Globally optimal deformable registration on a minimum spanning tree using dense displacement sampling.
Deformable image registration poses a highly non-convex optimisation problem. Conventionally, medical image registration techniques rely on continuous optimisation, which is prone to local minima. Recent advances in the mathematics and new programming methods enable these disadvantages to be overcom...
主要な著者: | Heinrich, M, Jenkinson, M, Sir Michael Brady, Schnabel, J |
---|---|
フォーマット: | Journal article |
言語: | English |
出版事項: |
2012
|
類似資料
-
TEXTURAL MUTUAL INFORMATION BASED ON CLUSTER TREES FOR MULTIMODAL DEFORMABLE REGISTRATION
著者:: Heinrich, M, 等
出版事項: (2012) -
MRF-based deformable registration and ventilation estimation of lung CT.
著者:: Heinrich, M, 等
出版事項: (2013) -
MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.
著者:: Heinrich, M, 等
出版事項: (2012) -
MIND: Modality independent neighbourhood descriptor for multi-modal deformable registration
著者:: Heinrich, M, 等
出版事項: (2012) -
Edge- and detail-preserving sparse image representations for deformable registration of chest MRI and CT volumes
著者:: Heinrich, M, 等
出版事項: (2013)