The “Demons Algorithm” in increasingly used for non-rigid registrationof 3D medical images. However, if it is fast and usually accurate, the algorithm is based onin tuitive ideas about image registration and it is difficult to predict when it will fail and why. We show in this paper that this algorithm can be considered as ana pproximationo f a second order gradient descent on the sum of square of intensity differences criterion. We also reformulate Gaussian and physical model regularizations as minimization problems. Experimental results on synthetic and 3D Ultrasound images show that this formalization helps identifying the weak points of the algorithm and offers new research openings.
CITATION STYLE
Pennec, X., Cachier, P., & Ayache, N. (1999). Understanding the “demon’s algorithm”: 3D non-rigid registration by gradient descent. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1679, pp. 597–606). Springer Verlag. https://doi.org/10.1007/10704282_64
Mendeley helps you to discover research relevant for your work.