Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement

Juan Liu; Masoud Malekzadeh; Niloufar Mirian; Tzu-An Song; Chi Liu; Joyita Dutta

doi:10.1016/j.cpet.2021.06.005

Artificial Intelligence-Based Image Enhancement in PET Imaging: Noise Reduction and Resolution Enhancement

PET Clin. 2021 Oct;16(4):553-576. doi: 10.1016/j.cpet.2021.06.005.

Authors

Juan Liu¹, Masoud Malekzadeh², Niloufar Mirian¹, Tzu-An Song², Chi Liu³, Joyita Dutta⁴

Affiliations

¹ Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
² Department of Electrical and Computer Engineering, University of Massachusetts Lowell, 1 University Avenue, Ball 301, Lowell, MA 01854, USA.
³ Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA. Electronic address: chi.liu@yale.edu.
⁴ Department of Electrical and Computer Engineering, University of Massachusetts Lowell, 1 University Avenue, Ball 301, Lowell, MA 01854, USA; Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: dutta.joyita@mgh.harvard.edu.

Abstract

High noise and low spatial resolution are two key confounding factors that limit the qualitative and quantitative accuracy of PET images. Artificial intelligence models for image denoising and deblurring are becoming increasingly popular for the postreconstruction enhancement of PET images. We present a detailed review of recent efforts for artificial intelligence-based PET image enhancement with a focus on network architectures, data types, loss functions, and evaluation metrics. We also highlight emerging areas in this field that are quickly gaining popularity, identify barriers to large-scale adoption of artificial intelligence models for PET image enhancement, and discuss future directions.

Keywords: Artificial intelligence; Deblurring; Deep learning; Denoising; PET; Super-resolution.

Publication types

Review

MeSH terms

Artificial Intelligence*
Humans
Image Enhancement
Image Processing, Computer-Assisted*
Positron-Emission Tomography
Signal-To-Noise Ratio

Abstract

Publication types

MeSH terms

Grants and funding