Worm Features
Features
Worms are tracked according to their distance from the pheromone spots and intrinsic features are computed from the image data for each worm.
Name |
Description |
Formula |
Width |
Model of worm Width |
|
Area |
Number of pixels in the worm |
| Ω | |
Minor Length |
Minor axis length of an ellipse with the same area as the worm which has been fit to our worm model |
|
Major Length |
Major axis length of an ellipse with the same area as the worm which has been fit to our worm model |
|
Eccentricity |
Ratio of maximum to minimum distance of the center of mass from the worm’s surface |
|
Orientation |
Angle between the first principal axis of a given worm and the ‘x’ axis |
|
t_start |
Frame number that worm was initially detected |
Ft(0) |
t_end |
Frame number that worm was last detected |
|
t_length |
Total number of frames worm was tracked in a given image sequence |
|
Curvature |
A metric to give an estimate of coiling as a worm behavior |
|
Sum Squared Curvature |
Average Curvature squared, gives an estimate of the worm’s bending energy |
|
Intensity |
The average intensity of the pixels in a worm |
mean( | Ω | ) |
Worm_Velocity |
The average worm speed |
mean([ui,...,un]) i=1,2,...,15 |
Peri_std |
The standard deviation of the worm speed. Gives users insight into irregularities of worm peristaltic progression |
std([ui,...,un]) i=1,2,...,15 |
D_head_std |
Standard deviation of the displacement of the worm’s head |
|
D_tail_std |
Standard deviation of the displacement of the worm’s tail |
|
Reversal Rate |
The frequency of backward progression by the worm’s head |
|
Class |
Each Phenotype is given a separate class from 1-N |
N / A |
Bearing |
The angle between the velocity vector and the spatial vector from the worm’s position to the center of the pheromone spot(chemical gradient) |
|
Instantaneous Turning Rate |
The change in orientation over time |
|