What Is Computational Pathology
A branch of pathology that examines patient samples using a variety of procedures and computer analysis to better understand disease. Using AI methods like deep learning, this work focuses on information extraction from digital pathology images and their related meta-data.
Deep learning methods, in particular convolutional neural networks (CNNs), are a natural fit for picture recognition and computer vision in the healthcare industry because they can extract features from visual input. Artificial intelligence (AI) models work as an extra set of eyes that can spot details that humans would miss out on out of fatigue or for other reasons
Uses Of Scanner In Computational Pathology
The Computational Pathology Laboratory (DCPL) uses bright field and fluorescence scanners to get high resolution images of tissue slides, enabling researchers to observe particular of the morphologic and spectral features of cells and/or cancer regions.
Computational Pathology Applications
Convolutional neural networks (CNNs), generative adversarial networks (GANs), and graph neural networks (GNNs), among others, have transformed the accuracy of prediction in a wide range of sectors over the past ten years. Deep learning algorithms have recently proven to have amazing potential for supporting physicians, automating diagnoses, and lowering costs for patients when applied to computer vision tasks in pathology.
Pathology Societys
European Society for Digital and Integrative Pathology,
Austrian Society of Pathology ,
The European Society of Pathology
Brazilian Society of Pathology
