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Abstract
Evidence-based medicine has received increasing attention. This type of medicine would have the benefit of using large data sets to investigate clinical–laboratory associations and validate hypotheses grounded on data. Pathology is one area that has been benefited from large data sets of images, having advances leveraged by computational pathology, which in turn relies in the advances of the methods conceived by the computational intelligence and the computer vision fields. This type of medicine would benefit of using large. By particularly considering kidney biopsies, computational nephropathology seeks to identify renal lesions from primary computer vision tasks that involve classification and segmentation of renal structures on histology images. In this context, this chapter aims at discussing some advances in computational nephropathology, contextualizing them in the scope of the PathoSpotter project. We also address current achievements and challenges, as well as dig in future prospects to the field.