A Cell Image Segmentation Algorithm By Simulating Particle Movement

Project report of Computer Vision

Xijiang Miao

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Outline

Introduction Related works The algorithm Potential problems

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Cells under microscope

mitosis

Gap

synthesis apoptosis

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Mission: Tell apart each cells

Knowing the number of cell is helpfulExtract RNA, …Currently, the number of cells is manually

counted. Classifying cells in different phase is

valuable.Check the effect a treatment. Integrate into cell sorting machine.

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Revisit the image

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Voting Based Algorithm

-0.2 -0.1 0.0 0.1 0.2

-0.2

0-0

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-0.1

0-0

.05

0.0

00

.05

0.1

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X axis of image

Inte

nsi

ty

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Experimental Result of Simple Voting

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A recent published vote based algorithm

Yang, Q. et al, Perceptual Organization of Radial Symmetries, Proceedings of (CVPR’04)

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Watershed algorithm

Vincent, L. and Soille, P. Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 13, NO. 6, JUNE 1991

Fig. 2. Building dams at the places where the water coming from two different minima would merge.

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Watershed…

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Watershed in ImageJImageJ: http://rsb.info.nih.gov/ij/

Watershed plugin: Biomedical Imaging Group

http://bigwww.epfl.ch/sage/soft/watershed/

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Think the pixels as particles

Think each pixel is a particle with its mass and velocity.

mAB = mA + mB

conservation of momentum mAvA + mBvB = (mA+mB)vAB

vAB = (mAvA + mBvB)/(mA+mB)

Interpretation of mass and velocity

A B AB

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Think the pixels as particles (2)

Average Mass and momentum Weighted by their mass.

The overall goal is to 1. bring down the effect of noise and 2. accelerate the process.

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The algorithm

1. Initialize the mass and speed.2. Repeat

1. Move particles at their speed and direction2. Once two particles collide together, merge these two

particles and recalculate their speed and mass.3. Adjust the speed and mass according to its neighbors.4. Record their paths

3. Until some terminate condition4. Segment the image according to paths

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Experiment result

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Parameters and Options

Initial parameters Mass

Gradient + ? Speed

Gradient w/ tangent direction Markers

Terminate condition Limited Steps Sand-box Compete

sigma

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Another example shows some problems

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The result

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Problems and workaround

Global color changesNormalize the marginal distribution.

Big blank areaUse different initial mass value

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Question/Question/SuggestionSuggestion