SPECTnet: a deep learning neural network for SPECT image reconstruction.

ABSTRACT:

Background

Single photon emission computed tomography (SPECT) is an important functional tool for clinical diagnosis and scientific research of brain disorders, but suffers from limited spatial resolution and high noise due to hardware design and imaging physics. The present study is to develop a deep learning technique for SPECT image reconstruction that directly converts raw projection data to image with high resolution and low noise, while an efficient training method specifically applicable to medical image reconstruction is presented.

Methods

A custom software was developed to generate 20,000 2-D brain phantoms, of which 16,000 were used to train the neural network, 2,000 for validation, and the final 2,000 for testing. To reduce development difficulty, a two-step train

SUBMITTER: Shao W 

PROVIDER: S-EPMC8246183 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature