Classification of Embryos Using Microscopic Pictures

This study focuses on classifying the microscopic images of embryo by using DL neural networks including Mobilenet that captures the crucial patterns in the images and classify whether the Embryo is Good or Bad for In-Vitro Fertilization (IVF). The paper introduces an enhanced DL-based approach for recognizing patterns within images and adjusting each input image to meet specified normalization criteria, as normalization plays a crucial role in ensuring consistency, comparability across data sets. The dataset consists of 1079 embryos from which 239 microscopy images were utilized to validate the proposed method.