Artificial Enhanced MRI Imaging Generative Model
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- INOUE Kenichi
- Shonan Memorial Hospital
Bibliographic Information
- Other Title
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- 非造影乳房MRIからの造影画像自動生成モデルの構築
Abstract
<p>[background]Breast MRI screening for breast cancer has been recommended for those with BRCA1/2 mutations. However, there are disadvantages having an annual MRI scan. The MRI imaging model which generated enhanced MRI images from the simple MRI without contrast agent was constructed. [materials&methods]Of the contrast-enhanced MRI images of the cases diagnosed as primary breast cancer, fat suppression T1-weighted images(T1), fat suppression T2-weighted images(T2), diffusion weighted images(DWI) and contrasted early-phase images(early phase) in which cut planes match in all types were used. U-Net algorithm was trained to estimate the early phase from T1, T2, and DWI. [result]The mean squared error was decreased down to 264. The peak signal-to-noise ratio was 55.1 dB, indicatig that the images were properly generated. [discussion]MRI screening can be performed more safely and efficiently without contrast agent.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2020 (0), 2Q6GS1002-2Q6GS1002, 2020
The Japanese Society for Artificial Intelligence
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Keywords
Details 詳細情報について
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- CRID
- 1390566775142872576
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- NII Article ID
- 130007857028
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed