The BANFF classification is a comprehensive system that strives to establish uniformity in the lesions resulting from rejection sub sequent to renal transplantation. This process is particularly time-consuming and energy-intensive for pathologists, as each sample from the biopsies must be analyzed in detail. The aim of this project is to automate this process, identifying the five most relevant element namely glomeruli, blood vessels, tubules, nuclei, and interstitial tissue. In this work, we focus on the detection of tubules, vessels and nuclei using a new database composed by nineteen wsi images collected by the University Hospital Center (CHU) of Nice. From the original data base, we selected and labeled a total of fifty-six 1024 x 1024 patches, nine per patient.