Clinton JungCjung3@jhu.edu

Advisor: Bir BhanuCenter for Research in Intelligent Systems

August 20, 2009

Overview

Background Project Objectives Technical Methods

Otsu’s MethodConnected Components

Algorithm

Results and Analysis Conclusions

Background What are stem cells? Two lines

Embryonic stem cellsAdult stem cells

Five statesAttached to substrateUnattachedDancing, or pre-attachment behaviorDeath, or apoptosisMitosis

Background cont. Stem cell culture conditions

37 degrees CelsiusTreated with cigarette smoke—traditional and

harm reductionMouse embryonic stem cells are used because

they are easier to obtain and manipulateMatragel substrate

Video CaptureUses Biostation HardwareTime-lapse style3.5 hours, 106 still images

Background cont. Stem cells alternate

between five statesDancing always comes

before a cell attachesMitosis only occurs when

cells are unattachedApoptosis is often confused

with dancing behavior

Cell ArrangementsSingle CellColony

Project ObjectivesCrop images for the cells undergoing

dancing and play as video for each cellDevelop image segmentation techniquesFind connected components and compute

featuresQuantify the dancing phenomenon and

change in shape

Example of Video

Video Cropped for Dancing

Dancing Cells

Observations Cells undergoing pre-

attachment behavior (dancing)

• Often have several legs or appendages when dancing. These bulbs are roughly one third or less of the original size of the cell before dancing

• A cell may undergo several cycles of detachment, dancing, attachment

• May affect the state of surrounding cells and influence them in some manner

• Dancing often occurs after mitosis but not necessarily

Cells undergoing pre-attachment behavior (dancing)

• Often have several legs or appendages when dancing. These bulbs are roughly one third or less of the original size of the cell before dancing

• A cell may undergo several cycles of detachment, dancing, attachment

• May affect the state of surrounding cells and influence them in some manner

• Dancing often occurs after mitosis but not necessarily

Cells attached to substrate

• Can be identified by an increase in surface area and exhibit a darker inner intensity value

• When cells attach, they lose their circular shape and instead become noncircular. There were cells that were semi-attached

Cells attached to substrate

• Can be identified by an increase in surface area and exhibit a darker inner intensity value

• When cells attach, they lose their circular shape and instead become noncircular. There were cells that were semi-attached

Technical Methods

Image Segmentation- Process of dividing an image into different segments (sets of pixels). This technique can be used to locate objects and boundaries based on lines, curves, contrasts

BenefitsAutomatically reduce image to simpler one to analyzeIdentify different components and features of an image

Simpler, processed images can then be analyzed

Otsu’s Method Step 1: Input Original Image and convert to grayscale Step 2: Find threshold automatically using histogram. Two groups of

pixels created such that the intra-class variance is minimal and inter-class variance maximal

Step 3: Split image into two classes (binary) based on the threshold value. This final image will have pixel values of either 0 or 255.

Grayscale Value

Num

ber

of

Pix

els

Calculated Threshold Value: 138

Otsu’s Method–Video application

Connected Components Algorithm Step 1: Input Original Image which must be a binary image Step 2: For each pixel, examine surrounding 8 pixels

If the pixel is neighboring, assign label 1 If pixel is not neighboring, assign label 0

Step 3: Continue to check each pixel line by line until entire image is checked, resulting in a matrix of 1’s and 0’s

Step 4: Convert image back to rgb in order to display components in colors.

Connected Components Algorithm—Video Application

Analysis Expand connected components program to count the

number of pixels in a cell undergoing pre-attachment behavior and plot this value over time

Total Number of Pixels vs. Time

Time (Video Frame Number)

Tot

al N

umbe

r of

Pix

els

in

conn

ecte

d co

mpo

nent

fr

ame

Frame 41

Frame 85

Analysis cont. Expand program to compute average grayscale value of a

dancing cell over time and examine the averages and standard deviations of these values over time per frame.

Time (Video Frame Number)

Ave

rage

Gra

ysca

le V

alue

Average Grayscale Value vs. Time

Analysis cont.

Time (Video Frame Number)

Gra

ysca

le S

tand

ard

Dev

iatio

n

Grayscale Standard Deviation vs. Time

Conclusions A preliminary calculation of the changes in pixel count for a cell

undergoing pre-attachment behavior displays no periodic behavior. Pixel count data is also consistent with our hypothesis of a high pixel count for cells in dancing and a low count for a cell in attachment.

The graphical analysis shows that the cells in the dancing, attached, and unattached states have very distinct average grayscale values per frame over the course of the video and can potentially be automatically differentiated using this property

However, the standard deviations of these values for the different stem cell states have a more inconsistent pattern which results in interference with each other

The average and standard deviation values can be combined using pattern recognition techniques

Acknowledgements

I would like to extend much gratitude toDr. Bir Bhanu for his guidance and adviceBenjamin Guan for his willingness to teach Jun Wang for the opportunity this summer to do

researchTalbot Lab—Dr. Prue Talbot and Sabrina Lin for

growing and filming the stem cells Shubham Debna and Lindsay Kulkin for their

collaborationOther members of the BRITE program and C.R.I.S.