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Automation of Vessel Counting Jessica DeQuachBoris Babenko Christman LabBelongie Lab
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Heart Attack Death of cells Degradation of ECM Heart Failure Negative left ventricular remodeling Wall thinning Myocardial Infarction and Heart Failure
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LV RV Myocardial Infarction and Heart Failure 6 weeks later….
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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
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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
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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
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Analysis Various methods to determine whether the material is helping the damaged area ▫Function ▫Neovascularization ▫Wall thickness ▫Cellular infiltration MRI
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Neovascularization Formation of new blood vessels with red blood perfusion http://www.omegagenesis.com/html/Research.html
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Animal Studies (weeks) Harvest tissue, freeze in OCT Section the sample to 10 um slices
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Injection Region Identify the injection region Stain five evenly spaced slides through the injection region H&E
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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
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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
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Vessel Quantification Criteria: ▫Within infarct or injection region ▫Has a lumen ▫Average diameter > 10 um
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Vessel Quantification Identify injection region 858_82_16
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Vessel Quantification Identify injection region 854_123_70
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Vessel Quantification Identify injection region 879_192_17
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Vessel Quantification Draw long and short axis
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Vessel Quantification Not all pictures will be that pretty 872_112_21
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Vessel Quantification Vessel long and short axis are averaged Only count vessels > 10 um Hundreds of images, takes hours Only 1 person can quantify
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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
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Matlab Program (designed by Boris et al)
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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
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Computer Vision (Belongie Lab) Pedestrian Detection Reading text “in the wild”
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Computer Vision and Bio Smart Vivarium (Piotr Dollar et al.) Coral Classification (Oscar Beijbom et al.)
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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
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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.
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Contacts Jessica DeQuach jdequach@ucsd.edu Boris Babenko bbabenko@ucsd.edu Anthony Monteforte amontefo@ucsd.edu
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