Sciweavers

Share
ISBI
2011
IEEE

Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm

8 years 2 months ago
Hippocampus segmentation using a stable maximum likelihood classifier ensemble algorithm
We develop a new algorithm to segment the hippocampus from MR images. Our method uses a new classifier ensemble algorithm to correct segmentation errors produced by a multi-atlas based segmentation method. Our classifier ensemble algorithm searches for the maximum likelihood solution via gradient ascent optimization. Compared to the additive regression based algorithm, LogitBoost, our algorithm avoids the numerical instability problem. Experiments on a hippocampus segmentation problem using the ADNI data show that our algorithm consistently converges faster and generalizes better than AdaBoost.
Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Mur
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ISBI
Authors Hongzhi Wang, Jung Wook Suh, Sandhitsu R. Das, Murat Altinay, John Pluta, Paul A. Yushkevich
Comments (0)
books