Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).

The use of fertility treatments has increased dramatically in the last 4 decades as a result of delayedx000D
childbearing. Unfortunately, female reproductive capacity declines from a peak in the 2nd and 3rd decades ofx000D
life so that by the age of 40 there is a significant reduction in fertility with a high chance of miscarriage.x000D
Assisted Reproductive Technology includes fertility treatments that involve handling eggs and embryos outsidex000D
the body. In Vitro Fertilization (IVF) is one of the most common fertility treatments in which ovaries are hyperx000D
stimulated to produce multiple eggs for external fertilization. The fertilized eggs (embryos) are incubated untilx000D
they reach the blastocyst stage (about 5 days after fertilization) and then are chosen for implantation. Optimalx000D
candidates are evaluated during the incubation process by assigning grades to reflect the quality of blastocystsx000D
based on intrinsic morphological structures. Being able to quantify why certain blastocysts have higherx000D
implantation potentials will help researchers to increase success rates and minimize the chances of multiplex000D
births due to transferring multiple embryos. Therefore, it is essential to identify and measure various embryox000D
components and developmental parameters in a reliable and accurate manner. The main focus of this researchx000D
project is to create semi-automated technologies that can assist and facilitate expert embryologists to identifyx000D
and mark regions of interest in a high pace. More specifically, we propose developing an image processingx000D
toolset that can automatically process some of the more tedious parts of ground truth identification and allowx000D
expert to improve results with the minimal manual intervention/effort in 2D microscopic images of humanx000D
embryos.