Literature DB >> 34537130

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

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

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.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

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

Mesh：

Year:  2021        PMID： 34537130      PMCID： PMC8457531          DOI： 10.1016/j.cpet.2021.06.005

Source DB:  PubMed          Journal:  PET Clin        ISSN： 1556-8598


  65 in total

1.  3D Auto-Context-Based Locality Adaptive Multi-Modality GANs for PET Synthesis.

Authors:  Yan Wang; Luping Zhou; Biting Yu; Lei Wang; Chen Zu; David S Lalush; Weili Lin; Xi Wu; Jiliu Zhou; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2018-11-29       Impact factor: 10.048

2.  Full-Dose PET Image Estimation from Low-Dose PET Image Using Deep Learning: a Pilot Study.

Authors:  Sydney Kaplan; Yang-Ming Zhu
Journal:  J Digit Imaging       Date:  2019-10       Impact factor: 4.056

3.  Full-count PET recovery from low-count image using a dilated convolutional neural network.

Authors:  Karl Spuhler; Mario Serrano-Sosa; Renee Cattell; Christine DeLorenzo; Chuan Huang
Journal:  Med Phys       Date:  2020-08-06       Impact factor: 4.071

4.  Higher SNR PET image prediction using a deep learning model and MRI image.

Authors:  Chih-Chieh Liu; Jinyi Qi
Journal:  Phys Med Biol       Date:  2019-05-23       Impact factor: 3.609

5.  PET image super-resolution using generative adversarial networks.

Authors:  Tzu-An Song; Samadrita Roy Chowdhury; Fan Yang; Joyita Dutta
Journal:  Neural Netw       Date:  2020-02-03

6.  Micro-Networks for Robust MR-Guided Low Count PET Imaging.

Authors:  Casper O da Costa-Luis; Andrew J Reader
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-04-08

7.  Suitability of bilateral filtering for edge-preserving noise reduction in PET.

Authors:  Frank Hofheinz; Jens Langner; Bettina Beuthien-Baumann; Liane Oehme; Jörg Steinbach; Jörg Kotzerke; Jörg van den Hoff
Journal:  EJNMMI Res       Date:  2011-10-05       Impact factor: 3.138

8.  Non-local means denoising of dynamic PET images.

Authors:  Joyita Dutta; Richard M Leahy; Quanzheng Li
Journal:  PLoS One       Date:  2013-12-05       Impact factor: 3.240

9.  Restoration of amyloid PET images obtained with short-time data using a generative adversarial networks framework.

Authors:  Young Jin Jeong; Hyoung Suk Park; Ji Eun Jeong; Hyun Jin Yoon; Kiwan Jeon; Kook Cho; Do-Young Kang
Journal:  Sci Rep       Date:  2021-03-01       Impact factor: 4.379
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  6 in total

Review 1.  Artificial Intelligence and Positron Emission Tomography Imaging Workflow:: Technologists' Perspective.

Authors:  Cheryl Beegle; Navid Hasani; Roberto Maass-Moreno; Babak Saboury; Eliot Siegel
Journal:  PET Clin       Date:  2022-01

Review 2.  Artificial Intelligence in Lymphoma PET Imaging:: A Scoping Review (Current Trends and Future Directions).

Authors:  Navid Hasani; Sriram S Paravastu; Faraz Farhadi; Fereshteh Yousefirizi; Michael A Morris; Arman Rahmim; Mark Roschewski; Ronald M Summers; Babak Saboury
Journal:  PET Clin       Date:  2022-01

3.  Virtual high-count PET image generation using a deep learning method.

Authors:  Juan Liu; Sijin Ren; Rui Wang; Niloufarsadat Mirian; Yu-Jung Tsai; Michal Kulon; Darko Pucar; Ming-Kai Chen; Chi Liu
Journal:  Med Phys       Date:  2022-08-13       Impact factor: 4.506

Review 4.  Advances in Preclinical PET.

Authors:  Stephen S Adler; Jurgen Seidel; Peter L Choyke
Journal:  Semin Nucl Med       Date:  2022-03-18       Impact factor: 4.802

5.  Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT.

Authors:  Kathleen Weyts; Charline Lasnon; Renaud Ciappuccini; Justine Lequesne; Aurélien Corroyer-Dulmont; Elske Quak; Bénédicte Clarisse; Laurent Roussel; Stéphane Bardet; Cyril Jaudet
Journal:  Eur J Nucl Med Mol Imaging       Date:  2022-05-20       Impact factor: 10.057

6.  Effect of Denoising and Deblurring 18F-Fluorodeoxyglucose Positron Emission Tomography Images on a Deep Learning Model's Classification Performance for Alzheimer's Disease.

Authors:  Min-Hee Lee; Chang-Soo Yun; Kyuseok Kim; Youngjin Lee
Journal:  Metabolites       Date:  2022-03-07
  6 in total

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