Cherenkov-excited luminescence scanned tomography reconstruction based on Unet

Wenqian Zhang; Zhe Li; Zhonghua Sun; Kebin Jia; Jinchao Feng

doi:10.1117/12.2607408

4 March 2022 Cherenkov-excited luminescence scanned tomography reconstruction based on Unet

Wenqian Zhang, Zhe Li, Zhonghua Sun, Kebin Jia, Jinchao Feng

Proceedings Volume 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII; 119430F (2022) https://doi.org/10.1117/12.2607408
Event: SPIE BiOS, 2022, San Francisco, California, United States

Conference Poster

Abstract

Cherenkov-excited luminescence scanned tomography (CELST) is an emerging tomographic optical imaging modality. However, recovering spatial distribution of luminescent source from boundary measurements is a typically ill-posed problem. To improve the performance of CELST reconstruction, an end-to-end reconstruction algorithm is developed by combining dilated convolution and attention mechanism based on Unet (DA-Unet). Its performance is validated with numerical simulations. The results reveal that DA-Unet has superior reconstruction performance with high spatial resolution. It achieves image quality with PSNR of more than 35 dB and SSIM of larger than 0.95. Furthermore, the DAUnet can reconstruct luminescent source even with less boundary measurements.

Conference Presentation

Citation Download Citation

Wenqian Zhang, Zhe Li, Zhonghua Sun, Kebin Jia, and Jinchao Feng "Cherenkov-excited luminescence scanned tomography reconstruction based on Unet", Proc. SPIE 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII, 119430F (4 March 2022); https://doi.org/10.1117/12.2607408

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