PhD Proposal by Meredith Fay

Event Details
  • Date/Time:
    • Tuesday March 8, 2022
      10:00 am - 12:00 pm
  • Location: Atlanta, GA; REMOTE
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Summaries

Summary Sentence: Automated precision computational image analysis and applied machine learning for experimental and clinical hematology applications

Full Summary: No summary paragraph submitted.

Meredith Fay
BME PhD Proposal Presentation

Date:2022-03-08
Time: 10:00 - 11:00
Location / Meeting Link: https://emory.zoom.us/j/95615458895

Committee Members:
Wilbur Lam, MD, PhD (advisor) Eva Dyer, PhD David Gutman, MD, PhD Cassie Mitchell, PhD Russell Ware, MD, PhD

Title: Automated precision computational image analysis and applied machine learning for experimental and clinical hematology applications

Abstract: Hematology, the study of blood and blood disorders, is a broad field of science and medicine spanning research at the cellular level to clinical treatment for patient well-being. Imaging at all scales, ranging from microscopy to diagnostic scans of the body, represents one of the best methods to investigate salient features of fundamental biology and disease. The imaging data produced is information-rich, but hematology presents with specific issues that hinder analysis, including diverse cell populations, an emphasis on fluid flow, and importance of spatial relationships. Computational pipelines for image processing coupled with applied machine learning interpretation represent a solution by providing methods that balance high-throughput automation with precise, quantitative results. To this end, this work aims to develop a series of computational workflows to provide greater resolution in hematology research such that more detailed experimental conclusions can be made from imaging data. In aim 1, the open source, standalone software iCLOTS (interactive cellular assay labeled observation and tracking software) will be developed and utilized to draw novel conclusions about research at the cellular level, including in patient clinical samples. This software will be distributed to the greater hematology community. Aim 2 will explore features of disease risk and progression in magnetic resonance imaging of the cerebrovasculature of pediatric sickle cell disease patients. The results of this work provide new methodologies for applied image processing and machine learning in hematology research, and may contribute to precision medicine efforts.

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Phd proposal
Status
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Feb 23, 2022 - 9:17am
  • Last Updated: Feb 23, 2022 - 9:17am