Deep learning-based multi-frequency denoising for myocardial perfusion SPECT.

ABSTRACT:

Background

Deep learning (DL)-based denoising has been proven to improve image quality and quantitation accuracy of low dose (LD) SPECT. However, conventional DL-based methods used SPECT images with mixed frequency components. This work aims to develop an integrated multi-frequency denoising network to further enhance LD myocardial perfusion (MP) SPECT denoising.

Methods

Fifty anonymized patients who underwent routine ^99mTc-sestamibi stress SPECT/CT scans were retrospectively recruited. Three LD datasets were obtained by reducing the 10 s acquisition time of full dose (FD) SPECT to be 5, 2 and 1 s per projection based on the list mode data for a total of 60 projections. FD and LD projections were Fourier transformed to magnitude and phase images, which were then s

SUBMITTER: Du Y 

PROVIDER: S-EPMC11447183 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature