1. BMME 560 & BME 590I Medical Imaging: X-ray, CT, and Nuclear Methods
X-ray Imaging Part 2

2. Today Contrast Noise Resolution vs. noise Nonuniformities Scatter
Inverse square law
Oblique angle
Heel effect
Scatter
Contrast agents
Metals
Noise
Photonic noise
Film noise
Electronic noise
QE and DQE
Resolution vs. noise

3. Contrast So, contrast depends on two primary factors
The difference in linear attenuation coefficient between feature and background
The thickness (size) of the feature
All is a function of energy.

4. Contrast
Properties of materials

5. Contrast Several factors can create nonuniformity of the beam.
This does not really change local contrast.
It does make comparisons at different points of the radiograph difficult.

6. Contrast Nonuniformties Heel effect Inverse square law
Oblique beam angle

7. Contrast Anode heel effect
Angle of anode (target) results in angle-dependent production and attenuation of X-rays
Beam intensity drops off significantly on anode side, and somewhat on cathode side.
This curve represents beam intensity

8. Contrast Ways to combat heel effect
Restriction/collimation
Compensation filtering
Smart patient positioning
Increase source-detector distance
Change anode angle
What are the disadvantages of each of these?

9. Contrast Inverse square law
We know the flux drops off as the inverse square of the distance from the source.
Flux = photons per unit area
The corner of the detector is further from the source I2 I1 r d q

10. Contrast Oblique angle X-rays strike the detector at an oblique angle.
The effective area of a detector pixel is reduced. I2 I1 r d q

11. Contrast
Net effect
The net effect of square law and oblique angle is to cause the intensity to drop off as: I2 I1 r d q

12. Contrast Ways to angular nonuniformity
Compensation filtering
Smart patient positioning
Increase source-detector distance
What are the disadvantages of each of these?

13. Contrast Compton scatter Scatter has broad low-level tails.
For a relatively uniform object, this produces a constant background across the image.

14. Contrast without scatter: with scatter:
contrast degradation due to scatter
Scatter-to-primary ratio

15. Contrast
Scatter
Question: Can’t we just estimate the scatter and subtract it?

16. Contrast Contrast agents must be Iodine and barium are the most common
soluble (i.e., easy to introduce into the body and mobile within it)
high-Z
non-toxic (at concentrations that will provide contrast)
Iodine and barium are the most common
Air is pretty good too, though it is a low-Z contrast agent

17. Contrast Contrast agents: Iodine and barium
K-absorption edges in the radiographic energy range make these better than most materials

18. Contrast Iodine contrast agents
Solubility is useful for injection and intravenous use
Vascular imaging
Thyroid imaging
Renal and urinary tract imaging
Angiography link

19. Contrast Barium sulfate
Not so soluble, but good for gastrointenstinal applications – “Barium milkshake”
Mimics properties of digested material
Image source: American Society of Radiologic Technologists

20. Contrast Air or CO2 Nearly zero attenuation
Lungs (about one-third tissue)
Intestine

21. Contrast Metals High contrast No internal detail
X-rays do not pass through
image from: Wagner et al, “Qualitative evaluation of titanium implant integration into bone by diffraction enhanced imaging,” Phys Med Biol, 51 (2006) 1313–1324.

22. Noise
Noise is random pixelwise intensity variation about the expected image
Raw noise is often “white”
Noise can be filtered and reduced, but at the expense of resolution.
Noise creates problems in:
Visualizing details
Quantifying regions of images

23. Noise Several potential sources of noise Photonic noise Film noise
Electronic noise

24. Noise Photons are discrete packets of energy.
They are emitted at random.
Photon emission follows the Poisson distribution:
where n is the random variable, the number of photons emitted in a unit time (a positive integer),
and m is the average number of photons emitted in that time (a positive real number).

25. Noise Key property of the Poisson distribution:
So, as the mean photon flux increases, the variance increases also.
More photons = more noise?

26. Noise Look at it as a signal-to-noise ratio
Let signal be the mean number of photons in a detector pixel in a unit time =
Let noise be the standard deviation of the number of photons measured in that time =
The signal to noise ratio is

27. Key point
As we increase the mean number of photons detected per unit area of detector, what happens to signal-to-noise ratio?

28. Example Problem Comparing two detector materials
Material 1 stops and records 50% of incident photons
Material 2 stops and records 80% of incident photons
For an exposure producing 106 photons incident on the detector, what is the SNR for detectors made of each material?
How about for 103 photons?

29. Noise Ways to increase the number of photons collected per pixel:
What are the disadvantages of each?

30. Noise
Nonuniformities in the beam can cause nonuniform noise properties
Heel effect
Angular variation
Recall that we can use compensation filters to improve uniformity, but at what cost?

31. Noise Thought question:
What regions of the radiograph will have higher photonic noise?

32. Noise
Other sources
Film grain
Detector electronics
These are often modeled as constant background noise.
They add to the photonic noise

33. Noise

34. Noise
What happens to noise when we subtract two images?

35. Noise Quantum efficiency (QE) Detective quantum efficiency (DQE)
The probability that a photon incident on the detector will be stopped and detected
This does not say how well it is detected!
Detective quantum efficiency (DQE)
The decrease in SNR from detector input to output
Accounts for probability of detection and quality of detection

36. Example Problem
A detector stops 80% of incident photons and has background noise of variance 1000.
What is its DQE for 104 incident photons?
At 103 incident photons, this decreases to .358.

37. Key Point
There is an essential and inescapable tradeoff between noise and resolution in every imaging system.
Resolution (FWHM)
Noise variance

38. Noise and Resolution Factors limiting resolution
Detector design
Focal spot
Scatter
Magnification
Factors contributing to noise
Number of photons collected per pixel per unit time
Background

39. Noise and Resolution Detector design Focal spot
Improve resolution with smaller pixels, but detect fewer photons per pixel.
Improve QE with thicker scintillator layer, but degrade resolution due to light scattering.
Focal spot
Decrease focal spot size by making components smaller, but decrease flux available due to heating considerations.

40. Noise, Contrast, and Resolution
Scatter
Apply anti-scatter grid to improve contrast, but detect fewer photons and fewer primary photons.
Magnification
Shorten source-to-detector distance to increase magnification, but increase nonuniformity due to angular effects.

41. Other tradeoffs Temporal resolution versus spatial resolution
Magnification versus field of view
Contrast versus dynamic range