Automatic Breast Screening by Fully Automated Ultrasound Imaging Using CNN And Transformer Algorithm
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- INOUE Kenichi Inoue
- Breast Cancer Center, Shonan Memorial Hospital
Bibliographic Information
- Other Title
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- CNN+transformerを用いた全自動超音波検査による自動診断の検討
Abstract
<p>To investigate and evaluate the accuracy of automatic detection of breast cancer by fully automated ultrasound imagings(called “ring echo”) using deep learning. One hundred and ninety-four women diagnosed as breast cancer were performed by ring echo to obtain 917 images with breast cancer and 3321 images without breast cancer. These datasets were trained with the novel algorithm using convolutional neural network and transformer. The result showed accuracy 87.9%, sensitivity 87.9%, specificity 85.3% per images, and accuracy 78.6%, sensitivity 85.7%, specificity 71.4% per case. Ring echo imaging could help contribute and change whole system of breast screening with ultrasound.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2022 (0), 2P1GS1003-2P1GS1003, 2022
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
- 1390011231125753856
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- Text Lang
- ja
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- Data Source
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- JaLC
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- Abstract License Flag
- Disallowed