Case study: medical web service for the automatic 3D documentation for neuroradiological diagnosis

Authors:
S. Iserhardt-Bauer;P. Hastreiter;T. Ertl;K. Eberhardt;B. Tomandl
Affiliations:
Visualization and Interactive Systems Group, University of Stuttgart, Germany;Neurocenter, University of Erlangen-Nuremberg, Germany;Visualization and Interactive Systems Group, University of Stuttgart, Germany;Division of Neuroradiology, University of Erlangen-Nuremberg, Germany;Division of Neuroradiology, University of Erlangen-Nuremberg, Germany
Venue:
Proceedings of the conference on Visualization '01
Year:
2001

Citing 4
Cited 1

Image Analysis Using Mathematical Morphology

IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-automatic generation of transfer functions for direct volume rendering

VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Combining local and remote visualization techniques for interactive volume rendering in medical applications

Proceedings of the conference on Visualization '00
Fast Analysis of Intracranial Aneurysms Based on Interactive Direct Volume Rendering and CTA

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention

Story telling for presentation in volume visualization

EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization

Quantified Score

Hi-index	0.00

Visualization

Abstract

This case study presents a medical web service for the automatic analysis of CTA (Computer Tomography Angiography) datasets. It aims at the detection and evaluation of intracranial aneurysms which are malformations of cerebral blood vessels. To obtain a standardized 3D visualization digital videos are automatically generated. The time-consuming video production caused by the manual delineation of structures, software based volume rendering, and the interactive definition of an optimized camera path is considerably improved with a fully automatic strategy. Therefore, a previously suggested approach [11] is applied which uses an optimized transfer function as a template and automatically adapts it to an individual dataset. Furthermore, we introduce hardware-accelerated morphologic filtering in order to detect the location of mid-size and giant aneurysms. The actual generation of the video is finally integrated into a hardware accelerated off-screen rendering process based on 3D texture mapping ensuring fast visualization of high quality. Overall, clinical routine can be considerably assisted by providing a web based service combining automatic detection and standardized visualization.