Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI-Reference-Cited by-同舟云学术

Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI

Published:2021-01 Issue: Volume:198 Page:105817
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Xanthis Christos G.,Filos Dimitrios^ORCID,Haris Kostas^ORCID,Aletras Anthony H.

Funder

European Social Fund

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference39 articles.

1. Machine learning and radiology;Wang;Medical image analysis,2012

2. Machine learning approaches in medical image analysis: From detection to diagnosis;de Bruijne;Medical image analysis,2016

3. Haskins G, Kruger U, Yan P. Deep Learning in Medical Image Registration: A Survey. arXiv preprint arXiv:190302026. 2019.

4. Review of MRI-based Brain Tumor Image Segmentation Using Deep Learning Methods;Işın;Procedia Computer Science,2016

5. Deep learning in breast cancer risk assessment: evaluation of convolutional neural networks on a clinical dataset of full-field digital mammograms;Li;J Med Imaging (Bellingham),2017

Cited by 8 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. High-resolution conductivity reconstruction by electrical impedance tomography using structure-aware hybrid-fusion learning;Computer Methods and Programs in Biomedicine;2024-01

2. Deep-Learning-Enabled Differentiation between Intraprostatic Gold Fiducial Markers and Calcification in Quantitative Susceptibility Mapping;2023-10-31

3. Neural Network-based Tool for Survivability Assessment of K-variant Systems;International Journal on Artificial Intelligence Tools;2023-05-24

4. MRXCAT2.0: Synthesis of realistic numerical phantoms by combining left-ventricular shape learning, biophysical simulations and tissue texture generation;Journal of Cardiovascular Magnetic Resonance;2023-04-20

5. Prototype of a Cardiac MRI Simulator for the Training of Supervised Neural Networks;Functional Imaging and Modeling of the Heart;2023