Using deep learning to remove computed tomography artifacts due to hip replacement
Computed Tomography (CT) is the most common diagnostic method for cancer and prostate cancer is the most common cancer among men in Sweden. Some of the patients that get scanned have hip replacements that cause artifacts in CT scans that make the CT images unreadable for physicians. In this Master’s Thesis an autoencoder model was implemented to reduce artifacts due to hip replacements in CT image
