Introduction to IDL Dr James Scuffham

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

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”

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

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

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

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%

3D Data Visualisation slices isosurfaces contours

Application Development

Advanced Image Processing

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