id: 05979053
dt: a
an: 05979053
au: Gooya, Ali; Pohl, Kilian M.; Bilello, Michel; Biros, George; Davatzikos,
    Christos
ti: Joint segmentation and deformable registration of brain scans guided by a
    tumor growth model.
so: Fichtinger, Gabor (ed.) et al., Medical image computing and
    computer-assisted intervention ‒ MICCAI 2011. 14th international
    conference, Toronto, Canada, September 18‒22, 2011. Proceedings, Part
    II. Berlin: Springer (ISBN 978-3-642-23628-0/pbk). Lecture Notes in
    Computer Science 6892, 532-540 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: joint segmentation-registration; EM; diffusion-reaction model
ci: 
li: doi:10.1007/978-3-642-23629-7_65
ab: Summary: This paper presents an approach for joint segmentation and
    deformable registration of brain scans of glioma patients to a normal
    atlas. The proposed method is based on the Expectation Maximization
    (EM) algorithm that incorporates a glioma growth model for atlas
    seeding, a process which modifies the normal atlas into one with a
    tumor and edema. The modified atlas is registered into the patient
    space and utilized for the posterior probability estimation of various
    tissue labels. EM iteratively refines the estimates of the registration
    parameters, the posterior probabilities of tissue labels and the tumor
    growth model parameters. We have applied this approach to 10 glioma
    scans acquired with four Magnetic Resonance (MR) modalities (T1, T1-CE,
    T2 and FLAIR ) and validated the result by comparing them to manual
    segmentations by clinical experts. The resulting segmentations look
    promising and quantitatively match well with the expert provided ground
    truth.
rv: