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Digital Micrograph

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References

General References

  • Some references to the general principles of image processing are given in W&C. Although the present chapter is intended to be self-contained, you may find it interesting to see how large the topic really is.

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Specific References

  • The following publications highlight the use of DigitalMicrograph scripting in technique development for both data acquisition and evaluation.

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  • Mitchell DRG, Schaffer B (2005) Scripting-customised microscopy tools for Digital Micrograph™. Ultramicroscopy 103(4):319–332

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  • Kimoto K, Kothleitner G, Grogger W, Matsui Y, Hofer F (2005) Advantages of a monochromator for bandgap measurements using electron energy-loss spectroscopy. Micron 36(2):185–189

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  • Lozano-Perez S, Titchmarsh JM (2007) EFTEM assistant: A tool to understand the limitations of EFTEM. Ultramicroscopy 107(4):313–321

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  • Mitchell DRG (2008) DiffTools: Electron diffraction software tools for DigitalMicrograph™. Microsc Res Techniq 71(8):588–593

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  • Mitchell DRG (2008) Circular Hough transform diffraction analysis: A software tool for automated measurement of selected area electron diffraction patterns within Digital Micrograph™. Ultramicroscopy 108(4):367–374

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  • Shi J, Williams DR, Stewart PL (2008) A Script-Assisted Microscopy (SAM) package to improve data acquisition rates on FEI Tecnai electron microscopes equipped with Gatan CCD cameras. J Struct Biol 164(1):166–169

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  • Sader K, Schaffer B, Vaughan G, Brown BRA, Bleloch A (2010) Smart Acquisition EELS. Ultramicroscopy 110(8):998–1003

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  • Braidy N, Le Bouar Y, Lazar S, Ricolleau C (2012) Correcting scanning instabilities from images of periodic structures. Ultramicroscopy 118:67–76

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  • Kim KH, Zuo JM (2013) Symmetry quantification and mapping using convergent beam electron diffraction. Ultramicroscopy 124:71–76

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  • Lucas G, Burdet P, Cantoni M, Hébert C (2013) Multivariate statistical analysis as a tool for the segmentation of 3Dspectral data. Micron 52(53):49–56

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Correspondence to Bernhard Schaffer .

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Appendix

Appendix

6.1.1 People

Peter Roland Swann (see page 75) founded the company Gatan with his brother Rex in 1964.

6.1.2 Self-Assessment Questions

Q6.1:

How would you go about calibrating image intensity in camera images in electrons?

Q6.2:

Why are ‘unprocessed’ TEM camera images of type integer but ‘gain normalized’ images of type real?

Q6.3:

Most EFTEM data analysis requires multiple images to be spatially registered with each other. Which image filters are typically applied for automated registration techniques and why?

Q6.4:

What happens to the (back-transformed) image if in its Fourier transform all complex values get their phase set to zero (but the modulus remains)? What if all the modulus values get set to zero (but the phase stays)?

Q6.5:

What would be needed to be able to reconstruct a high-resolution image from a recorded diffraction pattern?

Q6.6:

How can you calibrate a high-resolution TEM image of Si in [110] zone axis using Fourier transformations and standard DigitalMicrograph tools?

Q6.7:

What is the highest spatial frequency a Fourier transform image contains?

Q6.8:

Cross-correlations compute the relative shift of two images using Fourier transformations. Why is it often beneficial to filter one of the images with a filter to reduce image contrast at the borders to a constant value? Why is it contra-productive to apply the filter to both images?

Q6.9.:

How can Fourier transforms of STEM images be used to diangose scan instabilities caused by instabilities in electric circuits or main power lines?

6.1.3 Text-Specific Questions

T6.1:

What is the main difference between graphic software and scientific image-processing software?

T6.2:

Explain all the information which might be lost if an image recorded at the microscope (with DigitalMicrograph and a camera) is stored as JPEG image.

T6.3:

What are the advantages of keeping image ‘display’ settings separate from image ‘data’?

T6.4:

Which different settings or tools can you use to visualize faint intensity differences in an image?

T6.5:

Explain how you can find the exposure time of an acquired micrograph in a stored DigitalMicrograph image.

T6.6:

Using Fig. 6.5, explain the main features of the Histogram tool and how it displays the mapping of values to colors in the image.

T6.7:

Assume you have the image of a perfect layer structure of exactly known layer thickness. Describe how you would use this information and existing tools in DigitalMicrograph to calibrate the image.

T6.8:

In the Fe jump-ratio image of Fig. 6.7, how would you extract and compare intensity values from the matrix across the smaller particle at the bottom of the image?

T6.9:

Give three examples for digital image filters and their application.

T6.10:

Give three examples for the use of Fourier transformations in microscopy-related image processing.

T6.11:

Explain why the “masking tools” in DigitalMicrograph are all point-symmetric.

T6.12:

Using Fig. 6.10 discuss the merits and pitfalls of presenting chemical information in color-mix RGB images.

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Schaffer, B. (2016). Digital Micrograph. In: Carter, C., Williams, D. (eds) Transmission Electron Microscopy. Springer, Cham. https://doi.org/10.1007/978-3-319-26651-0_6

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