Transcript Quantifying Dancing Stem Cells - Bourns College of Engineering

Understanding and Quantifying the Dancing Behavior of Stem Cells Before Attachment
1
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Clinton Y. Jung and Dr. Bir Bhanu , Department of Electrical Engineering
1. Biomedical Engineering, Johns Hopkins University, MD 21218, USA
2. Center for Research in Intelligent Systems, University of California, Riverside, CA 92521, USA
Grayscale Image
Histogram
Total Number of Pixels vs. Time
2000
1800
Binary
Image
Connected
Components
Image
Total Number of Pixels
-We are supplied videos captured in time-lapse fashion. The
videos are in .avi format and cover 3.5 hours over the course of
106 still images
-All programming and image segmentation techniques are
carried out in MATLAB code
Example of a single frame of video
1600
1400
1200
1000
800
600
400
200
0
Unattached
Cell
1
Number
of Pixels
5
Average Grayscale Value vs. Time
Grayscale Value
180
Calculated Threshold Value: 162
160
Attached
Cell
Grayscale Value
140
120
100
80
Dancing Cells
60
Attached Cell
40
Apoptotic Cell
20
Calculated Threshold Value: 155
0
1
5
OBJECTIVES
-First, apply Otsu’s Method to separate the image
into two groups of pixels such that the intra-class
variance is minimal and inter-class variance
maximal
-Next, apply connected components algorithm,
another image segmentation method.
-Expand connected components program to count
the number of pixels in a cell undergoing preattachment behavior and plot this value over time
-Also 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.
-Compare calculations for different stem cell
stages
Pre-attachment
Behavior
Grayscale Standard Deviation vs. Time
70
Grayscale Value
Calculated Threshold Value: 138
Otsu’s Method
Step 1: Input Original Image and convert to grayscale
Step 2: Find threshold automatically using histogram
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.
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.
Acknowledgements
Jun Wang, Benjamin Guan, Dr. Prue Talbot, Shawn Fonteno, Sabrina Lin, Giovanni
Denina, National Science Foundation
Grayscale Standard Deviation
TECHNICAL METHODS
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Time (Video Frame Number)
Number
of Pixels
-Crop images for the cells undergoing dancing and
play as video for each cell
-Perform segmentation techniques
-Compute features
-Quantify the dancing phenomenon and change in
shape
9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101105
Time (Video Frame Number)
Average Grayscale Value
Stem cells have proven themselves to be a
promising frontier of biomedical research. They
have an ability to develop into different cell types
in the body especially when the human body is
still in its earliest stages of life and growth. As
the body ages, stem cells continue to serve in
different tissues and divide to replenish other
cells. What is incredible about stem cells is the
fact that they can become other types of cells in
order to perform a specialized function. As we
continue to observe stem cells and try to
understand their behaviors in order to more fully
tap into their potential, learning about the
different states of the stem cells is of significant
importance .
In this project, stem cells are hypothesized to
be in one of five states—attached, non-attached,
dancing, death, and mitosis. We focus on
investigating the dancing, or pre-attachment,
behavior of stem cells. This is a new, previously
unobserved phenomenon. In this state, the cell
loses its defined border and instead has several
small bulbs attached to it.
ANALYSIS
DATA /IMAGE SEGMENTATION PROCESS
Number
of Pixels
INTRODUCTION
60
50
40
30
Dancing Cells
20
Attached Cell
10
Apoptotic Cell
0
1
5
9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97 101105
Time (Video Frame Number)
CONCLUSIONS
-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
-A preliminary calculation of the changes in pixel sizes for
a cell undergoing pre-attachment behavior displays no
periodic behavior