An algorithmic overview of surface registration techniques for medical imaging

This paper presents a literature survey of automatic 3D surface registratio n techniques emphasizing the mathematical and algorithmic underpinnings of the subject. The relevance of surface registration to medical imaging is th at there is much useful anatomical information in the form of collected sur face points which originate from complimentary modalities and which must be reconciled. Surface registration can be roughly partitioned into three iss ues: choice of transformation, elaboration of surface representation and si milarity criterion, and matching and global optimization. The first issue c oncerns the assumptions made about the nature of relationships between the two modalities, e.g. whether a rigid-body assumption applies, and if nor, w hat type and how general a relation optimally maps one modality onto the ot her. The second issue determines what type of information we extract from t he 3D surfaces, which typically characterizes their local or global shape, and how we organize this information into a representation of the surface w hich will lead to improved efficiency and robustness in the last stage. The last issue pertains to how we exploit this information to estimate the tra nsformation which best aligns local primitives in a globally consistent man ner or which maximizes a measure of the similarity in global shape of two s urfaces. Within this framework, this paper discusses in detail each surface registration issue and reviews the state-of-the-art among existing techniq ues. (C) 2000 Elsevier Science BN. All rights reserved.