Prostate Cancer Detection Using a Transformer-Based Architecture and Radiomic-Based Postprocessing

Abstract

The detection of prostate cancer is an important challenge for medical personnel. To improve the medical system’s ability to process increasing numbers of oncological patients, demand for automation systems is growing. At the National Information Processing Institute, such systems are undergoing active development. In this work, the authors present the results of a pilot study whose goal is to analyze possible directions in the development of new, advanced deep learning systems using a high quality dataset that is currently in development.