A leading provider of digital health in precision medicine aims to enhance medical care by accelerating the discovery of new drugs and treatment possibilities by applying the Bio-AI artificial intelligence model and dealing with histology images to predict the pharmacological activities of drug candidates. With multi-drug therapy being a mainstay, they hope to benefit pharmaceutical companies, patients, and society at large with scalable and cost-effective solutions.
Automating and accelerating the discovery of new drugs and treatment possibilities. With help of Bio–AI artificial intelligence helps to benefit pharmaceutical companies, patients, and society at large with scalable and cost-effective solutions. Data Integration is an open platform that integrates multiple datatypes which helps to increase the efficiency of analysis and improves success for biomarker development. Deals with histology images where the texture, spectral and structural features such as the nucleus are identified with the help of Image processing. The structural features such as shape index, compactness, elliptic fit, distance, etc. of the nucleus. The spectral features involve finding out the optical density format of the given images and obtaining the stain vectors and intensity for the stains involved in the histology images such as Hematoxylin, Eosin, and Residual.
In the first part of this article, we have discussed about the basics of Image Segmentation, its process, and its use. In this article, we will discuss the type of image segmentation, architectures, loss functions, and some interesting use cases of image segmentation.