1. CT Learning Objectives
Central Section Theorem
-F{g (R)} = F(r, )
-Understand what this means and how to apply it backwards and forwards
-Understand how this theorem applies to CT reconstruction.
Two CT reconstruction methods
Convolution-Back Projection
∫ d ∫ [ g (R) * c (R) ]  ( x cos  + y sin  - R) dR ∞

2. -o o Filtered Back Projection Filtering Function: CT SNR where
w = width of pixel
h = slice thickness
M = number of projections
C = contrast
= average attenuation

3. CT Learning Objectives
Appearance of CT impulse response in cases of angular undersampling
Requirements for angular sampling to meet Nyquist sampling requirement