Exploring Deep Learning to Improve Compton Camera Based Prompt Gamma Image Reconstruction for Proton Radiotherapy

Abstract

Proton beam radiotherapy is a cancer treatment method that uses proton beams to irradiate cancerous tissue while simultaneously sparing doses to healthy tissue. In order to optimize radiational doses to the tumor and ensure that healthy tissue is spared, many researchers have suggested verifying the treatment delivery through real-time imaging. One promising method of real-time imaging is through a Compton camera, which can image prompt gamma rays emitted along the beam’s path through the patient. However, the reconstructed images are often noisy and unusable for verifying proton treatment delivery due to limitations with the camera. We present the usage of deep learning to remove and correct the various problems that exist within our data.