U-Net for nuclei image segmentation

Abstract

The nucleus is the core of a cell. The genetic information, commonly known as a living being's DNA, is stored in this massive yet tiny membrane-bound organelle. Biomedical image segmentation has a lot of scope for improvement, thus it's been hypothesized that by segmenting high-resolution nuclei images, we can extract high-quality nuclei features. Deep Learning techniques are thought to have a bright future in computing pathology. However, in this case, we're leveraging U-Net to automate nucleus identification in order to help speed up the development of therapies for everything from rare disorders to the common cold.