Investigating the challenges and generalizability of deep learning brain conductivity mapping
説明
To investigate deep learning electrical properties tomography (EPT) for application on different simulated and in-vivo datasets, including pathologies for brain conductivity reconstructions, 3D patch-based convolutional neural networks were trained to predict conductivity maps from B
収録刊行物
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- Physics in Medicine & Biology
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Physics in Medicine & Biology 65 (13), 135001-, 2020-06-26
IOP Publishing
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キーワード
- EPT
- Normal Distribution
- Deep Learning
- Journal Article
- Image Processing, Computer-Assisted
- Humans
- electromagnetic field simulations
- electrical properties tomography
- Brain Diseases
- Brain Mapping
- Radiological and Ultrasound Technology
- Electric Conductivity
- deep learning
- Brain
- Radiology Nuclear Medicine and imaging
- Case-Control Studies
- Positron-Emission Tomography
- brain tissue conductivity
- Artifacts
- Algorithms
- MRI
詳細情報 詳細情報について
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- CRID
- 1360290617746329472
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- ISSN
- 13616560
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- PubMed
- 32408291
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- 資料種別
- journal article
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- データソース種別
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- Crossref
- KAKEN
- OpenAIRE