Computational Pathology Group

Computational pathology aims to improve diagnostic accuracy, optimize patient care, and reduce costs by bringing global collaboration. Computational pathology has the potential to transform the traditional core functions of pathology and not just growing sub-segments such as digital pathology, molecular pathology, and pathology informatics. Digital pathology utilizes virtual microscope, which includes the process of digitizing glass slides using a whole slide image (WSI) scanner and then analyzing the digital images. Different image processing techniques are required to achieve a reliable image from the biological tissues. The digital data of the slides can be stored in a central cloud-based space allowing for remote access to the information for manual review by a pathologist or automated review by deep learning algorithms. Therefore, computational pathology involves extracting information from digitized pathology images in combination with their associated metadata, typically using artificial intelligence methods to detect, diagnose, and predict different diseases. We aim to develop image ana¬ly¬tics that can quan¬ti¬fy path¬o¬gen¬esis in a high-through¬put, bias-free and ro¬bust way.