Reference-driven method for MR image reconstruction based on wavelet sparsity and nonlocal total variation

A novel reference-driven method for MR image reconstruction based on wavelet sparsity and nonlocal total variation（NLTV）is proposed.Utilizing the sparsity of the difference image between the target image and the motion-compensated reference image in wavelet transform domain,the proposed method does not need to estimate contrast changes and therefore increases computational efficiency.Additionally,NLTV regularization is applied to preserve image details and features without blocky effects.An efficient alternating iterative algorithm is used to estimate motion effects and reconstruct the difference image.Experimental results demonstrate that the proposed method can significantly reduce sampling rate or improve the quality of the reconstructed image alternatively.

Blind Image Quality Assessment by Pairwise Ranking Image Series

Image quality assessment(IQA)is constantly innovating,but there are still three types of stickers that have not been resolved:the“content sticker”-limitation of training set,the“annotation sticker”-subjective instability in opinion scores and the“distortion sticker”-disordered distortion settings.In this paper,a No-Reference Image Quality Assessment(NR IQA)approach is proposed to deal with the problems.For“content sticker”,we introduce the idea of pairwise comparison and generate a largescale ranking set to pre-train the network;For“annotation sticker”,the absolute noise-containing subjective scores are transformed into ranking comparison results,and we design an indirect unsupervised regression based on EigenValue Decomposition(EVD);For“distortion sticker”,we propose a perception-based distortion classification method,which makes the distortion types clear and refined.Experiments have proved that our NR IQA approach Experiments show that the algorithm performs well and has good generalization ability.Furthermore,the proposed perception based distortion classification method would be able to provide insights on how the visual related studies may be developed and to broaden our understanding of human visual system.

Feasibility study of phase-sensitive imaging based on multiple reference optical coherence tomography

Multiple reference optical coherence tomography（MR-OCT） is a recently developed, low-cost and compact time-domain OCT solution for primary care and consumer level applications. A combination of a voice coil actuator and a partial mirror（PM） extends the scan range for imaging depths of approximately 1 mm in biological samples. Our previous research on MR-OCT is based only on intensity information obtained from the depth-resolved interference signal. In this Letter, we extract the phase information from the MR-OCT signal and, hence, provide an additional contrast modality. The phase sensitivity of the system is measured to be approximately 0.2 and 1.5 rad for the first and twelfth orders of reflection when using a mirror as the sample.This Letter describes first results of phase-sensitive data measured on a phantom obtained with MR-OCT. Data from a chick embryo chorioallantoic membrane（CAM） is used to demonstrate the feasibility of MR-OCT for in vivo phase-sensitive imaging.