Qu is a MATLAB toolbox for the visualization and analysis of N-dimensional datasets targeted to the field of biomedical imaging. It supports several microscopy image formats and offers a plugin mechanism and a consistent API for easy extension. One of its advantages compared to similar tools is that it makes use of the power of MATLAB and can use its innumerable tools and functions.

Introduction

Qu makes use and extends MATLAB’s Image Processing Toolbox to address the needs of scientists in the field of biomedical research. It allows the visualization and analysis of 4D (XYZT) datasets with any number of color channels. It allows the loading of several microscopy formats and offers a consistent API to handle the image data, the metadata, and the results of the analyses associated to the data. Primary and derived data are stored in a “Qu project”, a container class that can be saved to disk and reloaded later to continue the analysis from where it was left. In the future, I plan to add database support to (optionally) store Qu projects. Qu implements a plugin mechanism (still under development), that allows users to develop their own processing functions and easily add them to the Qu framework without having to modify the core package. Qu requires MATLAB and the Image Processing Toolbox to run but can make use of any tool(box) that runs on the user’s MATLAB installation. Taking advantage of the capabilities of MATLAB to interface with Java classes and dynamically linked libraries, the user can easily implement new processing and analysis tools in the MATLAB programming language, Java, C/C++, and Fortran, or make use of existing ones. The results can then easily be stored and visualized in Qu through the API. Plugins will also be downloadable from sourceforge.net. An example plugin is contained in the Qu core package. Moreover, Qu offers a connection to Bitplane’s Imaris through ImarisXT, allowing the two-way exchange of data between Imaris and Qu.