usage:division_detection

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usage:division_detection [2019/11/15 18:36] – [Model training] pseudomoanerusage:division_detection [2023/07/05 15:36] (current) – [The Division Detection module] pseudomoaner
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 Despite these differences, most of the machinery responsible for performing these assignments remains the same. The layout and usage of the division detection module is therefore very similar to that of the tracking module. For the purposes of conciseness, the below usage guide focuses on the ways in which the two modules differ, rather than providing a complete guide on each aspect of the division detection process. To initialise it, simply press the 'Divisions' button on the home panel. The following GUI should now appear: Despite these differences, most of the machinery responsible for performing these assignments remains the same. The layout and usage of the division detection module is therefore very similar to that of the tracking module. For the purposes of conciseness, the below usage guide focuses on the ways in which the two modules differ, rather than providing a complete guide on each aspect of the division detection process. To initialise it, simply press the 'Divisions' button on the home panel. The following GUI should now appear:
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 +{{ :usage:divisiondetectionv2.png?nolink&800 |}}
  
 ===== Model training ===== ===== Model training =====
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 <note tip> <note tip>
 Because there are no other internal values to compare it to, $R$ is not very useful for determining the ease of division assignment. Instead, it is recommended that the accuracy of division detection be assessed following its completion using the **View divisions** panel and the [[usage:overlays|overlays]] module. Because there are no other internal values to compare it to, $R$ is not very useful for determining the ease of division assignment. Instead, it is recommended that the accuracy of division detection be assessed following its completion using the **View divisions** panel and the [[usage:overlays|overlays]] module.
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 +Division events are much sparser than ordinary frame-frame links between objects, and typically need less feature information for assignment. Prediction of the location of daughter cells in feature space is also more noisy than the prediction of a single object's location in the subsequent frame, meaning some highly variable features can actually detract from the accuracy of division detection if included. It is therefore recommended that you initially try training the division detection model with only the **Position** feature active.
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 ===== Division detection ===== ===== Division detection =====
  
-Selection of the **division threshold** is also very similar to selection of the **adaptive linking threshold** in the tracking module, with the user repeatedly performing a cycle of threshold selection - division detection - validation - threshold update. However, unlike the tracking module, the relative sparseness of division events means that it is practical to perform threshold selection by repeatedly analysing the entire dataset, rather than a single pair of frames. +In contrast to the Tracking module, the Division Detection module does not require the user to manually select a tracking threshold. Instead, the division detection algorithm automates selection of this threshold by iteratively modifying its value such that the resulting lineage structure is maximally connected while still remaining a tree (i.e. contains no loops). In practice, this generally gives a near-optimal balance between assigning true links - correct assignments between mother and daughter cells - and suppressing false links.
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-To perform initial division detection, simply click the **Find divisions!** button. One of two outcomes will then occur: +
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-  - If division detection completed successfully, the division viewer and lineage distribution windows will update. +
-  - If division detection resulted in a lineage with a cycle (i.e. a cell marked as its own ancestor), the following warning notice will appear and the division detection process will be aborted: +
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-{{ :usage:detectionwarning.png?nolink&400 |}} +
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-In the case of scenario (2), the **division threshold** should be reduced until the warning notice ceases to appear.+
  
 +Once training has completed, it is therefore sufficient to simply press the **Find divisions!** button to launch this iterative algorithm and generate your lineage.
 ==== Validation ==== ==== Validation ====
  
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 ===== Video demonstration ===== ===== Video demonstration =====
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 +{{ youtube>e6IF4OKy3v0?large }}
  • usage/division_detection.1573842988.txt.gz
  • Last modified: 2019/11/15 18:36
  • by pseudomoaner