PhD defense David Tellez

David Tellez obtained his PhD title cum laude after succesfully defending his thesis entitled 'Advancing computational pathology with deep learning: from patches to gigapixel image-level classification' in the Auditorium of Radboud University on the 18th of July

Pathology is the cornerstone of clinical diagnostics. When there is a suspicion of abnormal tissue, e.g. a lump in a breast or a nodule in the lungs, a biopsy is taken in order to examine the tissue sample under the microscope and produce a diagnostic. The field of pathology is undergoing a major digital revolution, from analog microscopes and glass slides, to a fully digital workflow. Dr. David Tellez' work contributes to develop artificial intelligence (AI) algorithms to assist pathologists in their daily tasks, e.g. breast cancer diagnostics. Dr. David Tellez' research explores a specific type of AI called deep learning or artificial neural networks that simulates how neurons in the brain learn and communicate to each other. These artificial neural networks are the most successful form of AI currently, and are destined to improve the quality of clinical diagnostics while decreasing the costs of healthcare. Some of the algorithms developed in this thesis are currently been validated for their application in breast cancer grading.

More information can be found in the Radboud University website.

Defense David Tellez Martin I

Defense David Tellez Martin II

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