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# ITK (Insight Toolkit)
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ITK is a comprehensive, open-source C++ toolkit for medical image analysis, providing advanced algorithms for image segmentation (identifying structures in medical images) and registration (aligning multiple image datasets). Built with a modular architecture, ITK supports cross-platform development and extensive customization for medical imaging research and clinical applications.
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## Package Information
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- **Package Name**: ITK (Insight Toolkit)
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- **Package Type**: C++ Library
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- **Language**: C++
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- **Build System**: CMake
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- **Installation**: Build from source using CMake, or use system package managers
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- **Version**: 4.13.2
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## Core Imports
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ITK uses a namespace-based approach with templated classes:
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```cpp
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#include "itkImage.h"
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#include "itkImageFileReader.h" 
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#include "itkImageFileWriter.h"
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// Using ITK namespace
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using namespace itk;
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// Typical type definitions
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typedef short                             PixelType;
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const unsigned int                        Dimension = 3;
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typedef itk::Image<PixelType, Dimension>  ImageType;
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```
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## Basic Usage
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```cpp
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#include "itkImage.h"
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#include "itkImageFileReader.h"
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#include "itkImageFileWriter.h"
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int main()
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{
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    // Define image types
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    typedef short                             PixelType;
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    const unsigned int                        Dimension = 3;
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    typedef itk::Image<PixelType, Dimension>  ImageType;
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    // Create reader and writer
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    typedef itk::ImageFileReader<ImageType>   ReaderType;
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    typedef itk::ImageFileWriter<ImageType>   WriterType;
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    ReaderType::Pointer reader = ReaderType::New();
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    WriterType::Pointer writer = WriterType::New();
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    // Configure pipeline
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    reader->SetFileName("input.nii");
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    writer->SetFileName("output.nii");
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    writer->SetInput(reader->GetOutput());
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    // Execute pipeline
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    try {
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        writer->Update();
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    } catch (itk::ExceptionObject & error) {
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        std::cerr << "Error: " << error << std::endl;
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        return EXIT_FAILURE;
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    }
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    return EXIT_SUCCESS;
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}
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```
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## Architecture
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ITK follows a pipeline-based architecture with the following key design patterns:
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- **Smart Pointer Management**: All objects use reference-counted smart pointers (`Pointer` and `ConstPointer`)
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- **Template-Based Design**: Extensive use of C++ templates for type safety and performance
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- **Pipeline Architecture**: Data flows through connected processing objects with lazy evaluation
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- **Modular Structure**: Organized into specialized modules for different imaging tasks
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- **Observer Pattern**: Event-driven notifications for progress and status updates
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## Capabilities
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### Core Data Structures
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ITK provides fundamental data structures for medical image analysis.
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```cpp { .api }
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// N-dimensional templated image
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template<typename TPixel, unsigned int VDimension>
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class Image : public ImageBase<VDimension>;
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// Image region specification  
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template<unsigned int VDimension>
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struct ImageRegion;
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// N-dimensional point
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template<typename T, unsigned int VDimension>
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class Point;
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// N-dimensional vector
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template<typename T, unsigned int VDimension>
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class Vector;
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```
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[Core Data Structures](./core-data-structures.md)
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### Input/Output Operations
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Comprehensive support for reading and writing medical and standard image formats.
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```cpp { .api }
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// Generic image file reader
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template<typename TOutputImage>
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class ImageFileReader : public ImageSource<TOutputImage>;
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// Generic image file writer  
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template<typename TInputImage>
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class ImageFileWriter : public ProcessObject;
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// Base class for format-specific IO
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class ImageIOBase;
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```
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[Input/Output Operations](./io-operations.md)
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### Image Processing Filters
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Extensive collection of image processing and analysis filters.
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```cpp { .api }
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// Base class for image-to-image filters
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template<typename TInputImage, typename TOutputImage>
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class ImageToImageFilter : public ImageSource<TOutputImage>;
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// Gaussian smoothing filter
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template<typename TInputImage, typename TOutputImage>
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class SmoothingRecursiveGaussianImageFilter : public ImageToImageFilter<TInputImage, TOutputImage>;
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// Threshold segmentation filter
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template<typename TInputImage, typename TOutputImage>
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class BinaryThresholdImageFilter : public ImageToImageFilter<TInputImage, TOutputImage>;
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```
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[Image Processing Filters](./image-processing.md)
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### Registration Framework
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Algorithms for aligning and registering multiple image datasets.
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```cpp { .api }
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// Main registration method class
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template<typename TFixedImage, typename TMovingImage>
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class ImageRegistrationMethod : public ProcessObject;
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// Base class for similarity metrics
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template<typename TFixedImage, typename TMovingImage>
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class ImageToImageMetric : public SingleValuedCostFunction;
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// Base class for geometric transformations
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template<typename TScalarType, unsigned int NDimensions>
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class Transform : public TransformBase;
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```
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[Registration Framework](./registration.md)
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### Segmentation Algorithms
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Advanced algorithms for identifying and classifying structures in medical images.
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```cpp { .api }
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// Connected component segmentation
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template<typename TInputImage, typename TOutputImage>
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class ConnectedThresholdImageFilter : public ImageToImageFilter<TInputImage, TOutputImage>;
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// Level set segmentation base
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template<typename TInputImage, typename TFeatureImage, typename TOutputPixelType>
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class SegmentationLevelSetImageFilter : public SparseFieldLevelSetImageFilter<TInputImage, TOutputPixelType>;
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// Fast marching method
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template<typename TLevelSet, typename TSpeedImage>
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class FastMarchingImageFilter : public ImageToImageFilter<TSpeedImage, TLevelSet>;
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```
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[Segmentation Algorithms](./segmentation.md)
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### Mesh Processing
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Support for mesh data structures and geometric processing.
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```cpp { .api }
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// General mesh structure
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template<typename TPixelType, unsigned int VDimension>
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class Mesh : public PointSet<TPixelType, VDimension>;
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// Advanced mesh topology
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template<typename TPixel, unsigned int VDimension>
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class QuadEdgeMesh : public Mesh<TPixel, VDimension>;
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// Point cloud representation
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template<typename TPixelType, unsigned int VDimension>  
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class PointSet : public DataObject;
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```
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[Mesh Processing](./mesh-processing.md)
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### Spatial Objects
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Geometric primitives and spatial object representations.
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```cpp { .api }
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// Base spatial object class
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template<unsigned int TDimension>
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class SpatialObject : public DataObject;
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// Elliptical spatial objects
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template<unsigned int TDimension>
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class EllipseSpatialObject : public SpatialObject<TDimension>;
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// Tubular structures
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template<unsigned int TDimension>
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class TubeSpatialObject : public SpatialObject<TDimension>;
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```
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[Spatial Objects](./spatial-objects.md)
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### Mathematical Operations
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Numerical algorithms, optimization, and statistical operations.
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```cpp { .api }
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// Base optimizer class
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class Optimizer : public Object;
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// Gradient descent optimization
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class GradientDescentOptimizer : public SingleValuedNonLinearOptimizer;
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// Statistical sample interface
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template<typename TMeasurementVector>
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class Sample : public DataObject;
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```
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[Mathematical Operations](./mathematical-operations.md)
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## Common Types
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```cpp { .api }
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// Smart pointer types
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template<typename T>
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class SmartPointer;
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template<typename T>  
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class WeakPointer;
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// Base object types
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class LightObject;
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class Object : public LightObject;
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class DataObject : public Object;
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class ProcessObject : public Object;
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// Numeric traits
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template<typename T>
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struct NumericTraits;
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// Exception handling
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class ExceptionObject;
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class ProcessAborted : public ExceptionObject;
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// Time and modification tracking
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typedef unsigned long ModifiedTimeType;
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class TimeStamp;
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// Event system
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class EventObject;
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class Command;
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```
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ITK's extensive API surface includes hundreds of specialized classes for medical image analysis. Each capability area provides both high-level convenience classes and fine-grained control over processing parameters, making it suitable for both rapid prototyping and production medical imaging applications.