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Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.
Comparison and evaluation of segmentation techniques for subcortical structures in brain MRI.
In: (International Conference on Medical Image Computing and Computer-Assisted Intervention). Berlin [u.a.]: Springer, 2008. 409-416 (Lect. Notes Comput. Sc. ; 5241 LNCS)
The automation of segmentation of medical images is an active research area. However, there has been criticism of the standard of evaluation of methods. We have comprehensively evaluated four novel methods of automatically segmenting subcortical structures using volumetric, spatial overlap and distance-based measures. Two of the methods are atlas-based - classifier fusion and labelling (CFL) and expectation-maximisation segmentation using a dynamic brain atlas (EMS), and two model-based - profile active appearance models (PAM) and Bayesian appearance models (BAM). Each method was applied to the segmentation of 18 subcortical structures in 270 subjects from a diverse pool varying in age, disease, sex and image acquisition parameters. Our results showed that all four methods perform on par with recently published methods. CFL performed significantly better than the other three methods according to all three classes of metrics. © 2008 Springer-Verlag Berlin Heidelberg.
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Publikationstyp
Artikel: Konferenzbeitrag
ISSN (print) / ISBN
0302-9743
e-ISSN
1611-3349
Konferenztitel
International Conference on Medical Image Computing and Computer-Assisted Intervention
Zeitschrift
Lecture Notes in Computer Science
Quellenangaben
Band: 5241 LNCS,
Heft: PART 1,
Seiten: 409-416
Verlag
Springer
Verlagsort
Berlin [u.a.]
Nichtpatentliteratur
Publikationen
Institut(e)
Institute for Machine Learning in Biomed Imaging (IML)