Enhancement of Noisy Planar Nuclear Medicine Images using Mean Field Annealing

TL;DR

This paper introduces a method using Mean Field Annealing to effectively reduce noise and blur in planar nuclear medicine images, enhancing image quality for better diagnostic accuracy.

Contribution

The study applies Mean Field Annealing to nuclear medicine images, improving noise reduction and edge preservation beyond standard processing methods.

Findings

Significant noise reduction achieved in NM images.

Enhanced image sharpness and clarity after MFA and sharpening filter.

Maintained edge integrity while reducing noise.

Abstract

Nuclear medicine (NM) images inherently suffer from large amounts of noise and blur. The purpose of this research is to reduce the noise and blur while maintaining image integrity for improved diagnosis. The proposed solution is to increase image quality after the standard pre- and post-processing undertaken by a gamma camera system. Mean Field Annealing (MFA) is the image processing technique used in this research. It is a computational iterative technique that makes use of the Point Spread Function (PSF) and the noise associated with the NM image. MFA is applied to NM images with the objective of reducing noise while not compromising edge integrity. Using a sharpening filter as a post-processing technique (after MFA) yields image enhancement of planar NM images.