installers

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2026-10-16T11:30:12+00:00

Installers On this page, you can find the platform-specific installers for the current stand-alone version of FAST (v2.1). Please select one of the options below: Windows (v2.2.1) Linux (v2.1) Compiled in Ubuntu v20.04 macOS (v2.1)

installation

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2026-10-16T10:57:08+00:00

Installation As FAST has been developed in Matlab, you can download its unencrypted .m and .fig files and run it directly from Matlab's command line. This option allows you to make direct modifications to FAST's code, necessary for some advanced capabilities. It also allows use of FAST's

start

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2026-10-16T10:56:38+00:00

FAST, the Feature-Assisted Segmenter/Tracker Have you struggled with automated measurement of the movement of many closely-packed individuals? The Durham lab's tracking system, FAST, may be the answer to your problems. Its features include: * A user-friendly

publications_using_fast

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2026-07-30T15:54:39+00:00

Publications using FAST * Granato, E. T, Foster, K. R, The evolution of mass cell suicide in bacterial warfare, Curr. Bio. (2020) 30 pp 1-8, doi: * Meacock, O. J, Doostmohammadi, A, Foster, K. R, Yeomans, J. M, Durham, W. M, Bacteria solve the problem of crowding by moving slowly

contact_information - [Further questions? Want to get involved?]

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2026-07-30T15:48:31+00:00

Contact information How to cite FAST If you find FAST useful, please include the following citation in any publications you produce using it: * Meacock, O. J, Durham, W. M, Tracking bacteria at high density with FAST, the Feature-Assisted Segmenter/Tracker

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2023-10-10T10:19:07+00:00

division_detection - [The Division Detection module]

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2023-07-05T14:36:33+00:00

The Division Detection module In the tracking module, we sought the optimal way to integrate feature information to pair detected objects between frames. Division detection is conceptually similar, but instead of linking one object to another we wish to optimally use feature information to pair each mother cell with two daughter cells. This is achieved using a similar algorithm to the tracking module, with a few key modifications:$R$$R$

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2023-07-05T14:36:09+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2023-03-09T16:29:22+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2022-07-18T22:32:38+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-11-27T13:17:18+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-11-27T13:07:27+00:00

remhalosdemo.png

pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-29T09:50:29+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-29T09:45:51+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-29T08:58:53+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-26T19:53:05+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-26T19:52:52+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-26T19:52:39+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-26T19:51:32+00:00

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pseudomoaner (pseudomoaner@undisclosed.example.com) — 2021-10-26T19:51:07+00:00