DocumentCode
575351
Title
Optimization of parameter for extracting brain regions using deformable contour models
Author
Odagiri, Seiya ; Sato, Kazuhito ; Madokoro, Hirokazu
Author_Institution
Grad. Sch., Fac. of Syst. Sci. & Technol., Akita Prefectural Univ., Yurihonjo, Japan
fYear
2012
fDate
20-23 Aug. 2012
Firstpage
608
Lastpage
613
Abstract
This paper presents a method that considers sharing of parameters of Level Set Methods and optimizes method using Genetic Algorithm. We optimized parameters of LSMs that is deformable model using GA of evolutional learning. However, the proposal method needs Ground Truth for each clinical image. Therefore, application with clinical images without GT was challenging task. In this paper, we focus on shaering of parameters and try application of the proposal method for clinical images without GT for an individualization trade-off problem. Moreover, the extraction accuracy performed the optimal value search for iterations of updating to the low case using Active Appearance Models after sharing.
Keywords
biomedical MRI; computational geometry; feature extraction; genetic algorithms; learning (artificial intelligence); medical image processing; parameter estimation; active appearance models; brain region extraction; clinical images; deformable contour models; deformable model; evolutionary learning; genetic algorithm; ground truth; individualization trade off problem; level set methods; optimized LSM parameters; parameter optimization; parameter sharing; Accuracy; Atrophy; Deformable models; Genetic algorithms; Head; Optimization; Shape; Active Appearance Models; Genetic Algorithm; Level Set Methods;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE Annual Conference (SICE), 2012 Proceedings of
Conference_Location
Akita
ISSN
pending
Print_ISBN
978-1-4673-2259-1
Type
conf
Filename
6318510
Link To Document