title: Optshrink LR + S: accelerated fMRI reconstruction using non-convex optimal singular value shrinkage.
abstract: This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l1minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.
authors.affiliation: SBILab, Department of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India. priyaa@iiitd.ac.in.
authors.forename: Priya
authors.initials: P
authors.lastname: Aggarwal
authors.affiliation: SBILab, Department of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India.
authors.forename: Parth
authors.initials: P
authors.lastname: Shrivastava
authors.affiliation: SBILab, Department of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India.
authors.forename: Tanay
authors.initials: T
authors.lastname: Kabra
authors.affiliation: SBILab, Department of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India.
authors.forename: Anubha
authors.initials: A
authors.lastname: Gupta
keywords: Accelerated functional MRI; Compressed sensing; Low-rank recovery; Sparse recovery; Undersampling; k–t acceleration