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Principles of CT.

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Presentation on theme: "Principles of CT."— Presentation transcript:

1 Principles of CT

2 Limitations of Radiography
Inefficient x-ray absorption: typically ~25% for par speed cassette (prior to rare earth technology) High Scatter-to-Primary Ratios: may have >50% scatter at receptor with large beams even with high ratio grid Receptor Contrast vs latitude: required film dynamic range limits film contrast Superposition/Conspicuity: overlapping structures with 3D anatomy rendered on 2D image

3 Focal Plane Tomography: Bocage 1921

4 Early Attempts at CT Gabriel Frank: 1940 Patent: described CT principles using optical backprojection reconstr (but no filter) Takahashi (Japan, ‘40s, published 1956): describes equipment to image slices by backprojection Tetel’baum et al (Russia, 1957): Accurate formulation of inverse Radon Transform; TV-based reconstruct Kuhl & Edwards: (1963): cross-sectional NM images by back-projecting transmission data on oscilloscope Alan Cormack: built simple CT to measure densities for radiotherapy. Shared Nobel Prize.

5 Godfrey Hounsfield and EMI: 1967
Considered areas where much information available but inefficiently used: radiography Estimated that if efficient detection/analysis, attenuation coefficients measurable within 0.5% from transmission measurements ---> sufficient to distinguish soft tissue differences Invisioned “slice” divided in small “voxels” Experiments using Americium source (9-day acquisition) verified 0.5% accuracy achievable

6 Pixels and Voxels

7 1st Generation Data Collection

8 Hounsfield’s CT Formulation
Measurement Ni written as sum of attenuation of pixel along path Solve simultan-eous equations from data at many positions and angles Experiments achieved 0.5% accuracy.

9 Hounsfield’s Experimental CT

10 Specimen Scan with Lab Device

11 1st Generation Data Collection
1 Pencil Beam and 1 NaI detector 160 samples/traverse 1o increms over 180o 28,800 samples Solved simultaneous equations (Fortran) 1602 image matrix but reduced to 802 for practical clinical use

12 EMI Mark 1

13 Image Reconstuction

14 Image Reconstuction

15 Backprojection



18 Backprojection (con’t)

19 Convolution

20 Filtered Backprojection



23 CT Numbers: Hounsfield Units
Example 1: voxel contains water (up= uw): CT# = 1000 x (uw - uw)/ uw = 0 Example: voxel contains air (up≈ 0): CT# = 1000 x (0 - uw)/ uw = 1000 x (-1) = -1000

24 CT Numbers

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