Ground truth generation toolset for microscopic human embryo images

在过去的40年里，由于生育延迟，生育治疗的使用急剧增加。不幸的是，女性的生殖能力在生命的第二和第三个十年从高峰开始下降，到40岁时，生育能力显著下降，流产的几率很高。辅助生殖技术包括生育治疗，包括在体外处理卵子和胚胎。体外受精（IVF）是最常见的生育治疗之一，其中卵巢被过度刺激以产生多个卵子用于外部受精。受精卵（胚胎）被孵育，直到它们达到囊胚期（受精后约5天），然后被选择用于植入。在培养过程中，通过基于内在形态结构分配等级以反映囊胚的质量来评价最佳候选物。能够量化为什么某些囊胚具有更高的植入潜力将有助于研究人员提高成功率，并最大限度地减少由于移植多个胚胎而导致的多胞胎的机会。因此，准确、可靠地鉴定和测定各种胚胎成分和发育参数是十分必要的。该研究项目的主要重点是创建半自动化技术，可以帮助和促进专家胚胎学家识别和标记感兴趣的区域。更具体地说，我们建议开发一个图像处理工具集，可以自动处理一些更繁琐的部分地面真相识别，并允许专家以最小的手动干预/努力改善结果在2D显微图像的人类胚胎。

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.