Processing Volumetric Data

After collecting volumetric data with the Optotune you can now process your data as follows. First, use sbxsplit() to generate separate data files for each “slice” of the optotune. For example, if I have a data file gn7_008_001.sbx collected some data with an optotune waveform having a period of 5 the command will generate a…

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New alignment and segmentation tools

Improved alignment and segmentation tools have now been released in the latest version of Scanbox, while retaining much of the functionality of the last version. sbxaligntool. The new alignment tool, shown below, adds batch processing of files, including the processing of eye and ball motion if those data are present.  A region-of-interest (ROI) can optionally be…

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Spikefinder: the Vanilla algorithm

Over the last few months, the Spikefinder challenge has provided a playing ground for colleagues to offer ideas about how to estimate the spiking of individual neurons based on the measured activity of fluorescent calcium indicators. The challenge was for people to come up with strategies that beat the performance of state-of-the-art algorithms, STM & oopsi. A good number of algorithms were able…

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An extremely simple deconvolution algorithm

A number of sophisticated deconvolution algorithms have been proposed in the literature, most of which involve solving an optimization problem. While trying to develop a fast, on-line spike detection algorithm for Scanbox I tried a simple idea that seems to work reasonably well and the resulting algorithm is trivial. In all likelihood this must have been published somewhere.  If…

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A montage display for real-time display of volumetric data

  By default, Scanbox displays the incoming image stream on its main window. Thus, during volumetric scanning, one sees the incoming images as depth is changing over time.  If one is imaging only a handful of optical planes, it is difficult to see what is really going on. A different way to visualize the data in…

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Reading scanbox files in Python

One quick way to get your data into Python is by using the Matlab API for Python. First, install the MATLAB engine API for Python by following he instructions here.  You will need to install as administrator. Then, from your Python code you can simply do, as an example: This will read 50 frames starting at index…

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Improvements in alignment and segmentation tools

Two GUIs to align (sbxaligntool) and segment (sbxsegmenttool) two-photon imaging data from Scanbox were recently updated. Sbxaligntool allows users to perform alignment using rigid translation or a non-rigid deformation of the image stack. The tool now uses all the cores available in your computer along with the GPU.  Rigid alignment can take place at near…

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Sbxsegmenttool: A simple GUI for off-line segmentation

Sbxsegmenttool is a simple GUI that replicates the same mechanism used in Scanbox’s online segmentation to assist in the segmentation of cells and/or processes in data that has already been collected. Sbxsegmenttool expects the images to have already been rigidly aligned.  After loading an *.align file, the mean mean aligned image will be shown momentarily and then replaced by a…

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Non-rigid image alignment in twenty lines of Matlab

We have previously discussed rigid and non-rigid image alignment algorithms for calcium imaging data. If you have the image processing toolbox, a particularly compact solution for non-rigid image registration can be written in ~20 lines of code or so.  The code below returns a displacement field for each frame in the image sequence (output variable ‘disp’) that needs…

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Online cell segmentation in Scanbox

There is one hidden feature of Scanbox that has been around for some time, but I have not yet described. This feature allows for computer-assisted segmentation during an experiment. As you must already know, one way in which region of interests (ROIs) can be defined is manually.  This process can be initiated by clicking on the Add button…

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