You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardexpand all lines: _pages/plugins/snt/sholl.md
+7-7
Original file line number
Diff line number
Diff line change
@@ -41,13 +41,13 @@ After [installing SNT](/plugins/snt/#installation), Sholl commands can be access
41
41
{% include gallery align="center" content=
42
42
"
43
43
/media/plugins/snt/sholl-analysis-outputs.png | Overview of outputs: Linear and log-log profile (Sholl decay calculation), detailed and summary tables. ‘Traditional’ plots are obtained by disabling curve-fitting altogether
44
-
/media/plugins/bitmapsholl-ca1mask.png | [Skeletonized](/plugins/skeletonize3d) hippocampal CA1 cell[^8] in which apical and basal dendrites have been analyzed [separately](#ca1-cell-plot) and [color coded](#output-options) according to their Sholl profile. Warmer hues indicate higher number of Intersections (*N*). [Critical radius](#critical-radius) (*r<sub>c</sub>*) and [Mean value](#mean-value-of-function) (*N<sub>av</sub>*) are indicated.
45
-
/media/plugins/bitmapsholl-ca1compartment.png | Linear plot for the same CA1 cell[^8]. Using the soma as center, image was sampled twice using [hemishells](#hemishells) in order to segregate apical from basal dendrites. For clarity, distances for basal branches were assigned negative values and arbor overlaid (in green) over the profile.
46
-
/media/plugins/combineshollprofiles.png | *Combine Sholl Profiles...* aggregates individual profiles into a single plot, obtaining the average profile for groups of cells [[use case](https://forum.image.sc/t/sholl-merging-profiles-with-different-radii/54144/13)]
44
+
/media/plugins/snt/bitmapsholl-ca1mask.png | [Skeletonized](/plugins/skeletonize3d) hippocampal CA1 cell[^8] in which apical and basal dendrites have been analyzed [separately](#ca1-cell-plot) and [color coded](#output-options) according to their Sholl profile. Warmer hues indicate higher number of Intersections (*N*). [Critical radius](#critical-radius) (*r<sub>c</sub>*) and [Mean value](#mean-value-of-function) (*N<sub>av</sub>*) are indicated.
45
+
/media/plugins/snt/bitmapsholl-ca1compartment.png | Linear plot for the same CA1 cell[^8]. Using the soma as center, image was sampled twice using [hemishells](#hemishells) in order to segregate apical from basal dendrites. For clarity, distances for basal branches were assigned negative values and arbor overlaid (in green) over the profile.
46
+
/media/plugins/snt/combineshollprofiles.png | *Combine Sholl Profiles...* aggregates individual profiles into a single plot, obtaining the average profile for groups of cells [[use case](https://forum.image.sc/t/sholl-merging-profiles-with-different-radii/54144/13)]
47
47
/media/plugins/snt/sholl-group-statistics.png | Statistics for [groups of cells](/plugins/snt/analysis#comparing-reconstructions)[[use case](https://forum.image.sc/t/sholl-analysis-with-snt-one-graph-for-two-groups/82471/2)]
48
-
/media/plugins/animatedpolyfit.gif | Sampled data can be fitted to polynomials of varying degree (animation created using [BAR](/plugins/bar))
48
+
/media/plugins/snt/animatedpolyfit.gif | Sampled data can be fitted to polynomials of varying degree (animation created using [BAR](/plugins/bar))
49
49
/media/plugins/snt/sholl-convex-hull.png | Scripting allows for arbitrary focal points, in this case the centroid of the neuron's convex hull (*Convex Hull as Center* template script)
50
-
/media/plugins/shollresultasrois.png | Intersection points and sampling shells can be retrieved as ROIs. Intersection points are placed at edges of detected clusters of foreground pixels, not their center.
50
+
/media/plugins/snt/shollresultasrois.png | Intersection points and sampling shells can be retrieved as ROIs. Intersection points are placed at edges of detected clusters of foreground pixels, not their center.
51
51
/media/plugins/snt/sholl-rasterized-shells.png | Using Sholl to measure the distribution of image objects (_Sholl Rasterize Shells_ template script) [[use case](https://forum.image.sc/t/measuring-distribution-of-object-diameters-in-different-stripes-using-sholl-plugin/51087)]
52
52
/media/plugins/snt/snt-sholl-integrate-density-profiles.png | Not only neurons: Integrated-density profiles can be used to obtain radial maps of fluorescent markers.
53
53
"
@@ -74,7 +74,7 @@ The center of analysis can be specified using one of three possibilities:
74
74
75
75
3. Multipoint selection:A Multi-point selection (multipoint counter) in which the first point marks the center of analysis while the remaining points mark (count) the number of primary branches required for the calculation of [ramification indices](#schoenen-sampled)). Suitable for cases in which [inference from starting radius](#primary-branches) is not effective.
76
76
77
-
{% include img align="center" name="sholl plots" src="/media/plugins/shollanalysisstartuprois.png" %}
77
+
{% include img align="center" name="sholl plots" src="/media/plugins/snt/shollanalysisstartuprois.png" %}
78
78
79
79
Three types of ROIs expected by the plugin when analyzing images directly. <b>Left</b>: Line defining center of analysis (focal point), hemisphere restriction and ending radius. <b>Middle</b>: Single point defining center of analysis. <b>Right</b>: Multi-point selection in which the first point defines the focal point while the remaining points (2 to 5) serve as counters for primary neurites.
80
80
@@ -249,7 +249,7 @@ Detailed control over polynomial fitting is controlled by the options in the *Op
249
249
250
250
# Sholl Plots
251
251
252
-
{% include img align="center" name="sholl plots" src="/media/plugins/shollplots.png" %}
252
+
{% include img align="center" name="sholl plots" src="/media/plugins/snt/shollplots.png" %}
253
253
254
254
***Linear*, *Linear-norm*, *Semi-log* and *Log-log* profiles for the ddaC cell ({% include bc path='File|Open Samples|ddaC Neuron'%}), version 3.0**. Most of the retrieved [metrics](#metrics-based-on-fitted-data) are automatically highlighted by the plugin. *Linear profile*: [Mean value](#mean-value-of-function) (horizontal grid line) and [Centroid](#centroid) (colored mark). Logarithmic profiles: The [Sholl regression coefficient](#sholl-decay) (also known as Sholl decay) can be retrieved by linear regression using either the full range of data (blue line) or data within percentiles 10–90 (red line). For this particular cell type, the Semi-log method is more [informative](#dratio) when compared to the Log-log method.
There are several entry points to Strahler Analysis in SNT. You can find those in the _Neuroanatomy Shortcuts_ panel ({% include bc path='Plugins|Neuroanatomy|'%} or "SNT" icon in Fiji's toolbar):
17
17
<br/>
18
18
<ol>
19
-
<li><i>Strahler Analysis (Image)...</i> Direct parsing of skeletonized images, bypassing tracing</li>
20
-
<li><i>Strahler Analysis (Tracings)...</i> Parsing of traced structures</li>
19
+
<li><i>Strahler Analysis (Image)...</i> Direct parsing of skeletonized images, bypassing tracing (described on this page)</li>
20
+
<li><i>Strahler Analysis (Tracings)...</i> Parsing of traced structures (described in
<li><i>Strahler Analysis Scripts</i> Batch processing of files</li>
22
23
</ol>
23
-
This documentation page is mainly focused on _Strahler Analysis (Image)..._.
24
24
{% endcapture %}
25
25
{% include notice icon="info" content=strahler %}
26
26
@@ -29,7 +29,7 @@ While _Strahler Analysis (Image)..._ remains a functional workflow, you may find
29
29
{% endcapture %}
30
30
{% include notice icon="warning" background-color="#fffbeb" content=strahler %}
31
31
32
-
{% include img align="right" src="/media/plugins/strahler-classification-example.png" caption="Strahler classification"%}
32
+
{% include img align="right" src="/media/plugins/snt/strahler-classification-example.png" caption="Strahler classification"%}
33
33
Strahler numbering is a numerical procedure that summarizes the branching complexity of mathematical trees. It is described in detail [here](./analysis#strahler-analysis).
34
34
35
35
## Description
@@ -47,7 +47,7 @@ Strahler numbering is a numerical procedure that summarizes the branching comple
47
47
**Infer root end-points from rectangular ROI**: This option is only available when a rectangular ROI is present. It is described in [root detection](#root-detection).
48
48
49
49
<spanid="strahler-animation">
50
-
{% include img align="right" width="300" name="Strahler Analysis by iterative elimination of end-point branches" src="/media/plugins/strahleranimation.gif" caption="Direct analysis of images occurs through progressive pruning of terminal branches, *iterative tree simplification*, a method that requires detecting all terminal branches (i.e., branches that contain an end-point) and all the degree-one paths leading to them." %}
50
+
{% include img align="right" width="300" name="Strahler Analysis by iterative elimination of end-point branches" src="/media/plugins/snt/strahleranimation.gif" caption="Direct analysis of images occurs through progressive pruning of terminal branches, *iterative tree simplification*, a method that requires detecting all terminal branches (i.e., branches that contain an end-point) and all the degree-one paths leading to them." %}
51
51
52
52
**Ignore single-point arbors (Isolated pixels)** Elimination of end-point branches may give rise to single point arbors. Such 'debris' have 1 end-point but no slab branches or junctions. When this option is selected, single-point arbors will be discarded on each iteration. If deselected, the total number of end-points may be overestimated.
53
53
@@ -66,7 +66,7 @@ Strahler numbering is a numerical procedure that summarizes the branching comple
66
66
67
67
## Root Detection
68
68
69
-
{% include img align="right" width="600px" src="/media/plugins/strahler-rootprotection.png" caption="**Left**: Arbor with rectangular ROI containing root. **Middle**: Analysis ignores ROI. Root-branch is interpreted as any other terminal-branch and the resulting classification is inaccurate. **Right**: Analysis takes ROI into account and infers that the end-point contained by the ROI is the root of the structure. Root branch is excluded from the iteration and the classification is accurate." %}
69
+
{% include img align="right" width="600px" src="/media/plugins/snt/strahler-rootprotection.png" caption="**Left**: Arbor with rectangular ROI containing root. **Middle**: Analysis ignores ROI. Root-branch is interpreted as any other terminal-branch and the resulting classification is inaccurate. **Right**: Analysis takes ROI into account and infers that the end-point contained by the ROI is the root of the structure. Root branch is excluded from the iteration and the classification is accurate." %}
70
70
71
71
The problem with undiscriminated elimination of terminal branches is that a root-branch containing an end-point is always eliminated on the first iteration step. In order to protect root branches from elimination, *Strahler Analysis* needs to know where root branches are located. Root-detection is implemented by means of a rectangular ROI containing the root branch and by activating the *Infer root end-points from rectangular ROI* option. Here is an example:
0 commit comments