Title
Spatially aware patch-based segmentation (SAPS): an alternative patch-based segmentation framework
Abstract
Patch-based segmentation has been shown to be successful in a range of label propagation applications. Performing patch-based segmentation can be seen as a k-nearest neighbour problem as the labelling of each voxel is determined according to the distances to its most similar patches. However, the reliance on a good affine registration given the use of limited search windows is a potential weakness. This paper presents a novel alternative framework which combines the use of kNN search structures such as ball trees and a spatially weighted label fusion scheme to search patches in large regional areas to overcome the problem of limited search windows. Our proposed framework (SAPS) provides an improvement in the Dice metric of the results compared to that of existing patch-based segmentation frameworks.
Year
DOI
Venue
2012
10.1007/978-3-642-36620-8_10
MCV
Keywords
Field
DocType
spatially weighted label fusion,k-nearest neighbour problem,proposed framework,ball tree,label propagation application,patch-based segmentation framework,novel alternative framework,knn search structure,spatially aware patch-based segmentation,alternative patch-based segmentation framework,patch-based segmentation,limited search windows,spatial
Voxel,Nearest neighbour search,Affine transformation,Scale-space segmentation,Pattern recognition,Label propagation,Segmentation,Artificial intelligence,Fusion scheme,Dice,Geography
Conference
Citations 
PageRank 
References 
8
0.63
6
Authors
4
Name
Order
Citations
PageRank
Zehan Wang136911.51
Robin Wolz266134.42
Tong Tong380.63
Daniel Rueckert49338637.58