인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Image registration is the process of transforming a source image so that its appearance approximates a target image. It can be used to study the similarities and differences between the images. There are a variety of different methods of transforming the image that differ principally by the type of allowable transformation. In computational anatomy, the most common approach is to find a diffeomorphism between the two images using a method known as Large Deformation Diffeomorphic Metric Mapping. However, it may be that a smaller set of allowable transformations yields additional information about the relationship between the images. Motivated by the fact that many biological transformations seem to be approximately conformal, in this study we consider conformal image registration. Conformal maps are locally equivalent to similarity transformations (they linearize to rotations, translations, and scalings). In order to avoid having to enforce conformality via a constraint at every point, we represent conformal maps by truncated Taylor series, that is, by complex polynomials. The coefficients of the Taylor series are determined by gradient descent on the discrepancy between the target and the transformed source images. Numerical examples illustrate the ability of the method to perform conformal registration and the convergence of the method during gradient descent and with respect to the number of terms in the truncated Taylor series.
본문·목차
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