Title
Efficient Multi-Atlas Registration using an Intermediate Template Image.
Abstract
Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.
Year
DOI
Venue
2017
10.1117/12.2256147
Proceedings of SPIE
Keywords
Field
DocType
deformable registration,multi-atlas label fusion,normal-pressure hydrocephalus
Computer vision,Computer science,Atlas (anatomy),Artificial intelligence,Brain shape,Magnetic resonance imaging,Computation,Normal pressure hydrocephalus
Conference
Volume
ISSN
Citations 
10137
0277-786X
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Blake Dewey1114.24
Aaron Carass238343.15
Ari Blitz3222.94
Jerry L. Prince44990488.42