Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-23038-7_28
Title: Dynamic programming algorithms for efficiently computing cosegmentations between biological images
Authors: Xiao, H.
Zhang, M.
Mosig, A.
Leong, H.W. 
Issue Date: 2011
Source: Xiao, H.,Zhang, M.,Mosig, A.,Leong, H.W. (2011). Dynamic programming algorithms for efficiently computing cosegmentations between biological images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6833 LNBI : 339-350. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-23038-7_28
Abstract: Algorithms for comparing trees have recently been found relevant in the context of bioimage analysis. While previously proposed algorithms deal with problems that are computationally hard in general, we propose efficient algorithms for restricted versions that are able to handle significantly larger instances in practice. We propose two dynamic programming algorithms for the so-called tree assignment problem, which generalizes bipartite matchings to trees. We formulate restricted versions that are tractable by a dynamic programming algorithm. Furthermore, we describe a second dynamic programming algorithm that deals with the efficient computation of certain weights between so-called component trees that can be applied to obtain certain cosegmentations in bioimaging applications. Our investigations indicate that our algorithms are both efficient and effective, supported by evaluating the influence of the restrictions imposed by the dynamic programming formulation on a collection of image data. © 2011 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/41631
ISBN: 9783642230370
ISSN: 03029743
DOI: 10.1007/978-3-642-23038-7_28
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

1
checked on Dec 13, 2017

Page view(s)

56
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.