Using Imaging Tools To Track The Phenotype Changes To Capture Potential Genotype Changes | 19517
Journal of Molecular and Genetic Medicine
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Monitoring phenotype changes and linking them with potential genetic mutations has becoming an important tool for
building disease models and developing biomarkers and disease diagnosis methods. Phenotypic analysis of tissue
changes demands automated, high-throughput image analysis tools in communities such as human health informatics and
mammalian genetic communities. Image alignment is an essential step to remove image distortions caused by experiment
subjects movements and device system noise. Analyzing the aligned images is also important for comparing tissue changes over
time. We will discuss two image alignment technologies here. First, technological breakthroughs in the fields of electronics and
wireless communication will allow real-time monitoring of the human body movements and vital signals. Putting landmarks
onto the captured human tissue models for further statistical shape analysis is a powerful tool to find the covariance of the
organism?s phenotype changes. Second, intensity based image alignment will allow us to remove image distortions caused by
tissue movements and capture device background noise. For example, we can use the optical coherence tomography technology
(OCT) to capture retina images of a large amount of experimental subjects. Despite the high resolution and noninvasive
imaging, OCT suffers poor penetration depth through tissues and speckle noise. Aligning the repeatedly captured images will
allow us to average the intensities to create shaper images to reveal more detailed tissue structures and changes.
Mei Xiao has completed her PhD at the age of 32 years from UMass/Boston and postdoctoral studies from University of Calgary. She is a senior software engineer
of the Jackson Laboratory, a premier mammalian genetics research organization. She has published 15 papers in reputed journals and conferences.
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