Automation of Vessel Counting

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5 Νοε 2013 (πριν από 3 χρόνια και 5 μήνες)

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Automation of Vessel Counting

Jessica DeQuach


Boris
Babenko

Christman Lab


Belongie

Lab

Heart Attack

Death of cells

Degradation of ECM

Heart Failure

Negative left ventricular remodeling

Wall thinning

Myocardial Infarction and

Heart Failure

LV

RV

Myocardial Infarction and

Heart Failure

6 weeks later….

Research With Injectable Biomaterials


Want to develop an injectable biomaterial to
help regenerate/salvage damaged tissue


Skeletal muscle


Heart



Injectable materials


Minimally invasive (less surgery)


Contours to shape of wound

Animal Surgeries


Surgeries performed by Pam
or Rebecca


Animals anesthetized


First surgery: injury (infarct,
ischemia)


Second surgery: injection, ~1
week later


Animals kept in
vivarium

until time point

http://kentsimmons.uwinnipeg.ca/16cm05/16labman05/lb8pg12.htm

Animal Studies (weeks to months)


To get statistical significance, usually need
n

>= 4
per group


Need to account for animal death, and variability



Need to compare to a control group



Note* need to include different experimental groups
on each day

Analysis


Various methods to determine whether the
material is helping the damaged area


Function



Neovascularization


Wall thickness


Cellular infiltration

MRI

Neovascularization


Formation of new blood vessels with red blood
perfusion

http://
www.omegagenesis.com/html/Research.html

Animal Studies (weeks)


Harvest tissue, freeze in OCT


Section the sample to 10 um slices

Injection Region


Identify the injection region


Stain five evenly spaced slides through
the injection region

H&E

Vessel Stain


Antibody stain for vessels


Antibodies can identify
specific proteins



Smooth muscle actin (red)


Stains for smooth muscle
cells



Isolectin

(green)


Stains for endothelial cells

http://www.siumed.edu/~dking2/crr/cvguide.htm

Animal Studies (weeks)


Take images of vessel stain



Need to quantify!


The annotator should be trained to be
consistent


Blinded so that no bias


Only one person can quantify a set of data

Vessel Quantification


Criteria:


Within infarct or injection region


Has a lumen


Average diameter > 10 um


Vessel Quantification

Identify injection region

858_82_16

Vessel Quantification

Identify injection region

854_123_70

Vessel Quantification

Identify injection region

879_192_17

Vessel Quantification

Draw long and short axis

Vessel Quantification

Not all pictures will be that pretty

872_112_21

Vessel Quantification


Vessel long and short axis are averaged


Only count vessels > 10 um



Hundreds of images, takes hours



Only 1 person can quantify

Automation


Automation of the process would be beneficial


Need to determine “human error”



This is where you come in!



Quantify 150 images of skeletal muscle and heart.
Will need MATLAB, can do this from home


Need data from several people

Matlab

Program (designed by Boris et al)

Computer Vision (
Belongie

Lab)


Combination of Artificial Intelligence, Machine
Learning, Image Processing, 3D Geometry (and
sometimes Cognitive Science)


Examples in Industry:


Face detection (i.e. most P&S cameras today)


Google Goggles /
TinEye

Computer Vision (
Belongie

Lab)


Pedestrian Detection





Reading text “in the wild”

Computer Vision and Bio


Smart
Vivarium

(
Piotr

Dollar et al.)





Coral Classification
(Oscar
Beijbom

et al.)

Training


We will first label 10 images together


Then you will label 10 image on your own


After someone double checks the answer you will
be okay to quantify on your own

Commitment


Quantify 150 images of cardiac and skeletal
muscle, only in the Region of Interest (ROI)


The
Matlab

program will automatically save
your data even if it crashes


Can pace yourself, measure 10 or so a day



Opportunity to participate in Bioengineering
Research, and can come to lab meetings, etc.

Contacts


Jessica DeQuach


jdequach@ucsd.edu



Boris
Babenko


bbabenko@ucsd.edu



Anthony
Monteforte


amontefo@ucsd.edu