management. Comparison with text based searches of the image data set showed the accuracy of the method. Applied to literature searches it facilitated retrieval of mostly high relevance references. Applied to gene name data it provided a useful analysis of name variation of related genes within and between species.ConclusionThis method makes a powerful and useful addition to existing methods for searching gene data based on text retrieval or curated gene lists. In particular the method facilitates cross-species comparisons, and enables the handling of novel or otherwise un-annotated genes. Applications using the method are quick and easy to build, and the data require little maintenance. This approach largely circumvents the need for annotation, which can be a major obstacle to the development of genomic scale data resources.

Bioimage informatics: a new area of engineering biology

In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ‘bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.Contact: pengh@janelia.hhmi.orgSupplementary information: Supplementary data are available at Bioinformatics online.

Image processing, geometric modeling and data management for development of a virtual bone surgery system

This paper describes image processing, geometric modeling and data management techniques for the development of a virtual bone surgery system. Image segmentation is used to divide CT scan data into different segments representing various regions of the bone. A region-growing algorithm is used to extract cortical bone and trabecular bone structures systematically and efficiently. Volume modeling is then used to represent the bone geometry based on the CT scan data. Material removal simulation is achieved by continuously performing Boolean subtraction of the surgical tool model from the bone model. A quadtree-based adaptive subdivision technique is developed to handle the large set of data in order to achieve the real-time simulation and visualization required for virtual bone surgery. A Marching Cubes algorithm is used to generate polygonal faces from the volumetric data. Rendering of the generated polygons is performed with the publicly available VTK (Visualization Tool Kit) software. Implementation of the developed techniques consists of developing a virtual bone-drilling software program, which allows the user to manipulate a virtual drill to make holes with the use of a PHANToM™ device on a bone model derived from real CT scan data.

Image processing, geometric modeling and data management for development of a virtual bone surgery system

This paper describes image processing, geometric modeling and data management techniques for the development of a virtual bone surgery system. Image segmentation is used to divide CT scan data into different segments representing various regions of the bone. A region-growing algorithm is used to extract cortical bone and trabecular bone structures systematically and efficiently. Volume modeling is then used to represent the bone geometry based on the CT scan data. Material removal simulation is achieved by continuously performing Boolean subtraction of the surgical tool model from the bone model. A quadtree-based adaptive subdivision technique is developed to handle the large set of data in order to achieve the real-time simulation and visualization required for virtual bone surgery. A Marching Cubes algorithm is used to generate polygonal faces from the volumetric data. Rendering of the generated polygons is performed with the publicly available VTK (Visualization Tool Kit) software. Implementation of the developed techniques consists of developing a virtual bone-drilling software program, which allows the user to manipulate a virtual drill to make holes with the use of a PHANToM™ device on a bone model derived from real CT scan data.

Open Tools for Storage and Management of Quantitative Image Data

The explosion in quantitative imaging has driven the need to develop tools for storing, managing, analyzing, and viewing large sets of data. In this chapter, we discuss tools we have built for storing large data sets for the lifetime of a typical research project. As part of the Open Microscopy Environment (OME) Consortium, we have built a series of open-source tools that support the manipulation and visualization of large sets of complex image data. Images from a number of proprietary file formats can be imported and then accessed from a single server running in a laboratory or imaging facility. We discuss the capabilities of the OME Server, a Perl-based data management system that is designed for large-scale analysis of image data using a web browser-based user interface. In addition, we have recently released a lighter weight Java-based OME Remote Objects Server that supports remote applications for managing and viewing image data. Together these systems provide a suite of tools for large-scale quantitative imaging that is now commonly used throughout cell and developmental biology.

S212: Orbital Surgery for the Oral and Maxillofacial Surgeon: Anatomical and Imaging Considerations

The orbit is one of the most fascinating areas of anatomical enquiry because it exhibits unparalleled features of architectural organization to accommodate the complex demands of vision. Orbital involvement in trauma, infections as well as neoplastic processes spreading from the maxillofacial region, and during the course of certain orthognathic surgical techniques requires a thorough understanding of orbital anatomy by the Oral and Maxillofacial surgeon. Although the core principles of orbital surgery have not radically altered during the past decade, improvement in our knowledge of orbital anatomy has improved our understanding of orbital pathophysiology and has brought refinement to orbital surgery. Multislice CT and High resolution MR display orbital anatomy with considerable clarity and provide most of the information needed. However, the nature of pathological process and the compact anatomy of the orbit sometimes necessitate the use of more than one modality with creative juxtaposition of information through image data management to permit a lucid interpretation of the characteristics of orbital pathology. In this presentation, we will provide a comprehensive survey of orbital anatomy with particular emphasis on those aspects of particular relevance in orbital surgery. The application of various imaging modalities to display normal orbital anatomy and delineate specific changes induced by various pathological processes will be demonstrated and discussed. Case studies of common as well as uncommon orbital pathology from our experience illustrating specific problems and challenges in orbital surgery will be presented.