The wide-spread adoption of digital pathology has opened new horizons for histopathology. Artificial intelligence (AI) algorithms are able to operate on digitized slides to assist pathologists with different tasks. Whereas AI involving classification and segmentation methods have obvious benefits for image analysis, image search represents a fundamental shift in computational pathology. Image-based search for digitized […]

Advances in Whole Slide Imaging (WSI) and Machine Learning (ML) open new opportunities to create innovative solutions in healthcare and in particular digital pathology to increase efficiencies, reduce cost and most importantly improve patient care. This project envisions the creation of new automated ML tools including the design of a custom Convolution Neural Network (CNN) […]

Fluorescence imaging is a powerful technique to focus and acquire high-resolution pathology images that contain rich sources of information that is useful for diagnostics in clinical trials to study possible disease such as cancer glands and tumors. Despite the high definition images, the collected images are severely contaminated with noise artifacts which make most feature […]