1. Introduction to IDL
Dr James Scuffham

2. Interactive Data Language
What is IDL?
Interactive Data Language
“Procedural” programming language
Compiled functions and procedures OR run-time interpreter
Enormous library of pre-written and validated routines
Widely used in the medical imaging community

4. What can it do? Data Analysis and modelling: Image Processing:
Maths: calculus, solve equations, FFT, DWT, optimisation
Statistics: regression, hypothesis testing, curve fitting
Image Processing:
Translate, transpose, rotate, zoom, resample, extract, warp
Regions of interest, profiles, histograms
Filtering, edge enhancement, 2D-FFT
Convolution, correlation, feature extraction
Data Visualisation:
Plot graphs and display images
Animate dynamic data
Volume rendered surface plots
Vector field visualisation
Application development:
‘Widgets’
Cross-platform capability: “Virtual Machine”

5. Applications in Nuclear Medicine
Supports DICOM and Interfile formats
Displaying static images, drawing ROIs, obtaining statistics
Displaying dynamic images, plotting time-activity curves, processing results
Performing advanced image processing

6. Basic Image Processing
READ_INTERFILE, ‘muga.HDR’, X
frame0=ROTATE(X,7)
frame0 = CONGRID(frame0,512,512)
XROI, BYTSCL(frame0), STATISTICS=stats

7. Dynamic Images PRO cine_muga, data, repeats
data = BYTSCL(ROTATE(data,7))
data = CONGRID(data, 512, 512)
howbig = SIZE(data)
FOR c = 0, howbig[3]*repeats DO BEGIN
display_image = data[*,*,(c MOD howbig[3]-1)]
TV, display_image
ENDFOR
END

8. Curve Processing left_area = INT_TABULATED(time, left_kid)
right_area = INT_TABULATED(time, right_kid)
left_div_func = 100.0*left_area/(left_area+right_area)
right_div_func = 100.0*right_area/(left_area+right_area)
Left = 56%
Right = 44%

9. 3D Data Visualisation
slices
isosurfaces
contours

10. Application Development

11. Advanced Image Processing

12. Summary
IDL is really useful…..
……and not just for image processing