ITK Lecture 10 Review

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ITK Lecture 10Review Toolbox Part II
Damion Shelton

• Methods in Image Analysis
• CMU Robotics Institute 16-725
• U. Pitt Bioengineering 2630
• Spring Term, 2006

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Some thoughts

• Ive collected a bunch of stuff that is either
• Grandiose preaching from the pulpit
• Useful filters/tips/tricks Ive run across
• A lot of what Ill be talking about Ive
  mentioned in passing before hopefully you have a
  different perspective after having written a
  filter

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Generic programming revisited

• Generic programming may be loosely defined as
  programming with concepts (David Musser)
• What concepts have we looked at so far?

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Concept of an image

• An image is rectilinear container in N-space
  which holds regular samples of some physical
  space
• Each of these regular samples is called a pixel

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Concept of a pixel

• A pixel is a sample of data in N-space, and may
  be represented by a variety of data types
  depending on the modality used to acquire the data

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Concept of an iterator

• An iterator is a way to move over an image it
  provides method that mimics sequential access
  regardless of the actual access method or
  dimensionality

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Concept of a pipeline

• There are two main types of objects in the world,
  data objects and process objects
• Typically, we feed a data object to a process
  object and get a new data object as a result
• A sequentially chain of process objects is called
  a pipeline

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Writing generic code

• Successful generic programming means that you
  ignore concerns that would be specific to a
  particular image
• pixel type (i.e. the actual data type)
• dimensionality
• The first way you do this is with templating

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Writing generic code, cont.

• But... templating alone doesnt ensure that your
  code is generic
• Avoid loops that maneuver through dimensionality,
  instead, loop over an iterator
• Use data types (VNL vectors, etc.) to make math
  easier in N-d

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Questions to ask yourself

• Am I making tradeoffs between
• Speed of coding and reusability?
• Level of generality and execution speed?
• Compactness and clarity?
• ITK seems to lean towards reusable, generic, and
  clear code depending on your needs this may be a
  criticism or a point in favor of the toolkit

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When generic programming fails

• As much as wed like, not all algorithms extend
  to N-d or to all pixel types
• But... dont assume that things wont work in
  higher (or lower) dimensions
• I was surprised to discover that code I wrote to
  do medial axis analysis in 3D worked correctly on
  a 4D hypersphere

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The other way of reading images

• You may recall that I mentioned there was another
  way of reading images, besides that presented in
  class
• This method relies on ITKs factory architecture

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Image reading first technique

• We know what kind of image we have (from a dialog
  box, for instance)
• Create a reader that can read that type of image
• Read the image

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Image reading second technique

• We know what kinds of images we might have, but
  dont assume that the user knows
• Register instances of all of reader types we
  might need
• The readers will let us know if they can read the
  file and will do so if possible

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Reading images with the factory

• m_ImageReader ImageFileReaderTypeNew()
• itkMetaImageIOFactoryRegisterOneFactory()
• m_ImageReader-gtSetFileName(m_Filename )
• m_ImageReader-gtUpdate()

Here I only register one factory, but theres no
reason I couldnt have more
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Factory advantages

• The factory model of image reading is a bit more
  flexible and requires less advance knowledge
• If you have a dialog box, you dont have to parse
  the filename to decide what type of reader to
  create
• Less risk of being wrong about file types

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Factory disadvantages

• I find it a bit harder to think of conceptually,
  and you often know what image formats youre
  dealing with anyways

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Gallery of useful ITK classes

• These are classes I have found that solve
  particularly common problems that arise in image
  processing
• Dont re-invent the wheel!
• This list is not comprehensive (obviously)
• I leave specific documentation of these filters
  as an EFTR

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Padding an image

• Problem you need to add extra pixels outside of
  an image (e.g., prior to running a filter)
• Solution PadImageFilter its derived classes

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Cropping an image

• Problem trimming image data from the outside
  edges of an image (the inverse of padding)
• Solution CropImageFilter

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Rescaling image intensity

• Problem you need to translate between two
  different pixel types, or need to shrink or
  expand the dynamic range of a particular pixel
  type
• Solution RescaleIntensityImageFilter

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Computing image derivatives

• Problem you need to compute the derivative at
  each pixel in an image
• Solution DerivativeImageFilter, which is a
  wrapper for the neighborhood tools discussed last
  week
• See also LaplacianImageFilter

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Compute the mirror image

• Problem you want to mirror an image about a
  particular axis or axes
• Solution FlipImageFilter - you specify flipping
  on a per-axis basis

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Rearrange the axes in an image

• Problem the coordinate system of your image
  isnt what you want the x axis should be z, and
  so on
• Solution PermuteAxesImageFilter - you specify
  which input axis maps to which output axis

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Resampling an image

• Problem you want to apply an arbitrary
  coordinate transformation to an image, with the
  output being a new image
• Solution ResampleImageFilter - you control the
  transform and interpolation technique

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Getting a lower dimension image

• Problem you have read time-series volume data as
  a single 4D image, and want a 3D slice of this
  data (one frame in time), or want a 2D slice of a
  3D image, etc.
• Solution ExtractImageFilter - you specify the
  region to extract and the index within the
  parent image of the extraction region

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An(other) introduction to VTK

• For the remainder of this class Ill present a
  brief summary of how VTK works
• Its useful to know whats going on behind the
  scenes in myITKgui
• Its very likely that some of you will want to
  use VTK in stand-alone mode without the FLTK
  wrapper

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Rendering layout of VTK

• vtkRenderWindow defines the window that is
  displayed on your monitor
• vtkRenderers are attached to windows and are
  responsible for converting more abstract
  primitives (vtkActors) into displayed images

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Actors in VTK

• The basic thing that can be displayed in VTK is
  an Actor
• Mappers convert raw data to Actors
• For example
• boundary points in ITK ? VTK pointset ? VTK point
  mask filter ? VTK polygon data mapper ? VTK actor

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vtkRenderWindowInteractors

• Interactors are objects that work with
  RenderWindows to pass mouse and keyboard events
  back and forth
• One particularly useful interactor is
  vtkFlRenderWindowInteractor, which lets you use
  VTK windows with the FLTK window manager

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Widgets

• Widgets are more complicated objects that combine
  some of the functionality of Interactors and
  Actors
• The ImagePlaneWidget is a mouse-controlled object
  that provides an arbitrary slice through a 3D
  volume

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Program layout

• Create a RenderWindow
• Create a Renderer
• Create a FlRenderWindowInteractor
• Load an image
• Create 3 image plane widgets, attach them to the
  interactor
• Enter a message loop to run the program

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Adding additional stuff

• Its easier than you might think to render
  additional objects along with the image plane
  widgets (boundary points for instance)
• Starting with some sort of object in ITK, you
  would do the following...

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Arbitrary object visualization

• Figure out what type of primitive you have
  (points/lines/etc.)
• Create VTK data representing your primitives
• Convert this to poly data
• Map this to an actor

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Data representation in VTK

• For geometric data, you may be interested in the
  following classes
• vtkPoints stores a list of 3D points
• vtkUnstructuredGrid stores a collection of
  arbitrary cells, where a cell is a primitive such
  as a vertex or line (vtkLine)

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Data representation cont.

• This may seem a bit convoluted, but in practice
  its pretty simple once you get the hang of it
• VTK has a pipeline, similar to that of ITK, so
  changing the data/mapper/etc. will affect
  downstream filters but not upstream ones

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Cool side effects

• My favorite1 added bonus of using VTK is the
  ability to export scenes to files
• Since data and rendering are abstracted away from
  each other, its pretty easy to, for example,
  dump your entire rendering setup to a Pixar
  Renderman format file
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