Improved image quality for Cherenkov-excited luminescence scanned tomography based on learned KSVD

Hu Zhang; Zhe Li; Zhonghua Sun; Mengfan Geng; Kebin Jia; Jinchao Feng

doi:10.1117/12.2607478

4 March 2022 Improved image quality for Cherenkov-excited luminescence scanned tomography based on learned KSVD

Hu Zhang, Zhe Li, Zhonghua Sun, Mengfan Geng, Kebin Jia, Jinchao Feng

Proceedings Volume 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII; 119430G (2022) https://doi.org/10.1117/12.2607478
Event: SPIE BiOS, 2022, San Francisco, California, United States

Conference Poster

Abstract

Cherenkov-excited luminescence scanned imaging (CELSI) is a new emerging imaging modality, which uses linear accelerator (LINAC) to induce Cherenkov radiation, and then secondary excite molecular probes to produce luminescence. The tomographic distribution of the molecular probes can be recovered by a reconstruction algorithm. However, the reconstruction images usually suffer from many artifacts. To improve the image quality for tomographic reconstruction, we propose a reconstruction method based on learned KSVD. Numerical simulation experiments reveal that the proposed algorithm can reduce the artifacts in the reconstructed image. The quantitative results show that the structured similarity (SSIM) is improved more than 8.8% compared to the existing algorithms. In addition, our results also demonstrate that the proposed algorithm has the best performance under different noise levels (0.5%, 1%, 2%, and 4%).

Conference Presentation

Citation Download Citation

Hu Zhang, Zhe Li, Zhonghua Sun, Mengfan Geng, Kebin Jia, and Jinchao Feng "Improved image quality for Cherenkov-excited luminescence scanned tomography based on learned KSVD", Proc. SPIE 11943, Molecular-Guided Surgery: Molecules, Devices, and Applications VIII, 119430G (4 March 2022); https://doi.org/10.1117/12.2607478

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available