Deep learning in Nuclear Medicine—focus on CNN-based approaches for PET/CT and PET/MR: where do we stand?
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology Nuclear Medicine and imaging
Link
http://link.springer.com/content/pdf/10.1007/s40336-021-00411-6.pdf
Reference76 articles.
1. Erickson BJ (2019) Deep learning and machine learning in imaging: basic principles. Artificial intelligence in medical imaging. Springer International Publishing, Cham, pp 39–46
2. Benjamens S, Dhunnoo P, Meskó B (2020) The state of artificial intelligence-based FDA-approved medical devices and algorithms: an online database. npj Digit Med 3:118
3. Zhou L, Schaefferkoetter JD, Tham IWK, Huang G, Yan J (2020) Supervised learning with cyclegan for low-dose FDG PET image denoising. Med Image Anal 65:101770
4. Xiang L, Qiao Y, Nie D, An L, Lin W, Wang Q et al (2017) Deep auto-context convolutional neural networks for standard-dose PET image estimation from low-dose PET/MRI. Neurocomputing 267:406–416
5. Spuhler K, Serrano-Sosa M, Cattell R, DeLorenzo C, Huang C (2020) Full-count PET recovery from low-count image using a dilated convolutional neural network. Med Phys 47:4928–4938
Cited by 17 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. Nondestructive Determination of TSS Content in Postharvest Mulberry Fruits Using Hyperspectral Imaging and Deep Learning;SPECTROSC SPECT ANAL;2024
2. Transforming clinical cardiology through neural networks and deep learning: A guide for clinicians;Current Problems in Cardiology;2024-04
3. Empowering PET: harnessing deep learning for improved clinical insight;European Radiology Experimental;2024-02-07
4. Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space;Computer Methods and Programs in Biomedicine;2024-01
5. Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT;PLOS ONE;2023-09-14
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3