Ground truth generation toolset for microscopic human embryo images

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