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Low Light Tracking Tool

101 bytes removed, 13:23, 8 October 2015
Replace User links with Person template
{{Infobox Plugin
| name = Blob Tracking
| software = Fiji
| author = [[User:{{Person|Alex-krull | Alexander Krull]]}}, [[User:damienrj {{Person| Damien Ramunno-Johnson]]Damienrj}}| maintainer = [[User:{{Person|Alex-krull|Alexander Krull]]}}, [[User:damienrj {{Person| Damien Ramunno-Johnson]]Damienrj}}
| source = https://github.com/alex-krull/fiji
| released = May 22<sup>nd</sup>, 2013
This software is a tool for the tracking of low-light sub-resolution objects in fluorescent microscopy. It can be applied in other fields as well. The plugin implements the localization algorithm described in the following paper:
"A Divide and Conquer Strategy for the Maximum Likelihood localization of Low Intensity Objects" by Alexander Krull et al, 2013 Optics Express, Vol. 22, Issue 1, pp. 210-228 (under preparation2014).
=Installation of the plugin=
[[Image:Controlwindownew.png]]
If you would like the windows to become larger or smaller, change the size of the main data window and then select '''Arrange Windows''', from the '''View''' menu. Alternatively you can use the [[Low_Light_Tracking_Tool#Hot-Keys | hot-key]] '''{{key|Ctrl-}}+{{key|W''' }} (when the focus is on the control panel) or '''{{key|W''' }} (when the focus is on one of the other windows). This will also organize the windows if they have become scattered.
If you close some of the windows you can bring them back using the '''Windows''' menu in the control panel.
There are currently two tracking algorithms available:
===GaussianML===
This algorithm implements the [http[wikipedia://en.wikipedia.org/wiki/Maximum_likelihood_estimator Maximum likelihood estimator|maximum likelihood estimator]] based on a [http[wikipedia://en.wikipedia.org/wiki/Shot_noise Shot noise|shot noise]] model. This means it considers the statistics of photon distribution in the image generation process to find the optimal location estimate. In our publication this is referred to as the inner loop.
===EMCCD-GaussianML===
This algorithm implements the maximum likelihood estimator based on a more sophisticated model which in addition includes the stochastic amplification process in an [http[wikipedia://en.wikipedia.org/wiki/Electron-multiplying_CCD multiplying CCD|EMCCD]] camera. We have shown, that it yields more accurate results in situations with low light levels. In our publication this algorithm is referred to as the '''Nested Maximum Likelihood Algorithm'''.
==Pick session options==
[[Image:SessionOptions.png]]
After clicking '''OK''', a new window will open. In this window you can choose a '''σ''' value, which denotes the standard deviation (in pixels) of the Gaussian used to approximate the [http[wikipedia://en.wikipedia.org/wiki/Point_spread_function Point spread function|Point Spread Function]] (PSF) of the tracked objects. If you select '''Automatic σ''', this value is used only as initialization. In this case '''Min''' and '''Max''' are used as bounds for the estimation. These values will be the default values for all new traces you make in this session.
You also can set your quality threshold. Smaller numbers are higher quality, while larger numbers are lower quality but faster.
==Adding objects to track==
To add an object in order to track it, make sure the cross hair icon in the Fiji toolbar is selected and then double click roughly on the object you would like to track in the main window. This new object is represented as a circle. An accordant entry will appear in the table in the control panel representing the objects trace. You can select objects by clicking on them in the control panel or directly in the main window. You can then move them around, using drag and drop or edit them. Multiple objects can be selected by holding '''{{key|Shift''' }} when selecting.
[[Image:CreateDots.png]]
[[Image:MScaleOptions.png]]
The algorithm builds a [http[wikipedia://en.wikipedia.org/wiki/Pyramid_Pyramid %28image_processing28image processing%29 |pyramid]] by repetitively smothing the image with a Gaussian kernel with the standard deviation given in the '''Smoothing σ''' field and than down-sampling it by a factor set in the '''Downscaling''' field. The pyramid's hight (i.e. the number of repetitions) can be set in the '''iterations''' field.
Localization is than first performed on the top level of the pyramid and repeated until its bottom, which is the original image.
=Tips=
* If you want to be able to see the original image data and find your tracking results get in the way, you use the hot-key '''{{key|P''' }} or '''{{key|Ctrl-}}+{{key|P''' }} respectively to hide all overlays (all circles lines and cross-hairs drawn on top of the image).
* If some of the windows appear to bright or to dark use '''View->Adjust Brightness/Contrast''' to correct them.
* You can use '''File->Export images''' to export a sequence of image with the tracking results drawn on top of them. You can use this to create a movie in order to demonstrate your tracking results. In your working directory a new folder named '''movieMain''' will be created and filled with images.
* If you have multichannel data, each channel needs its own session. You can select which sessions are visible by checking their boxes in the '''Visible Sessions''' list. You can use the current session drop down menu to switch between sessions.
* You can zoom into the kymographs by moving the cursor over the kymograph window and holding down '''{{key|Shift'''}}, while using the scroll wheel on the mouse.
* You can use the '''optimize''' button. This will perform the tracking of the selected objects on the single frame you are looking at. You can use this for example with '''Automatic σ''' turned on to determine the size of the target's PSF on a single frame.
=Hot-keys=
There are several hot-keys you can use. You can find the key to press in the menus of the control panel. When the focus is on the control panel you have to press '''{{key|Ctrl''' }} to access hotkeys. When the focus is on one of the other windows this is not necessary.
=File format=
'''<name of image file>_<name of session>_<label of trace>_<id of trace>.trcT'''
The files are created in the working directory. Each file begins with some lines starting with '#'. These lines store information for the tracking program they will be ignored by most programs like matlab [[MATLAB]] or gnuplot potentially used to further analyze the data.
This meta information is followed by columns of data holding the actual tracking results.
The columns have the following meaning:
Bureaucrat, emailconfirmed, incoming, administrator, uploaders
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