A method for acquiring a three-dimensional image volume using a magnetic resonance imaging device, the method comprising: performing a multi-slab acquisition process to acquire a plurality of three-dimensional slabs corresponding to an imaged object using a plurality of coils included in the magnetic resonance imaging device, wherein each respective three dimensional slab included in the plurality of three-dimensional slabs comprises k-space data; and applying an iterative compressed-sensing reconstruction process to jointly reconstruct the plurality of three-dimensional slabs as a single consistent volume, wherein the iterative compressed-sensing reconstruction process solves a cost function comprising a summation of individual data fidelity terms corresponding to the plurality of three-dimensional slabs, wherein the multi-slab acquisition process is a multi-slab acquisition process which performs incoherent undersampling of the imaged object along a slab direction, wherein the cost function is: f ^ = argmax f 1 2 ∑ n s = 1 N s ∑ n c = 1 N c ‖ G n s , n c − F u S n s , n c ⊙ ∏ n s f ‖ 2 2 + λ ‖ Λ ⊙ Wf ‖ 1 . , wherein f is a one-dimensional vector which is the vectorized version of the signal to be reconstructed, N c is the number of coils used by the MRI device, N s is the number of slabs, F u is a measurement matrix, G ns,nc is the measured data for a particular coil and a particular slab, S ns,nc is the coil sensitivity profile for a particular coil and a particular slab, the operator Π ns is applied to f to extract a particular slab n s from the overall volume, W represents a redundant Haar wavelet transform, Λ is a regularization weighting factor and λ is a regularization parameter governing the tradeoff between data fidelity and its sparsity. performing a multi-slab acquisition process to acquire a plurality of three-dimensional slabs corresponding to an imaged object using a plurality of coils included in the magnetic resonance imaging device, wherein each respective three dimensional slab included in the plurality of three-dimensional slabs comprises k-space data; and applying an iterative compressed-sensing reconstruction process to jointly reconstruct the plurality of three-dimensional slabs as a single consistent volume, wherein the iterative compressed-sensing reconstruction process solves a cost function comprising a summation of individual data fidelity terms corresponding to the plurality of three-dimensional slabs, wherein the multi-slab acquisition process is a multi-slab acquisition process which performs incoherent undersampling of the imaged object along a slab direction, wherein the cost function is: f ^ = argmax f 1 2 ∑ n s = 1 N s ∑ n c = 1 N c ‖ G n s , n c − F u S n s , n c ⊙ ∏ n s f ‖ 2 2 + λ ‖ Λ ⊙ Wf ‖ 1 . , wherein f is a one-dimensional vector which is the vectorized version of the signal to be reconstructed, N c is the number of coils used by the MRI device, N s is the number of slabs, F u is a measurement matrix, G ns,nc is the measured data for a particular coil and a particular slab, S ns,nc is the coil sensitivity profile for a particular coil and a particular slab, the operator Π ns is applied to f to extract a particular slab n s from the overall volume, W represents a redundant Haar wavelet transform, Λ is a regularization weighting factor and λ is a regularization parameter governing the tradeoff between data fidelity and its sparsity. <EOS>