Deep transfer learning for DOI domain transformation

Nazish Murad, Min Chun Pan, Ya Fen Hsu

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

In the study transfer learning was employed to adapt the previously developed deep networks, 1D_BNCNN and 2D_BNCNN, to handle elliptical phantoms in DOI. The network was fine-tuned using the newly acquired elliptical phantom dataset by leveraging the knowledge and pre-trained weights obtained from the circular phantom dataset. This approach can potentially enhance the realism and accuracy of DOT imaging, enabling more precise characterization of biological tissues and structures.

原文???core.languages.en_GB???
主出版物標題Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences
編輯Liang Gao, Guoan Zheng, Seung Ah Lee
發行者SPIE
ISBN(電子)9781510669734
DOIs
出版狀態已出版 - 2024
事件Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences 2024 - San Francisco, United States
持續時間: 27 1月 202429 1月 2024

出版系列

名字Progress in Biomedical Optics and Imaging - Proceedings of SPIE
12857
ISSN(列印)1605-7422

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???event.eventtypes.event.conference???Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences 2024
國家/地區United States
城市San Francisco
期間27/01/2429/01/24

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