Abstract
Electron microscope tomography allows determination of the 3D structure of biological specimens, which is critical to understanding their function. Prior to the 3D reconstruction procedure, the images taken from the microscope have to be properly registered. Traditional alignment methods in this field are based on a phase residual function that is minimized by inefficient exhaustive search procedures. This work addresses this minimization problem from a global optimization perspective. A stochastic multimodal optimization algorithm has been applied and evaluated for the task of image registration in this field. This algorithm has turned out to be a promising technique alternative to the standard methodology. The alignments that have been found out show high levels of accuracy, while reducing the number of function evaluations by a significant factor with respect to the standard method.
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Redondo, J.L., Ortigosa, P.M., García, I., Fernández, J.J. (2004). Image Registration in Electron Microscopy. A Stochastic Optimization Approach. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3212. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30126-4_18
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DOI: https://doi.org/10.1007/978-3-540-30126-4_18
Publisher Name: Springer, Berlin, Heidelberg
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