Welcome to the Future of Kinetic Modeling in Healthcare

Comprehensive tools for total-body PET analysis and dynamic tracer studies.

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Enhancing tracer kinetic modeling for PET imaging research.

Innovating PET Imaging

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Collaborate with OpenKMI to develop scalable and open PET solutions.

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The Heart of OpenKMI: Meet OpenKMAP

KMAP (Kinetic Modeling and Analysis Package) offers a collection of C/C++ source code and wrapper functions designed to implement and apply different tracer kinetic models for analyzing dynamic positron emission tomography (PET) data, particularly in response to the challenges emerging in total-body PET kinetic modeling. The package was originally developed at the University of California, Davis. Its open-source version, OpenKMAP, was launched to support the Open Kinetic Modeling Initiative. The primary objective of this open-source package is to share tracer kinetic modeling techniques and offer kinetic modeling developers a foundation to build upon without starting from scratch.

As part of OpenKMAP, two key packages are currently provided:

  • KMAP-C: A C/C++ toolkit that provides a suite of routines for implementing various tracer kinetic models. These include source code and MEX files that enable integration with other software, such as MATLAB.
  • KMAP-M: A MATLAB toolbox built on top of OpenKMAP-C. This toolbox provides an interface for performing kinetic modeling and analysis using MATLAB, supporting multiple operating systems including Windows, Linux, and macOS.

Together, KMAP-C and KMAP-M offer a solution for researchers in tracer kinetic modeling, providing both the low-level computational tools and the high-level MATLAB functionality.

WARNING

The OpenKMAP packages offer open-source code to disseminate basic and advanced tracer kinetic modeling approaches in a timely manner. These packages are not intended to serve as a comprehensive and user-friendly software solution for end users. For those seeking an all-encompassing solution, commercial software like PMOD may be a better option.

Both KMAP-C and KMAP-M are continually being updated. The development team is working on adding new models, optimizing performance, and expanding the functionality. These packages are provided “as is” without warranty. The shared modeling code may also only reflect the research interests of a very limited number of groups.

Contributing

We welcome contributions from the community! Whether you’d like to suggest improvements, report bugs, or contribute code, we encourage you to get involved. Please refer to the contribution guidelines in each repository for more details.

Our Projects

KMAP-C

A robust library for compiling and optimizing MEX binaries for advanced kinetic modeling, ensuring performance and scalability.

KMAP-M

A MATLAB-based interface simplifying kinetic modeling workflows, from TAC generation to advanced parametric imaging.

OpenIFun

A dedicated toolset for efficiently working with input functions, streamlining preprocessing and data integration in modeling.

Frequently Asked Questions

OpenKMAP is an open-source framework for kinetic modeling and parametric imaging, offering robust tools for analyzing PET data using various compartmental models. It simplifies research workflows through precompiled binaries and intuitive MATLAB integrations.
OpenKMAP is designed for a diverse audience, including researchers, clinicians, and data scientists in fields such as medical imaging, computational biology, and healthcare analytics. Its open-source nature makes it accessible to everyone.
OpenKMAP supports a range of models, including:
  • One-tissue compartment model (1TCM)
  • Two-tissue compartment model (2TCM)
  • Liver-specific models
  • Patlak and relative Patlak plots
These models cover a wide variety of kinetic analyses and use cases.
Not at all! OpenKMAP offers precompiled binaries for Linux, Windows, and macOS, ensuring seamless cross-platform compatibility.
We welcome contributions from the community! Whether it's improving existing features, reporting bugs, or adding new functionality, your contributions are invaluable. Visit our GitHub repository for more details on how to get started.
No, OpenKMAP is designed to be user-friendly. While basic MATLAB knowledge is helpful, the intuitive wrapper functions and detailed documentation make it easy to use for both beginners and experienced users.
To get started:
  • Clone or download the repositories from our GitHub page.
  • Install the required dependencies (details in the documentation).
  • Explore the sample demos provided to familiarize yourself with the framework.
OpenKMAP is fully open-source and distributed under the MIT license. This allows users to freely modify, use, and distribute the framework while retaining appropriate attribution.