Medical Image Analysis and Programming Tools

Transcription

1 Lecture 10 part 2, Medical Image Analysis and Programming Tools No suggested problem... Magnus Gedda

2 Programming for Image Analysis/Processing Tools and guidelines for writing your own image analysis/processing applications What is needed when you start a project Tools to help you along the way 2

3 What you need to start Choice of environment depends on Image format Algorithm(s) Data structures Graphical user interface (GUI) Performance requirements 3

4 Image format File TIFF, JPG, GIF, PNG, BMP,... Raw files Exotic format Dimensions 2D 3D More (colour, time, features,...) 4

5 Algorithms and data structures Typical data structures Arrays (images) Stacks and queues (e.g., region growing) Graphs, trees, lists,... Typical algorithms Convolution Numerical (e.g., integration) Transforms (e.g., FFT) Geometry (e.g., convex hull) 5

6 GUI Does the application require user interaction? 6

7 Some available tools Survival kit for non serious image processing Matlab ITK ImageJ There are a lot of other possibilites out there (often customized for application) 7

8 Survival kit View XV (*nix freeware) IrfanView (Win freeware) Convert ImageMagick (Mac/*nix freeware) Manipulate, create (and convert) Adobe Photoshop (Win/Mac commercial) Paint Shop Pro (Win shareware) The Gimp (Win/Mac/*nix open source) 8

9 The Gimp Photoshop like Open source with big community Plugins Developed on Unix platform. Windows version is a port. No real CMYK handling (bad for Desktop Publishing) 9

10 Matlab MATrix LABoratory Optimized for matrix computations No for loops Image Processing Toolbox Commercial Matlab SEK IP Toolbox SEK Complete Matlab SEK 10

11 Matlab IO File formats JPG, TIFF, GIF, PNG, BMP,... Support for DICOM Raw files imread, imwrite I=imread('imagename.tif','tif') imwrite(i,'imagename.tif','tif') Image acquisition toolbox fid=fopen( file.raw','r') img=fread(fid_in,'uchar'); img=reshape(img,x,y,z); Direct feed from cameras, microscopes,... 11

12 Matlab Basic functions Image arithmetics Operate directly on matrices: +,,... Work with uint8, uint16 data: imadd, imsubstract, Image enhancement imadd, Change brightness/contrast: imadjust Histogram equalisation: histeq 12

13 Matlab Basic functions Geometric transformations imrotate, imcrop imtransform (affine, projective,...) Resizing, interpolation imresize Interpolation methods Nearest (neighbour) Bilinear (2x2), bicubic (4x4) Spline (if Spline toolbox installed) 13

14 Matlab Basic functions Feature extraction Linear filtering: filter2 Classical edge operators: edge f=fspecial('gaussian'); bilg=filter2(f,bil)); biledge=edge(bil,'sobel'); 14

15 Matlab Advanced Filtering (FIR filter creation SP toolbox) Inverse filtering (restoration) Image transforms (FFT, PCA,...) Binary and greyscale morphology Segmentation Watershed (also on color images) 15

16 Matlab Visualization 2D display imshow imagesc 3D surface rendering isosurface, patch isocaps, isonormals... 16

17 Matlab GUI 17

18 Matlab More Integration capabilities Matlab C compiler JAVA Pros and cons + Easy to learn + All basic tools in IP toolbox + Multi platform (*.m scripts) + N dimensional Memory handling (double) [Matlab7 uses single] Only optimal for vectorizable algorithms 18

19 Matlab Usage Prototyping of programs Easy for advanced 2D Simple 3D 19

20 ImageJ Originally developed on Mac for cell analysis of microscopic images (NIH image) rsb.info.nih.gov Open source (public domain) 20

21 ImageJ IO File formats TIF (even 16 bits), GIF, JPG, Raw,... Support for DICOM via plugin Lots of plugins for different microscopes 21

22 ImageJ Basic functions Image enhancement Image measurements ROI tools: draw, count, measure Edge extraction, binary & grayscale morphology 22

23 ImageJ Extensions Add plugin in JAVA TransformJ: geometric transformations FeatureJ: gradient, 2 nd derivative, VolumeJ: volume renderer... Scripting language (record function + edit script) Use ImageJ as a toolbox within another applet 23

24 ImageJ Pros and cons + JAVA: easy to learn + JAVA: runs on all platforms + Open source: FREE + Extensions by JAVA plugins or scripting Data type not originally meant for 3D 24

25 ImageJ Usage Complete user interfaced solution Easy for mid advanced 2D Simple 3D 25

26 ITK NLM Insight Segmentation & Registration Toolkit Project at the National Library of Medicine (at NIH) Goals Support the Visible Human Project Create a repository of fundamental algorithms Develop a platform for advanced product development Grow a self sustaining community of software users and developers 26

27 ITK Principles The data pipeline File Reader Image Gaussian Image Writer File Generic programming with templates ITK images are N dimensional ITK handles arbitrary pixel type 27

28 ITK Available algorithms Binary and grayscale morphology Watershed Partial differential equations methods Anisotropic diffusion filters Level sets, fast marching Advanced data structures Mesh, point clouds, vector images See IA MN2 28

29 ITK Extensions Write new filters GUI: fltk, QT, Windows MFC Visualisation: VTK Scripting: Tcl, Python, JAVA 29

30 ITK Pros and cons + Growing and very active community + Can handle N dimensional data + Open Source: FREE + Very advanced algorithms Steep learning curve No built in GUI 30

31 ITK Usage Serious IA/IP needs Multi dimensional algorithms Speed (C++ on image buffers) Prototyping IA/IP programs using scripting languages 31