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Examples of image analysis

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Below is a list of examples of how Pixcavator has been used to analyze images in an enormous variety of fields.

Virtually all of the examples below solve real-life problems for our users.

Note that almost none of the analysis examples require prior image enhancement. While looking at the analyzed images, observe that the analysis settings are appended to the name of the original image (for example, cells_100_20.bmp is the image that displays the results of the analysis of cells.bmp with the settings: size = 100, contrast = 20). This way you can easily reproduce the results on your own. There are also screenshots that show the settings. For more see Pixcavator help.

Please feel free to use Pixcavator's screenshots in presentations, publications, reports, etc. Many users have done this previously and we appreciate that they give us the credit. For the legal details see Pixcavator's user's license and Terms and conditions.

See also this point-by-point comparison of Pixcavator and ImageJ.


1 Is Pixcavator for you?

Basophil  (a type of white blood cell)
Basophil (purple) captured along with the rest
Nuclei
Nuclei, captured
Drosophila nuclei
Drosophila nuclei, captured
Nuclei
Nuclei, captured
Comet DNA at different stages
Comet DNA, captured
Nerve cells
Nerve cells, captured
Parenchyma (plant cells)
Parenchyma cells, captured
Meat
Lean meat, captured
Fat, captured
The original image of bee brood
Analysis: areas of occupied cells are captured and measured
Eye atrophy
Atrophy captured and evaluated
Mouse retina cells
Total of 3811 cells
Transversal section of a cassava root (a tropical tuber)
Transversal section of a root, dark area captured
Particles of various shapes and sizes
Particles captured
Lung biopsies
Intensity of staining measured
Red blood cells - elliptocytosis
Red blood cells, captured
Coral lesion
Coral lesion, perimeter measured
Image of grass
Vegetation volume measured
Hose cross section
Hose cross section, thickness measured

There are several ways to approach this question.

First, you can determine if your images may be good candidates for analysis with Pixcavator by reading Images appropriate for analysis.

Second, you can consider these (overlapping) categories of examples classified according to the image analysis tasks:

  1. Counting
  2. Measuring
  3. Image statistics
  4. Calibration
  5. Locations
  6. Color analysis
  7. Customization
  8. 3D analysis

Third, see these categories of examples classified according to the field of application:

  1. Microscopy
  2. Material science
  3. Medicine
  4. Machine vision
  5. Maps
  6. Biology
  7. Physics
  8. Mobile

You can also browse the complete list of examples in the next section or scan the images on the right (if you find one of them interesting, click on the image and then go to the bottom of the page to "The following pages link to this file").

Consider also:


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2 Complete list of examples

Favorites are in bold.

  1. Analysis of sample images (synthetic images and standard images)
  2. Flow-through pore diameters (paper)
  3. Control of electron transport (paper)
  4. Inspecting semiconductor wafers (machine vision)
  5. Cell counting (measuring etc)
  6. Measuring staining in the liver
  7. Cell metal segregation and ultramicroscopy
  8. Blood vessels (not very successful)
  9. Evaluating ratio meat/fat
  10. Evaluating ratio meat/fat 2
  11. Character recognition (aka OCR)
  12. Image analysis for a hand-held diagnostic device (arrays)
  13. Mosaic making (fun)
  14. Optical illusions (fun)
  15. Microarray analysis (HTC)
  16. Drusen contours (ophthalmology)
  17. Counting sealed brood in bee frames
  18. Measuring the volume of prostate cancer tumor (slice by slice)
  19. Measuring holes in a gasket (calibration)
  20. Ophthalmology diagnosis
  21. Detecting a small breast cancer tumor
  22. MRI (under construction)
  23. Solar flares (astronomy)
  24. Cellular structures (cell counting)
  25. Iceberg is born (satellite imaging)
  26. Metallurgical image analysis
  27. Crystallites (counting particles)
  28. Measurement statistics of fibers
  29. Thermal imaging (night vision)
  30. Wall of a blood vessel (measuring thickness)
  31. Medical testing device
  32. Fluorescent images for tumor demarcation
  33. Measuring chromosomes (not quite successful)
  34. Measuring electronic components
  35. Testing vaccine spray/aerosol droplets
  36. High throughput screening (paper)
  37. Counting fixed and live red blood cells
  38. Melanoma (ABCD analysis)
  39. Counting and measuring lots (real estate)
  40. Corneas of rats (paper)
  41. Evaluation of quality of seeds (paper)
  42. Micropallet arrays
  43. Nanotechnology (counting particles)
  44. Corneal endothelial cells of the human eye (hexagonal cells)
  45. Particle cleaning process
  46. Measuring a needle
  47. Measuring micromechanical parameters of fiberglass
  48. Counting cones in a mouse's retina
  49. Measuring length of fish in petri dish
  50. Transversal section of a root (measuring)
  51. Circumference of a coral lesion
  52. Counting chocolates in a box
  53. Defective spring
  54. Microscopy of surfactants
  55. Membranes containing proteins
  56. Particle statistics with calibration
  57. Satellite image of Sicily
  58. Counting stained DNA
  59. Immunohistochemistry on lung biopsies
  60. Cluster size effects in molecular beam scattering (paper)
  61. Measure vegetation coverage
  62. Hose measurements
  63. Measuring seedling area
  64. Bubble sheets
  65. Quality of soldering
  66. Phase transition of petroleum
  67. Mobility and distribution of chlorophyll proteins
  68. The behaviour of double oxide film defects in liquid Al alloys
  69. Sub-pixel accuracy for distance measurement
  70. Analysis of SEM images of alloy
  71. Breast carcinoma detection
  72. Immunohistochemical detection in a study of hypertension
  73. Antimicrobial study of a medicinal plant
  74. Fish counting
  75. Colorant dispersion
  76. Seurat's painting
  77. Fungi kill spiders
  78. Properties of stones for railway foundation
  79. Geometry of corneocytes imaged with fluorescent microscopy
  80. Anticancer property of gallic acid
  81. Bioelectrical signals control stem cell progeny


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