A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Prakash, Jaya and Yalavarthy, Phaneendra K (2013) A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography. In: MEDICAL PHYSICS, 40 (3).

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Abstract

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Item Type:	Journal Article
Publication:	MEDICAL PHYSICS
Publisher:	AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS
Additional Information:	Copyright for this article belongs to the AMER ASSOC PHYSICISTS MEDICINE AMER INST PHYSICS, USA.
Keywords:	near infrared imaging; diffuse optical tomography; image reconstruction; inverse problems; regularization parameter
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	22 Apr 2013 06:45
Last Modified:	22 Apr 2013 06:45
URI:	http://eprints.iisc.ac.in/id/eprint/46438

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