IDL 102 (Particle Tracking)

Our MO• Convert Image DV -> gdf

– Do not byte-scale– Also, do byte scale (after conversion)

• Find dots in each frame– “Clean” image– Find all candidate dots– Refine dots set

• Link dots frame-to-frame to get trajectories– How far are we willing to look for a particle?– How about gaps?– How about blinky, random noise?

Conversion isn’t futile• Images are acquired at 16bit (0 -> 216=65536)• Images have to be displayed at 8bit (0 ->

28=256)

HOT pixels are bad

DEAD pixels are bad too

Pre-tracking• Find dots in each frame– “Clean” image– Find all candidate dots– Refine dots set

Cleaning the image: band-passing with bpass.pro

These could be candidates

Select them with a reasonable masscut

0 1 2 3 4 5 0 3 4 5 6 7 0 1 8 9 10 11 12 0 2 13 14 15 16 17 0 3 18 19 20 21 22 0 4 23 24 25 26 27 2 5 28 29 30 31 32 2 6 33 34 35 36 37 3 7 38 39 40 41 42 4 8 43 44 45 46 47 5 9 48 49 50 51 52 5 10 53 54 55 56 57 5 11 58 59 60 61 62 5 12 63 64 65 66 67 6 13 68 69 70 71 72 12 14 73 74 75 76 77 12

X Y Mass Radius Eccentricity Time

You need to refine them using reasonable criteria

Criteria• X, Y can be used to clip edges, where things usually go

wrong• “Mass” is total integrated brightness in each blob• Radius of gyration is a measure of size that makes dimmer

pixels count less• Eccentricity:

– 0: a perfect disk– 1: a perfect line segment

• Use eclip.pro, where(), or edgeclip.pro to refine ranges of these criteria

A few things you can use to evaluate your pretracking:

• Say your pretracked data is in ‘pt’• Overview:– ptexplore, pt

• Number of particles at each frame (bleaching?)– plot_hist, pt[5,*], bin=1

• Bias towards integer pixel positions– plot_hist, pt[0:1,*] mod 1, bin=.05

Now track them!• User defined params for tracking:– Distance to look for same particle frame-to-

frame• This must me less than interparticle distance in each

frame– Number of frames a particle is allowed to

disappear• This must be less than time it takes for two particles

to switch position– Shortest trajectory you consider real• This is a toughie. But setting this to something >0

helps get rid of artifacts that blink

Check tracking with• P(dx, dt=1)

Check with IDover2D

Analysis

AnalyzeMean squared displacement (MSD)


t=1 2

3

4

56

97

8

1012

15 14

13

11


• Measure all displacements that are Dt = 1 frame apart• Square them• Average them• Average over other particles if desired and “allowed”

t=1 2

3

4

56

97

8

1012

15 14

13

11

Dt (frames)M

SD(m

m2 )

1 13


• Measure all displacements that are Dt = 1 frame apart• Square them• Average them• Average over other particles if desired and “allowed”

t=1 2

3

4

56

97

8

1012

15 14

13

11

Dt (frames)M

SD(m

m2 )

1 2 13

• Then do it for Dt = 2 frames and so on

Says Einstein!

y =

m xx

Dt (frames)

MSD

(mm

2 )

m= D1

m= D2

constant in biology

A Yes/No test for diffusion(What’s this about logs and slopes of 1?)

A Yes/No test for diffusion(What’s this about logs and slopes of 1?)

y =

m xxc +

1

1

2

Ballistic motion(that of projectiles)

Constant velocity gives a slope 2 on a log-log plot

What about this mess of an MSD plot?

IDL 102 (Particle Tracking)

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