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Machine Vision

Read MHD/RAW Files in Python: A Complete Guide

By Jan on 03/11/2025

Learn how to easily read and process medical image data in MHD/RAW format using Python libraries like SimpleITK and nibabel.

Read MHD/RAW Files in Python: A Complete Guide

Table of Contents

Introduction

This guide provides a step-by-step approach to reading .mhd medical image files and accessing their data using Python. We will utilize the SimpleITK library, a powerful tool for medical image analysis.

Step-by-Step Guide

  1. Install SimpleITK:

    pip install SimpleITK

  2. Import necessary library:

    import SimpleITK as sitk

  3. Load the MHD file:

    image = sitk.ReadImage('path/to/your/image.mhd')

  4. Access image data as a NumPy array:

    image_array = sitk.GetArrayFromImage(image)

Now you have the image data in the image_array variable, which you can manipulate using NumPy.

Code Example

This Python code demonstrates how to load and access image data from an MHD file using the SimpleITK library. It reads an MHD image file, converts it into a NumPy array, and then shows how to access individual pixel values using array indexing.

# Install SimpleITK
# pip install SimpleITK

# Import necessary library
import SimpleITK as sitk

# Load the MHD file
image = sitk.ReadImage('path/to/your/image.mhd')

# Access image data as a NumPy array
image_array = sitk.GetArrayFromImage(image)

# Now you can work with the image data using NumPy
print(image_array.shape)  # Print the shape of the image array
print(image_array.dtype)  # Print the data type of the image array

# Example: Print the pixel value at coordinates (x=10, y=20, z=30)
x, y, z = 10, 20, 30
pixel_value = image_array[z, y, x]
print(f"Pixel value at ({x}, {y}, {z}): {pixel_value}")

Remember to replace 'path/to/your/image.mhd' with the actual path to your MHD file.

This code snippet demonstrates the basic steps of loading an MHD file using SimpleITK and accessing the image data as a NumPy array. You can then use NumPy functions to manipulate and analyze the image data.

Additional Notes

SimpleITK and MHD Files:

  • MHD/RAW Format: MHD files often come paired with a .raw file containing the actual image data. SimpleITK automatically handles this association, so you only need to specify the .mhd file path.
  • Alternatives to SimpleITK: While SimpleITK is recommended, other libraries like MedPy can also read MHD files. However, SimpleITK is generally considered more powerful and actively maintained.
  • Memory Management: Loading large medical images can consume significant memory. If you encounter memory issues, consider processing the image in chunks or using memory mapping techniques.

Working with Image Data:

  • Image Dimensions: The image_array.shape attribute provides the dimensions of the image (typically in the order of z, y, x for 3D images).
  • Data Type: The image_array.dtype attribute indicates the data type of the image pixels (e.g., uint8, int16, float32). This information is crucial for proper image processing and analysis.
  • Pixel Access and Manipulation: NumPy's array indexing and slicing capabilities allow you to access and modify individual pixels or regions of interest within the image.
  • Visualization: Libraries like Matplotlib can be used to visualize the image data. For 3D images, consider using tools like ITK-SNAP or 3D Slicer.

Beyond the Basics:

  • Image Metadata: The image object contains metadata about the image, such as pixel spacing, image orientation, and origin. This information is essential for accurate spatial calculations and image registration.
  • Image Processing and Analysis: SimpleITK offers a wide range of image processing and analysis algorithms, including filtering, segmentation, registration, and feature extraction.
  • File Format Conversion: You can use SimpleITK to convert MHD files to other common medical image formats like NIfTI (.nii) or DICOM.

This expanded set of notes provides a more comprehensive understanding of working with MHD files and their associated image data in Python.

Summary

Step Description Code
1. Install SimpleITK Install the SimpleITK library for medical image processing. pip install SimpleITK
2. Import SimpleITK Import the SimpleITK library into your Python script. import SimpleITK as sitk
3. Load MHD Image Load the MHD image file using sitk.ReadImage(). image = sitk.ReadImage('path/to/your/image.mhd')
4. Convert to NumPy Array Convert the SimpleITK image object to a NumPy array for further processing. image_array = sitk.GetArrayFromImage(image)

This table summarizes the key steps involved in loading and accessing image data from an MHD file using SimpleITK in Python.

Conclusion

This guide explained how to load and work with .mhd medical image data in Python using SimpleITK. By following these steps, you can easily integrate medical image analysis into your Python projects. Remember to explore the SimpleITK documentation for advanced image processing techniques and functionalities.

References

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