A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT-Reference-Cited by-同舟云学术

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A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT

Published:2023-04-03 Issue: Volume: Page:
ISSN:
Container-title:Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment
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Author:

Rahman Md Ashequr,Yu Zitong,Siegel Barry A.,Jha Abhinav K.

Publisher

SPIE

Reference19 articles.

1. ASNC imaging guidelines for SPECT nuclear cardiology procedures: Stress, protocols, and tracers

2. Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss

3. Initial investigation of low-dose spect-mpi via deep learning;Ramon,2018

4. Objective assessment of image quality: effects of quantum noise and object variability

5. Objective Task-Based Evaluation of Artificial Intelligence-Based Medical Imaging Methods

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial Intelligence in Nuclear Cardiology: An Update and Future Trends;Seminars in Nuclear Medicine;2024-09

2. Current status and future directions in artificial intelligence for nuclear cardiology;Expert Review of Cardiovascular Therapy;2024-07-16

3. Recent developments in denoising medical images using deep learning: An overview of models, techniques, and challenges;Micron;2024-05

4. DEMIST: A Deep-Learning-Based Detection-Task-Specific Denoising Approach for Myocardial Perfusion SPECT;IEEE Transactions on Radiation and Plasma Medical Sciences;2024-04

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