Image Analysis:

1. Image Analysis: • To utilize the information contained in the digital image data matrix for the purpose of quantification. • Particle Counts • Area measurements • Mean particle diameter • Length or Size distribution

2. Image Analysis: Underlying the principles of image analysis the operator must remember one essential fact.

3. Image Analysis: Underlying the principles of image analysis the operator must remember one essential fact. Computers are STUPID!

4. Image Analysis: Dog or Cat? Any four year old can tell the difference but even the most sophisticated computers would have difficulty making the distinction.

5. First step in image analysis is to define those features that you wish to analyze so that the computer can “know” what data in the image is significant. Thresholding • By grey level (pixel value) • By size (# of contiguous pixels within a certain value range) • By shape (round vs. elongate)

6. First step is create a binary image based on some cut off value for pixel intensity.

7. First step is create a binary image based on some cut off value for pixel intensity.

8. A binary image can also be adjusted to cover a subset of pixel values.

9. In cases where the objects of interest are quite distinct it can be relatively straightforward to distinguish them based on pixel value alone.

10. Sometimes simple thresholding is insufficient in defining those features one wishes to count, especially if the objects are touching each other making it difficult to distinguish one object from another.

11. Adjusting the contrast of the image may help the operator identify the objects of interest but the computer would still have difficulty identifying the objects.

12. The operator can use a marking tool to identify the objects of interest.

13. This image may be easily thresholded and made into a binary image in which the number of objects may be easily counted.

14. The creation of a binary image is only part of what needs to be done.

15. If Objects appear to be connected, even by a narrow bridge, then those two objects will be considered as a single object by the computer.

16. The connections can be dissolved by performing an “erosion” operation which will remove the peripheral pixels in a pixel by pixel manner.

17. This will reduce the area occupied by the objects but pixels can be added back by a process known as dilation so that objects are restored to nearly their original size without reconnection.

18. “Free” image analysis programs are available for downloading from the National Institutes of Health. They include many basic and some sophisticated capabilities. rsb.info.nih.gov/nih-image NIH Image (Mac) rsb.info.nih.gov/ijImageJ (PC)

19. Both NIH-Image and ImageJ have similar capabilities although the layouts are quite different.

20. First step is to crop the image so that only the area of interest is used.

21. Sometimes the image contrast must be inverted if the objects of interest are dark.

22. Next the image must be thresholded to create a binary image.

23. Using the “Analyze Particles” under the Analyze window all particles greater than 1 pixel and smaller than 999999 will be counted

24. Over 1300 particles are counted, most of which are only 1 pixel in size

25. If we raise the minimum size to 5 adjacent pixels and rerun the analysis

26. If we raise the minimum size to 5 adjacent pixels and rerun the analysis we get many fewer particles, only the 166 ones of interest

27. The output of the particle analysis can be exported as a file that can be uploaded into a spreadsheet program such as Excel and analyzed.

28. When placed in a spreadsheet the data can be analyzed in many different ways including size distribution, average size, percent area, etc.

29. Using this information one can refine the analysis looking for a way to distinguish single pores (72-92) vs. double pores (100-152)

30. An average area measurement can now be calculated for each single pore (85.5) and a ratio of single vs. double pores (5:2) can be determined.

31. Depending on how the image is to be used the operator can choose to collect the image in very high contrast. This will make the subsequent thresholding of the image much easier.

32. Side SE detector The choice of detector can also affect the image analysis In-lens SE detector

33. Side SE detector Especially after the image is thresholded In-lens SE detector

34. If one can calculate the pixel size, then accurate size and area measurements are possible.

35. Sophisticated image analysis can recognize patterns and detect and identify such complex patterns as those contained in diffraction patterns.

36. Measurements in Three Dimensions: What if we wanted to measure the precise height difference between two objects in an SEM image?

37. Measurements in Three Dimensions: First we must create a stereo pair image. Even though a conventional SEM image has a great depth of field it is still a two dimensional image.

38. Measurements in Three Dimensions: Steps in creating a stereo pair image (Bozzola & Russell p. 221-224) True 3-D imaging requires that the object be viewed from two different angles at the same time. A person with sight in only one eye can have excellent depth perception but cannot see something in 3-D.

39. Measurements in Three Dimensions: The first step is to create a stereo pair of images in which the specimen is eucentricaly tilted 8-12 degrees between pictures.

40. Measurements in Three Dimensions: To aid the observer in visualizing the stereo pair the “left hand” view can be colorized blue and the “right hand” view made red and superimposed on one another

41. Measurements in Three Dimensions: These Red/Blue images are known as anaglyph projections and can be quite dramatic

42. Quartz Crystals

43. Measurements in Three Dimensions:

44. Measurements in Three Dimensions: “MeX is a software product to compute and analyze digital elevation models (DEMs) from stereoscopic scanning electron microscope (SEM) images. MeX opens up the third dimension to the SEM users. In order to determine the topography of microstructures MeX is the ultimate tool when other means have come to an end. Using MeX you can measure profiles, roughness values, area parameters and even volumes of your specimen from SEM images.” www.alicona.com/

45. Measurements in Three Dimensions: First one defines an area for a digital elevation map (DEM). www.alicona.com/

46. Measurements in Three Dimensions: The creation of a DEM is computationally intensive and starts by building a wire-frame model which can then be surfaced rendered www.alicona.com/

47. Measurements in Three Dimensions: Once created the DEM can be viewed from many angles and color coded to emphasize features such as height. www.alicona.com/

48. Measurements in Three Dimensions: Compare the DEM with an anaglyph projection www.alicona.com/

49. Measurements in Three Dimensions: Profiles can produce accurate measurements for objects that vary in height www.alicona.com/

50. Measurements in Three Dimensions: One can even measure volumes using this software. Unlike ImageJ MeX is not free! www.alicona.com/