Title
Statistical models of shape and spatial relation-application to hippocampus segmentation
Abstract
This paper presents a new method based both on Active Shape Model (ASM) and spatial distance model to segment brain structures. It combines two types of a priori knowledge: the structure shapes and the distances between them. This knowledge consists of shape and distance variability which are estimated during a training step. Then, the obtained models are used to guide simultaneously the evolution of initial structure shapes towards the target contours. The proposed models are applied to extract two hippocampal regions on coronal MRI of the brain. The obtained results are encouraging and show the performance of the proposed model.
Year
Venue
Keywords
2014
2014 International Conference on Computer Vision Theory and Applications (VISAPP)
Spatial Relations,Active Shape Model-ASM,Statistical a Priori Knowledge,MRI,Hippocampus
Field
DocType
Volume
Spatial relation,Computer vision,Active shape model,Point distribution model,Pattern recognition,Computer science,Segmentation,A priori and a posteriori,Image segmentation,Artificial intelligence,Statistical model
Conference
1
Citations 
PageRank 
References 
3
0.42
10
Authors
3
Name
Order
Citations
PageRank
Saïd Ettaïeb130.76
Kamel Hamrouni24121.73
Ruan Su355953.00