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Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality.
Stud Health Technol Inform. 2004; 98:347-52.SH

Abstract

Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information promises to expand surgeons' abilities to interpret images and plan treatment.

Authors+Show Affiliations

Department of Surgery, The University of Chicago Hospitals Room A-105, MC 6051, 5841 S. Maryland Avenue Chicago, Illinois 60637-1470, USA. jcs@uchicago.eduNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

15544303

Citation

Silverstein, Jonathan C., et al. "Enhancing Radiological Volumes With Symbolic Anatomy Using Image Fusion and Collaborative Virtual Reality." Studies in Health Technology and Informatics, vol. 98, 2004, pp. 347-52.
Silverstein JC, Dech F, Kouchoukos PL. Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality. Stud Health Technol Inform. 2004;98:347-52.
Silverstein, J. C., Dech, F., & Kouchoukos, P. L. (2004). Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality. Studies in Health Technology and Informatics, 98, 347-52.
Silverstein JC, Dech F, Kouchoukos PL. Enhancing Radiological Volumes With Symbolic Anatomy Using Image Fusion and Collaborative Virtual Reality. Stud Health Technol Inform. 2004;98:347-52. PubMed PMID: 15544303.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality. AU - Silverstein,Jonathan C, AU - Dech,Fred, AU - Kouchoukos,Philip L, PY - 2004/11/17/pubmed PY - 2004/12/31/medline PY - 2004/11/17/entrez SP - 347 EP - 52 JF - Studies in health technology and informatics JO - Stud Health Technol Inform VL - 98 N2 - Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information promises to expand surgeons' abilities to interpret images and plan treatment. SN - 0926-9630 UR - https://www.unboundmedicine.com/medline/citation/15544303/Enhancing_radiological_volumes_with_symbolic_anatomy_using_image_fusion_and_collaborative_virtual_reality_ L2 - http://ebooks.iospress.nl/Extern/EnterMedLine.aspx?ISSN=0926-9630&Volume=98&SPage=347 DB - PRIME DP - Unbound Medicine ER -