This study proposes an automated segmentation of prostate cancer in transrectal ultrasound images using different preprocessing methods to enhance the segmentation accuracy. We propose the use of image intensity normalization and despeckle filtering, individually and in combination, as preprocessing techniques to improve the performance of a deep learning segmentation model (DeepLabv3 +) in ultrasound images of prostate cancer.