Multimodal evaluation for medical image segmentation

Details

Serval ID
serval:BIB_427D132FE642
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Multimodal evaluation for medical image segmentation
Title of the conference
12th International Conference on Computer Analysis of Images and Patterns
Author(s)
Cardenes R., Bach M., Chi Y., Marras I., de Luis R., Anderson M., Cashman P., Bultelle M.
Address
Vienna, Austria, August 27-29, 2007
ISBN
0302-9743
Publication state
Published
Issued date
2007
Peer-reviewed
Oui
Volume
4673
Series
Lecture Notes in Computer Science
Pages
229-236
Language
english
Notes
Publication type : Proceedings Paper
Abstract
This paper is a joint effort between five institutionsthat introduces several novel similarity measures andcombines them to carry out a multimodal segmentationevaluation. The new similarity measures proposed arebased on the location and the intensity values of themisclassified voxels as well as on the connectivity andthe boundaries of the segmented data. We showexperimentally that the combination of these measuresimprove the quality of the evaluation. The study that weshow here has been carried out using four differentsegmentation methods from four different labs applied toa MRI simulated dataset of the brain. We claim that ournew measures improve the robustness of the evaluation andprovides better understanding about the differencebetween segmentation methods.
Keywords
Multimodal evaluation, segmentation, similarity measures, brain tissue segmentation,
Create date
29/11/2011 16:40
Last modification date
20/08/2019 13:45
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