Pyvox is a software suite designed for the processing of medical images. It offers a range of tools to make the task more efficient and effective.
Pyvox is a software tool designed for medical image processing, primarily used for skull stripping and segmentation of MR brain images. It is intended to assist researchers in prototyping new image analysis algorithms and developing automated image analysis tools for specific image analysis applications. Pyvox operates through the use of the scripting language Python, which can be used interactively or in command files. The core image processing algorithms are written in C for efficient processing of volume images.
The software is designed to be portable across multiple Unix platforms, including Linux and Mac OS X, and suitable for rapid prototyping of new algorithms and analysis protocols. It is also efficient for automated processing of finished analysis protocols and easily extensible by programmers outside the original development team. Pyvox is distributed under an Open Source license, permitting free use, modification, and redistribution provided proper credit is given.
Pyvox is primarily designed for medical image processing, but other applications of volume images are also possible. The software is implemented as an extension to the Python language, which is a high-level object-oriented scripting language designed to be easily extensible in C.
Core image processing functions in Pyvox are written in C, which is more efficient than Python, ensuring that it is suitable for efficient, automated processing of the finished analysis protocols. To meet software portability requirements, Pyvox is written to comply with the usual standards, including ANSI C, Posix, and the X Window System.
The software is also designed to ensure that image files and other data files are portable across different Unix platforms. This is achieved through a set of portable C functions that read and write data in specified external formats, converting as necessary to or from the platform-native format.
Pyvox should be easily extensible by programmers outside the original development team. This is achieved through good software engineering practice in documenting the software for later maintenance and extensions.
Installation of Pyvox is simple if the prerequisites, including Python 2.1, X11 Window System, Tcl/Tk, Motif or Lesstif, and optionally LAPACK and BLAS are present and installed. The command sequence ./configure make make regress make install will compile, regression test, and install Pyvox. Otherwise, the Pyvox Reference Manual should be consulted for a detailed installation procedure.
The latest release of Pyvox features a completely redesigned interface for constructing convolution kernels, which now supports the dynamic modification of kernels. Additionally, internal types in the software now have min and max attributes, which contain the minimum and maximum possible finite positive values representable in that type.
The software is designed to be portable across multiple Unix platforms, including Linux and Mac OS X, and suitable for rapid prototyping of new algorithms and analysis protocols. It is also efficient for automated processing of finished analysis protocols and easily extensible by programmers outside the original development team. Pyvox is distributed under an Open Source license, permitting free use, modification, and redistribution provided proper credit is given.
Pyvox is primarily designed for medical image processing, but other applications of volume images are also possible. The software is implemented as an extension to the Python language, which is a high-level object-oriented scripting language designed to be easily extensible in C.
Core image processing functions in Pyvox are written in C, which is more efficient than Python, ensuring that it is suitable for efficient, automated processing of the finished analysis protocols. To meet software portability requirements, Pyvox is written to comply with the usual standards, including ANSI C, Posix, and the X Window System.
The software is also designed to ensure that image files and other data files are portable across different Unix platforms. This is achieved through a set of portable C functions that read and write data in specified external formats, converting as necessary to or from the platform-native format.
Pyvox should be easily extensible by programmers outside the original development team. This is achieved through good software engineering practice in documenting the software for later maintenance and extensions.
Installation of Pyvox is simple if the prerequisites, including Python 2.1, X11 Window System, Tcl/Tk, Motif or Lesstif, and optionally LAPACK and BLAS are present and installed. The command sequence ./configure make make regress make install will compile, regression test, and install Pyvox. Otherwise, the Pyvox Reference Manual should be consulted for a detailed installation procedure.
The latest release of Pyvox features a completely redesigned interface for constructing convolution kernels, which now supports the dynamic modification of kernels. Additionally, internal types in the software now have min and max attributes, which contain the minimum and maximum possible finite positive values representable in that type.
What's New
Version 0.72: N/A