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Date:  Fri, December 04, 2020
Time:  3:00pm - 4:00pm
Location:  online, please contact Dr. Ohta for details
Speaker:  Meenakshi Vohra, MS Candidate, Advisor Dr. Ohta

In-vitro fertilization (IVF) has become the most common method to treat infertility, despite being a complex and expensive process. Determining embryo health and viability at the time of transfer is a crucial process that influences the success rate of IVF. Current embryo grading system to assess embryo viability is subjective and time consuming. Embryologists determine embryo grade based upon visual attributes and grading is often subject to interobserver variance. Embryo misidentification may lead to failure of embryo implant which raises the need of multiple IVF cycles, and causes increased cost and emotional distress. We propose two techniques to provide a more quantitative approach for embryo viability assessment. First approach is a deep learning-based embryo image analysis technique used to calculate the growth rate of embryo over time. Embryos with a rapid growth rate are considered to be viable for a successful implantation. Second approach is to measure cellular impedance, which correlates to the growth rate and health of the embryo over time. A cell system is analogous to an electrical circuit and dielectric parameters of cells can be measured by electrical impedance. Impedance spectroscopy provides a non-invasive method to observe net change in impedance due to cell division and increase in net mass of embryo.