Automatic segmentation of the aortic dissection membrane from 3d CTA images

Authors:
Tamás Kovács;Philippe Cattin;Hatem Alkadhi;Simon Wildermuth;Gábor Székely
Affiliations:
Computer Vision Group, ETH Zurich, Zurich, Switzerland;Computer Vision Group, ETH Zurich, Zurich, Switzerland;Institute of Diagnostic Radiology, University Hospital, Zürich;Institut fuer Radiologie, Kantonsspital St. Gallen, St. Gallen, Switzerland;Computer Vision Group, ETH Zurich, Zurich, Switzerland
Venue:
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
Year:
2006

Citing 9
Cited 2

Model-based detection of tubular structures in 3D images

Computer Vision and Image Understanding
Tissue Classification Based on 3D Local Intensity Structures for Volume Rendering

IEEE Transactions on Visualization and Computer Graphics
A Microsurgery Simulation System

MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Muliscale Vessel Enhancement Filtering

MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Multiscale detection of curvilinear structures in 2-D and 3-D image data

ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Vessel Tracking in Peripheral CTA Datasets -- An Overview

SCCG '01 Proceedings of the 17th Spring conference on Computer graphics
Bone enhancement filtering: application to sinus bone segmentation and simulation of pituitary surgery

MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Robust segmentation of tubular structures in 3-D medical images by parametric object detection and tracking

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Snakes, shapes, and gradient vector flow

IEEE Transactions on Image Processing

Automatic detection of supraaortic branches and model-based segmentation of the aortic arch from 3D CTA images

ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Towards patient specific catheter selection: computation of aortic geometry based on fused MRI data

FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart

Quantified Score

Hi-index	0.00

Visualization

Abstract

Acute aortic dissection is a life-threatening condition and must be diagnosed and treated promptly. For treatment planning the reliable identification of the true and false lumen is crucial. However, a fully automatic Computer Aided Diagnosis system capable to display the different lumens in an easily comprehensible and timely manner is still not available. In this paper we present a method that segments the entire aorta and then identifies the two lumens separated by the dissection membrane. The algorithm misdetected part of the membrane in only one of the 15 cases tested, where the aorta has not been significantly altered by the presence of aneurisms.