Basic concept of image

1. BASIC CONCEPT OF IMAGE
N A D A F I T R I E Y A T U L H I K M A H

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3. What is an image?
• 2-dimensional matrix of intensity (gray or color) value.

4. Digital Image?
• Remember: Digitization causes a digital image to become an approximation
of a real scene.

5. 2D and 3D images
• 2D image ➔ picture elements (pixels)
• 3D image ➔ volume elements (voxels)

6. Image Types - Color
Common image formats include:
• 1 values per point/pixel (B&W or Grayscale)
• 3 values per point/pixel (Red, Green, and Blue)
• 4 values per point/pixel (Red, Green, Blue, + “Alpha” or Opacity)

7. Spatial Resolution (1)
• The spatial resolution of an image is determined by how fine/coarse sampling
was carried out.
• Spatial resolution: smallest discernable image detail
• Vision specialists talk about image resolution
• Graphic designers talk about dots per inch (DPI)

8. Spatial Resolution (2)
Stretched Images:

9. Intensity Level Resolution (1)
• Intensity level resolution: number of intensity levels used to represent the
image.
• The more intensity levels used, the finer the level of detail discernable in an
image.
• Intensity level resolution usually given in terms of number of bits used to
store each intensity level.

10. Intensity Level Resolution (2)

11. Image File Formats
• Hundreds of image file formats. Examples:
• Tagged Image File Format (TIFF)
• Graphics Interchange Format (GIF)
• Portable Network Graphics (PNG)
• Digital Imaging and Communications in Medicine (DICOM)
• JPEG, BMP, PBM, etc…
• Image pixel values can be:
• Grayscale: 0 – 255 range
• Binary: 0 or 1
• Color: RGB, HSV

12. Histogram
• Histograms plots how many times (frequency) each intensity value in image
occurs.
• E.g. K (Gray levels) = 16, 10 pixels have intensity value = 2.
• No indication of location of pixels.

13. Histogram of RGB Image
• The histogram of an RGB
image can be displayed in
terms of three separate
histograms—one for
each color component (R,
G, and B) of the image.

14. Contrast and
brightness of image
• Dark image: histograms are
concentrated toward the left.
• Light image: histograms are
concentrated toward the right.
• High contrast: histograms cover a
broad range of grayscale level.
• Low contrast: Histograms are
restricted to a smaller range

15. INTRODUCTION to MEDICAL
IMAGING

16. Medical Imaging
X-Rays: ionizing radiation
Radiography
CT scan (Computed Tomography)
Gamma rays
Nuclear Medicine
Sound waves
Ultrasound
Magnetic fields/radiofrequency waves
MRI (Magnetic Resonance Imaging)

17. Who Does Imaging?
• Radiologist
Consultant: Diagnostic, Subspecialties
Interventionalist
• Radiation Oncologist: Treatment planning
• Cardiologist: Invasive, Non-Invasive
• Vascular Surgeon: Endovascular procedures
• Other specialists
Usually for procedure guidance (Ob-Gyn, Internal medicine,
Orthopedics, etc.)

18. Radiography
X - R A Y S

19. Patient Position for Chest X-Ray
Posteroanterior (PA) Chest: X-ray beam
passes from posterior to anterior
RT LT

20. Caution: Pregnancy

21. Computed Tomography
X - R A Y S

22. CT 3D Volume Rendering
Aorta, plaque
Aortic arch
CT Angiogram

23. Diagnostic Ultrasound
Sound Waves

24. Magnetic Resonance Imaging
Magnetic fields

25. Magnetic Resonance Imaging
• Exquisite neuroanatomical detail
• Musculoskeletal disorders
• Cardiovascular

26. PET Scan: Cancer Detection
• Positron Emission
Tomography
• 18F-fluorodeoxyglucose
(FDG)
• Primarily used for
diagnosis, staging &
monitoring of cancers:
lung, breast, cervical,
colorectal, esophagus,
head & neck,
lymphoma, melanoma
Lymphoma pre and post
chemotherapy

27. PET-CT Scanner
Combined PET scanner and CT scanner

28. PET-CT Scans
Fusion imaging
CT PET PET-CT

29. How to access image with
Python
N A D A F I T R I E Y A T U L H I K M A H

30. Loading Images
• imageio : read and save images.

31. Metadata
(DICOM)
• Images are always acquired in a
specific context. This information
is often referred to as metadata.
• Accessible in image objects
through the meta dictionary
attribute.

32. Plotting Images
• Matplotlib's imshow() function displays
2D image data.
• Many colormaps available but ofen
shown in grayscale ( cmap='gray' )
• Axis ticks and labels are often not useful
for images

33. N-dimensional
images are stacks of
arrays

34. Plotting multiple images at once
• plt.subplots: creates a figure
canvas with multiple
AxesSubplots objects.

35. Slicing of 3D view
Modifying aspect ratio: