Introduction to ITK. David Doria. (Funded by the US National Library of Medicine)

Transcription

1 Introduction to ITK David Doria (Funded by the US National Library of Medicine)

2 Funded By: (clearly a lot of interest!) National Library of Medicine (NLM) National Institute of Dental and Craniofacial Research National Science Foundation (NSF) National Eye Institute (NEI) National Institute of Neurological Disorders and Stroke (NINDS) National Institute of Mental Health National Institute on Deafness and Other Communication Disorders (NIDCD) National Cancer Institute (NCI)

3 What is ITK?

4 ITK: Insight ToolKit Open source, c++ toolkit for image processing Image Registration and Segmentation Extracts insight from raw data

5 Why Use ITK? MUCH faster than MATLAB Free! Open source if you don't like something, you can change it! A common language for scientists to collaborate and share

6 Why Use ITK? Becoming a required skill for many employers Adobe, GE, Kitware, etc. Applicant should have experience with c++, ITK,

7 World wide collaboration Developers Many universities (UPenn, Columbia, etc) Many big players from industry (GE, etc) Hosted by Kitware (a local company Clifton Park!) Help ensure the open source doesn't get messy Looking for interns!

8 Installing ITK

9 Cross-platform Windows MAC Linux

10 Uses CMake Cross-platform make This is EXTREMELY important to ensure the previous slide (cross-platform-ness) actually works in practice

11 What Does ITK Provide?

12 Input/Output Most 2D and 3D image formats (TIFF, PNG, JPEG, DICOM, BMP, etc) ITK

13 Mathematics Uses the VNL package of VXL Vector and matrix operations

14 Image Transformations Translation Rotation Scaling Similarity Affine

15 Image Processing Histograms Hough Transform (line, circle detection) Edge detection (Canny) Intensity remapping Gradients

16 Image Processing Gaussian, Laplacian Filtering Mean, median filtering Edge preserving filtering Smoothing/blurring Frequency transforms (FFT)

17 Physical spacing, resolution, and direction The above doesn't have to be axis aligned!

18 Do all of this in N-D! Typically N=2,3 Volumetric data is common in medical imaging ITK also does some mesh processing

19 Registration Align two or more images Global registration No feature based registration (yet!)

20 Segmentation Find areas of an image that are similar Region growing Watershed Level Set

21 What does it look like?

22 Pipeline Architecture Connect pieces (filters) together Very easy to reuse code Input File Reader Gradient Filter Writer Output File

23 Pseudo code Compute Image Gradient Get input/output filenames from user (command line) Setup a Reader and read the input file Setup a Gradient filter and compute the gradient of the output of the reader (the image) Setup a Rescale filter to view the gradient as an image, the pixel values must be in a reasonable range Setup a writer and write the output file (gradient image)

24 Real code - Headers #include <string> #include "itkimage.h" #include "itkimagefilereader.h" #include "itkimagefilewriter.h" #include "itkrescaleintensityimagefilter.h" #include "itkgradientmagnitudeimagefilter.h"

25 Real code Command line parsing int main( int argc, char * argv[] ) { //verify command line arguments if( argc < 3 ) { std::cerr << "Usage: " << std::endl; std::cerr << argv[0] << " inputimagefile outputimagefile " << std::endl; return EXIT_FAILURE; } //parse command line arguments std::string inputfilename = argv[1]; std::string outputfilename = argv[2];

26 Real code - Typedefs //setup types typedef float inputpixeltype; typedef float outputpixeltype; typedef itk::image< inputpixeltype, 2 > inputimagetype; typedef itk::image< outputpixeltype, 2 > outputimagetype; typedef itk::imagefilereader< inputimagetype > readertype; typedef itk::gradientmagnitudeimagefilter< inputimagetype, outputimagetype > filtertype;

27 Real code Reader and Gradient Filter //create and setup a reader readertype::pointer reader = readertype::new(); reader->setfilename( inputfilename.c_str() ); //create and setup a gradient filter filtertype::pointer gradientfilter = filtertype::new(); gradientfilter->setinput( reader->getoutput() ); gradientfilter->update();

28 Real code - Rescaler //to write the gradient image file, we must rescale the gradient values to some reasonable range typedef unsigned char writepixeltype; typedef itk::image< writepixeltype, 2 > writeimagetype; typedef itk::rescaleintensityimagefilter< outputimagetype, writeimagetype > rescalefiltertype; rescalefiltertype::pointer rescaler = rescalefiltertype::new(); rescaler->setoutputminimum( 0 ); rescaler->setoutputmaximum( 255 ); rescaler->setinput( gradientfilter->getoutput() );

29 Real code - Writer //create and setup a writer typedef itk::imagefilewriter< writeimagetype > writertype; writertype::pointer writer = writertype::new(); writer->setfilename( outputfilename.c_str() ); writer->setinput( rescaler->getoutput() ); writer->update(); return 0; }

30 That s nice, but how do you see the images? ITK has a cousin VTK, the Visualization ToolKit Primary goal visualization Also has many image processing algorithms (some ITK overlap) Not templated can look easier to a non-c++ programmer

31 Resources

32 Where to get help? ITK Software Guide Nightly documentation (Doxygen): Mailing list