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In this practical you will learn about basic concepts of Fourier theory in digital image processing. You will gain a fundamental and intuitive understanding of the properties and applications of Fourier transforms, learn about convolution operations and their relation to kernels, the convolution theorem and its applications, and the effect of the transfer function of an imaging system on the final image.
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### [Practical 2 – 2D/3D reconstruction](https://edu.nl/tqpf8)
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### [Practical 2 – 2D/3D reconstruction](https://edu.nl/yb6n8)
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This practical will introduce you to the principles of single-particle reconstruction methods based on projection matching and Maximum Likelihood methods. You will learn about the pitfalls in assigning 3D orientations to particle images from cryo-EM experiments, the dangers of how a reference model can bias the outcome of a reconstruction if the noise level is high and you will explore some of the advantages of using probabilistic rather than deterministic models for orientation assignment.
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### [Practical 3 – Introduction to electron tomography](https://edu.nl/7kakp)
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### [Practical 3 – Introduction to electron tomography](https://edu.nl/9jbhb)
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In this practical you will apply your knowledge from the previous practicals to explore 3D reconstruction using tomographic imaging. You will learn about back-projection methods, the importance of sampling and the effect of missing information on image reconstruction.
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