An overview of deep learning in medical imaging focusing on MRI
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Summary
This paper indicates how deep learning has been applied to the entire MRI processing chain, from acquisition to image retrieval, from segmentation to disease prediction, and provides a starting point for people interested in experimenting and contributing to the field of deep learning for medical imaging.
- Type
- article
- Published
- 2018-11-25
- Cited by
- 1,992
- References
- 364
- Access
- Open access
- OpenAlex
- https://openalex.org/W2900954917
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:53753063
Keywords
Deep learning, Medical imaging, Field (mathematics), Artificial neural network, Convolutional neural network
References
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- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- DART: Dropouts meet Multiple Additive Regression Trees
- On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
- Understanding Neural Networks Through Deep Visualization
- CBMIR: Content-based Image Retrieval Algorithm for Medical Image Databases
- Brain tumor segmentation with Deep Neural Networks
- Fully convolutional networks for semantic segmentation
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- Synthesis of CT images from digital body phantoms using CycleGAN
- MRI in systems medicine
- Automated Segmentation of Tissues using CT and MRI: A Systematic Review
- Intelligent Imaging: Anatomy of Machine Learning and Deep Learning
- Towards the Design of the OTS Ceiling Suspension Unistruts of the XR-646 Medical Equipment
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