Download Image Analysis

Lecture 10 – part 2,
Medical Image Analysis and Programming Tools
No suggested problem...
Magnus Gedda [email protected]
2005­04­28
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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
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What you need to start
• Choice of environment depends on
– Image format
– Algorithm(s)
– Data structures
– Graphical user interface (GUI)
– Performance requirements
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Image format
• File
– TIFF, JPG, GIF, PNG, BMP, ...
– Raw files
– “Exotic” format
• Dimensions
– 2D
– 3D
– More (colour, time, features, ...)
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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)
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GUI
• Does the application require user interaction?
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Some available tools
• Survival kit for “non­serious” image processing
• Matlab
• ITK
• ImageJ
• There are a lot of other possibilites out there (often customized for application)
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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)
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The Gimp
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•
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Photoshop­like
www.gimp.org
Open source with big community
Plugins
Developed on Unix platform. Windows version is a port.
• No real CMYK handling (bad for Desktop Publishing)
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Matlab
• MATrix LABoratory
– Optimized for matrix computations
– “No for loops”
•
•
•
www.mathworks.com
Image Processing Toolbox
Commercial
– Matlab 8.000 SEK
– IP Toolbox 3.500 SEK
– Complete Matlab 30.000 SEK
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Matlab ­ IO
• File formats
– JPG, TIFF, GIF, PNG, BMP, ...
– Support for DICOM
fid=fopen(‘file.raw','r')
img=fread(fid_in,'uchar');
img=reshape(img,x,y,z);
– Raw files
• imread, imwrite
– I=imread('imagename.tif','tif')
– imwrite(I,'imagename.tif','tif')
• Image acquisition toolbox
– Direct feed from cameras, microscopes, ...
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Matlab – Basic functions
• Image arithmetics
– Operate directly on matrices: +, ­, ...
– Work with uint8, uint16 data: imadd, imsubstract, …
• Image enhancement
– Change brightness/contrast: imadjust
– Histogram equalisation: histeq
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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)
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Matlab – Basic functions
• Feature extraction
– Linear filtering: filter2
– Classical edge operators: edge
f=fspecial('gaussian');
bilg=filter2(f,bil));
bilEdge=edge(bil,'sobel');
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Matlab ­ Advanced
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Filtering (FIR filter creation – SP toolbox)
Inverse filtering (restoration)
Image transforms (FFT, PCA, ...)
Binary and greyscale morphology
Segmentation
– Watershed (also on color images)
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Matlab ­ Visualization
• 2D display
–
–
imshow
imagesc
• 3D surface rendering
– isosurface, patch
– isocaps, isonormals
– ...
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Matlab ­ GUI
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Matlab ­ More
• Integration capabilities
– Matlab C compiler
– JAVA
• Pros and cons
+ Easy to learn
+ All basic tools in IP toolbox
+ Multi­platform (*.m scripts)
­ Memory handling (double) [Matlab7 uses single]
­ Only optimal for “vectorizable” algorithms
+ N­dimensional
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Matlab ­ Usage
• Prototyping of programs
• Easy for advanced 2D
• Simple 3D
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ImageJ
• Originally developed on Mac for cell analysis of microscopic images (NIH image)
• rsb.info.nih.gov
• Open source (public domain)
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ImageJ ­ IO
• File formats
– TIF (even 16 bits), GIF, JPG, Raw, ...
– Support for DICOM via plugin
• Lots of plugins for different microscopes
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ImageJ – Basic functions
• Image enhancement
• Image measurements
– ROI tools: draw, count, measure
• Edge extraction, binary & grayscale morphology
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ImageJ ­ Extensions
• Add plugin in JAVA
– TransformJ: geometric transformations
– FeatureJ: gradient, 2nd derivative, …
– VolumeJ: volume renderer
– ...
• Scripting language (record function + edit script)
• Use ImageJ as a toolbox within another applet
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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
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ImageJ ­ Usage
• Complete user­interfaced solution
• Easy for mid­advanced 2D
• Simple 3D
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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 self­sustaining community of software users and developers
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ITK – Principles
• The data pipeline
File
Reader
Image
Gaussian
Image
Writer
File
• Generic programming with templates
– ITK images are N­dimensional
– ITK handles arbitrary pixel type
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ITK – Available algorithms
• Binary and grayscale morphology
– Watershed
• Partial differential equations methods
– Anisotropic diffusion filters
– Level sets, fast marching
See IA MN2
• Advanced data structures
– Mesh, point clouds, vector images
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ITK – Extensions
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•
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Write new filters
GUI: fltk, QT, Windows MFC
Visualisation: VTK
Scripting: Tcl, Python, JAVA
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ITK – Pros and cons
+ Growing and very active community
+ Can handle N­dimensional data
+ Open Source: FREE
+ Very advanced algorithms
­ Steep learning curve
­ No built­in GUI
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ITK – Usage
• Serious IA/IP needs
• Multi­dimensional algorithms
• Speed (C++ on image buffers)
• Prototyping IA/IP programs using scripting languages
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