Vasculature Morphology Description¶
File Format¶
The file contains a root /, with three HDF5 Datasets that describe the Vasculature morphology. The /properties group contains datasets that describe additional information about the vasculature at the point, segment and section level. For example, leakiness would apply to the segment level.
The datasets rooted in / are:
- points:
A 4 column data set composed of 32 bit floating point numbers representing morphology points, which are the position and diameter at a cross section. The first three columns represent the X, Y, and Z positions and the last column represents the diameter, all in micrometers. Implicit in the points dataset is an index, starting at 0, of each point.
- structure:
This dataset describes all the sections of the vasculature. It is composed of 2 columns: start offset and type. Implicit in the structure dataset is an index, starting at 0, of each section.
start offset: The implicit index in the points dataset of the first point of the section. The points in this section go until the start offset defined by the next row in the structure dataset, except for the last term:section in the file, then it runs until the end of the points dataset.
type: The type of process for this section. The integer can be interpreted as follows:
1: vein, 2: artery, 3: venule, 4: arteriole0, 5: venous-capillary, 6: arterial-capillary, 7: transitional
- connectivity:
This dataset describes the connectivity between all the sections described in the structure dataset. It has 2 columns which refer to the implicit index of the sections which are connected to each other. It implies that the last point in the section in column 1 is the same as the first point in the section in column 2 (duplicating points at the boundary). This dataset is sorted on the first column, and has a secondary sort on the second column.
The optional group /properties stores additional datasets under one of the following groups:
/properties/point_level/ for properties attached to a point. The datasets of this group are composed of 2 columns: point index and value. point index is a column of integers that relates to the index in the /points dataset and value is a column of float storing the property value for this point. An example of point level property could be the cross section surface at each point.
/properties/segment_level/ for properties attached to a segment. The datasets are composed of 2 columns: segment index and value. segment index is a column of integers that relates to the index in the /points dataset, but is interpreted as the segment between the point at the point index, and the one following it. value is a column of float storing the property value for this segment. An example of segment level property could be the leakiness.
/properties/section_level/ for properties attached to a section. The datasets are composed of 2 columns: section index and value. section index is a column of integers that relates to the index in the /structure dataset and value is a column of float storing the property value for this section. An example of section level property could be a section type.
Geometric interpretation¶
The additional connectivity dataset is included because the vasculature is represented as a graph, unlike the neuron which is a tree. Thus, each section can have multiple parents and children. The directionality of the graph is decided by the columns in the connectivity dataset (column 1 to column 2).
Example¶
For example, a simple morphology with 1 branching point would be expressed as:
points structure:
i
X
Y
Z
D
0
0
2
0
0
1
0
1
0
0
2
0
0
0
0
3
0
0
0
0
4
-1
0
0
0
5
-2
0
0
2
6
0
0
0
2
7
1
0
0
2
8
2
0
0
1
structure dataset, where SO is start offset and TYP is Type (i is the implicit index):
i
SO
TYP
0
0
1
1
3
1
2
6
1
connectivity dataset where S1 is section1 and S2 is section2:
S1
S2
0
1
0
2
Another example, using a more complex morphology (the shared points in black are duplicating):
points structure (note the implicit i index):
i
X
Y
Z
D
0
-2
3
0
0
1
-2
2
0
0
2
-2
2
0
0
3
-3
2
0
0
4
-2
2
0
0
5
-2
1
0
2
6
-2
0
0
2
7
-2
0
0
2
8
-2
-1
0
1
9
-2
0
0
2
10
-1
0
0
2
11
0
0
0
2
12
0
0
0
2
13
0
1
0
2
14
1
1
0
1
15
2
1
0
1
16
2
0
0
1.5
17
0
0
0
2
18
0
-1
0
2
19
1
-1
0
2
20
2
-1
0
0
21
2
0
0
1.5
22
2
0
0
1.5
23
3
0
0
0
24
4
0
0
2
25
4
0
0
2
26
4
-1
0
2
27
4
0
0
1
28
4
1
0
1
29
4
2
0
1
30
4
2
0
1
31
4
3
0
2
32
4
2
0
2
33
5
2
0
1
structure dataset, where SO is start offset and TYP is Type (i is the implicit index):
i
SO
TYP
0
0
1
1
2
1
2
4
1
3
7
1
4
9
3
5
12
7
6
17
7
7
22
4
8
25
2
9
27
2
10
30
2
11
32
2
connectivity dataset where S1 is section1 and S2 is section2:
S1
S2
0
1
0
2
2
3
2
4
4
5
4
6
5
7
6
7
7
8
7
9
9
10
9
11