Phase-Based User-Steered Image Segmentation

Authors:
Lauren O'Donnell;Carl-Fredrik Westin;W. Eric L. Grimson;Juan Ruiz-Alzola;Martha Elizabeth Shenton;Ron Kikinis
Affiliations:
-;-;-;-;-;-
Venue:
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Year:
2001

Citing 5
Cited 5

Intelligent scissors for image composition

SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
User-steered image segmentation paradigms: live wire and live lane

Graphical Models and Image Processing
Interactive segmentation with Intelligent Scissors

Graphical Models and Image Processing
Stability of Phase Information

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Integrated Visualization System for Surgical Planning and Guidance Using Image Fusion and Interventional Imaging

MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention

Review: A comparative study of deformable contour methods on medical image segmentation

Image and Vision Computing
Liver Segmentation from CT Scans: A Survey

WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Liver segmentation from computed tomography scans: A survey and a new algorithm

Artificial Intelligence in Medicine
Towards high resolution computational models of the cardiac conduction system: a pipeline for characterization of Purkinje-ventricular-junctions

FIMH'11 Proceedings of the 6th international conference on Functional imaging and modeling of the heart
Vision-based user interfaces for health applications: a survey

ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a user-steered segmentation algorithm based on the livewire paradigm. Livewire is an image-feature driven method that finds the optimal path between user-selected image locations, thus reducing the need to manually define the complete boundary. We introduce an image feature based on local phase, which describes local edge symmetry independent of absolute gray value. Because phase is amplitude invariant, the measurements are robust with respect to smooth variations, such as bias field inhomogeneities present in all MR images. In order to enable validation of our segmentation method, we have created a system that continuously records user interaction and automatically generates a database containing the number of user interactions, such as mouse events, and time stamps from various editing modules. We have conducted validation trials of the system and obtained expert opinions regarding its functionality.