MIPAV

MIPAV

MIPAV (Medical Image Processing, Analysis, and Visualization) is an open-source software tool for processing and analyzing medical images. It supports various image processing functions and quantitative analysis for MRI, PET, CT, and microscopy images.
MIPAV screenshot

MIPAV: Open-Source Medical Image Processing

MIPAV is an open-source software tool for processing and analyzing medical images. It supports various image processing functions and quantitative analysis for MRI, PET, CT, and microscopy images.

What is MIPAV?

MIPAV (Medical Image Processing, Analysis, and Visualization) is a comprehensive open-source software application for processing, analyzing, and visualizing medical images. Developed by the NIH's Center for Information Technology, MIPAV enables researchers and clinicians to leverage advanced quantitative imaging methods for biomedical research and clinical investigations.

Some of the key features and capabilities of MIPAV include:

  • Supports a wide range of medical image formats including DICOM, Analyze, NIfTI, and raw binary images
  • Provides image processing functions such as filtering, registration, segmentation, diffusion tensor tractography as well as quantitative image analysis
  • Advanced visualization with 2D, 3D and 4D viewing, maximum intensity projections (MIP), multiplanar reformatting (MPR) and surface rendering
  • Supports batch processing and execution of automated processing pipelines
  • Interoperability with other analysis software via input/output plugins
  • Customizable interface to facilitate user-driven product improvement
  • Free and open-source under the BSD license

Overall, MIPAV aims to make sophisticated imaging methods more accessible to biomedical researchers. Its comprehensive toolset, wide format support, batch processing capabilities and open architecture allow users to efficiently analyze large multi-parametric imaging datasets. MIPAV continues to be actively developed and maintained by contributors worldwide.

MIPAV Features

Features

  1. Image processing functions like filtering, segmentation, registration, etc
  2. Supports various medical image formats like DICOM, Analyze, Nifti, etc
  3. Quantitative analysis tools for MRI, PET, CT images
  4. 2D, 3D and 4D visualization
  5. Plugin architecture to extend functionality
  6. Scripting interface for batch processing

Pricing

  • Open Source

Pros

Free and open source

Cross-platform availability

Wide range of analysis tools

Support for many medical image formats

Can be extended via plugins

Cons

Steep learning curve

Limited documentation and support

Not as full-featured as some commercial alternatives

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