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Prostate disease (PCa) is a serious sort of malignant growth and makes significant passing among men due its poor demonstrative framework. The pictures got from patients with carcinoma comprise of intricate and fundamental highlights that can't be extricated promptly by customary symptomatic procedures. There have been only very few assessments that have portrayed the periods of partition of prostate CT pictures. As needs be, in this article, we propose an Ensembled Transfer Learning (ETL) design to arrange well, moderate and deficient isolated prostate CT pictures.