Adaptive compressed sensing for spectral-domain optical coherence tomography

Yi Wang; Xiaodong Chen; Ting Wang; Hongxiao Li; Daoyin Yu

doi:10.1117/12.2032301

4 March 2014 Adaptive compressed sensing for spectral-domain optical coherence tomography

Yi Wang, Xiaodong Chen, Ting Wang, Hongxiao Li, Daoyin Yu

Proceedings Volume 8934, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVIII; 89343F (2014) https://doi.org/10.1117/12.2032301
Event: SPIE BiOS, 2014, San Francisco, California, United States

Abstract

Spectral-domain optical coherence tomography (SD-OCT) is a non-contact and non-invasive method for measuring the change of biological tissues caused by pathological changes of body. CCD with huge number of pixels is usually used in SD-OCT to increase the detecting depth, thus enhancing the hardness of data transmission and storage. The usage of compressed sensing (CS) in SD-OCT is able to reduce the trouble of large data transfer and storage, thus eliminating the complexity of processing system. The traditional CS uses the same sampling model for SD-OCT images of different tissue, leading to reconstruction images with different quality. We proposed a CS with adaptive sampling model. The new model is based on uniform sampling model, and the interference spectral of SD-OCT is considered to adjust the local sampling ratio. Compared with traditional CS, adaptive CS can modify the sampling model for images of different tissue according to different interference spectral, getting reconstruction images with high quality without changing sampling model.

Citation Download Citation

Yi Wang, Xiaodong Chen, Ting Wang, Hongxiao Li, and Daoyin Yu "Adaptive compressed sensing for spectral-domain optical coherence tomography", Proc. SPIE 8934, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XVIII, 89343F (4 March 2014); https://doi.org/10.1117/12.2032301

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