Image-guided filtering for improving photoacoustic tomographic image reconstruction

Awasthi, Navchetan and Kalva, Sandeep Kumar and Pramanik, Manojit and Yalavarthy, Phaneendra K (2018) Image-guided filtering for improving photoacoustic tomographic image reconstruction. In: JOURNAL OF BIOMEDICAL OPTICS, 23 (9).

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Abstract

Several algorithms exist to solve the photoacoustic image reconstruction problem depending on the expected reconstructed image features. These reconstruction algorithms promote typically one feature, such as being smooth or sharp, in the output image. Combining these features using a guided filtering approach was attempted in this work, which requires an input and guiding image. This approach act as a postprocessing step to improve commonly used Tikhonov or total variational regularization method. The result obtained from linear backprojection was used as a guiding image to improve these results. Using both numerical and experimental phantom cases, it was shown that the proposed guided filtering approach was able to improve (as high as 11.23 dB) the signal-to-noise ratio of the reconstructed images with the added advantage being computationally efficient. This approach was compared with state-of-the-art basis pursuit deconvolution as well as standard denoising methods and shown to outperform them. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

Item Type:	Journal Article
Publication:	JOURNAL OF BIOMEDICAL OPTICS
Publisher:	SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Additional Information:	Copy right for this article belong to SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Keywords:	photoacoustic imaging; guided image filtering; Lanczos Tikhonov; basis pursuit deconvolution; total variation; model-based reconstruction
Department/Centre:	Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited:	30 Nov 2018 14:49
Last Modified:	30 Nov 2018 14:49
URI:	http://eprints.iisc.ac.in/id/eprint/61195

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