Method for inserting noise in digital mammography to simulate reduction in radiation dose

Abstract

The quality of clinical x-ray images is closely related to the radiation dose used in the imaging study. The general principle for selecting the radiation is ALARA (“as low as reasonably achievable”). The practical optimization, however, remains challenging. It is well known that reducing the radiation dose increases the quantum noise, which could compromise the image quality. In order to conduct studies about dose reduction in mammography, it would be necessary to acquire repeated clinical images, from the same patient, with different dose levels. However, such practice would be unethical due to radiation related risks. One solution is to simulate the effects of dose reduction in clinical images. This work proposes a new method, based on the Anscombe transformation, which simulates dose reduction in digital mammography by inserting quantum noise into clinical mammograms acquired with the standard radiation dose. Thus, it is possible to simulate different levels of radiation doses without exposing the patient to new levels of radiation. Results showed that the achieved quality of simulated images generated with our method is the same as when using other methods found in the literature, with the novelty of using the Anscombe transformation for converting signal-independent Gaussian noise into signal-dependent quantum noise.