TY - GEN
T1 - Segmentation of neurons based on one-class classification
AU - Hernandez-Herrera, Paul
AU - Papadakis, Manos
AU - Kakadiaris, Ioannis A.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/7/29
Y1 - 2014/7/29
N2 - In this paper, we propose a novel one-class classification method to segment neurons. First, a new criterion to select a training set consisting of background voxels is proposed. Then, a discriminant function is learned from the training set that allows determining how similar an unlabeled voxel is to the voxels in the background class. Finally, foreground voxels are assigned as those unlabeled voxels that are not classified as background. Our method was qualitatively and quantitatively evaluated on several dataset to demonstrate its ability to accurately and robustly segment neurons.
AB - In this paper, we propose a novel one-class classification method to segment neurons. First, a new criterion to select a training set consisting of background voxels is proposed. Then, a discriminant function is learned from the training set that allows determining how similar an unlabeled voxel is to the voxels in the background class. Finally, foreground voxels are assigned as those unlabeled voxels that are not classified as background. Our method was qualitatively and quantitatively evaluated on several dataset to demonstrate its ability to accurately and robustly segment neurons.
UR - http://www.scopus.com/inward/record.url?scp=84927924692&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84927924692&partnerID=8YFLogxK
U2 - 10.1109/isbi.2014.6868119
DO - 10.1109/isbi.2014.6868119
M3 - Conference contribution
AN - SCOPUS:84927924692
T3 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
SP - 1316
EP - 1319
BT - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Y2 - 29 April 2014 through 2 May 2014
ER -