Spectrally selective imaging with wideband balanced steady-state free precession MRI

Purpose Unwanted, bright fat signals in balanced steady-state free precession sequences are commonly suppressed using spectral shaping. Here, a new spectral-shaping method is proposed to significantly improve the uniformity of stopband suppression without compromising the level of passband signals. Methods The proposed method combines binomial-pattern excitation pulses with a wideband balanced steady-state free precession sequence kernel. It thereby increases the frequency separation between the centers of pass and stopbands by π radians, enabling improved water-fat contrast. Simulations were performed to find the optimal flip angles and subpulse spacing for the binomial pulses that maximize contrast and signal efficiency. Results Comparisons with a conventional binomial balanced steady-state free precession sequence were performed in simulations as well as phantom and in vivo experiments at 1.5 T and 3 T. Enhanced fat suppression is demonstrated in vivo with an average improvement of 58% in blood-fat and 68% in muscle-fat contrast (P < 0.001, Wilcoxon signed-rank test). Conclusion The proposed binomial wideband balanced steady-state free precession method is a promising candidate for spectrally selective imaging with enhanced reliability against field inhomogeneities. © 2015 Wiley Periodicals, Inc

Learning Visual Question Answering by Bootstrapping Hard Attention

Attention mechanisms in biological perception are thought to select subsets of perceptual information for more sophisticated processing which would be prohibitive to perform on all sensory inputs. In computer vision, however, there has been relatively little exploration of hard attention, where some information is selectively ignored, in spite of the success of soft attention, where information is re-weighted and aggregated, but never filtered out. Here, we introduce a new approach for hard attention and find it achieves very competitive performance on a recently-released visual question answering datasets, equalling and in some cases surpassing similar soft attention architectures while entirely ignoring some features. Even though the hard attention mechanism is thought to be non-differentiable, we found that the feature magnitudes correlate with semantic relevance, and provide a useful signal for our mechanism's attentional selection criterion. Because hard attention selects important features of the input information, it can also be more efficient than analogous soft attention mechanisms. This is especially important for recent approaches that use non-local pairwise operations, whereby computational and memory costs are quadratic in the size of the set of features.Comment: ECCV 201

Enhanced phase-sensitive SSFP reconstruction for fat-water separation in phased-array acquisitions

Purpose: To propose and assess a method to improve the reliability of phase-sensitive fat–water separation for phased-array balanced steady-state free precession (bSSFP) acquisitions. Phase-sensitive steady-state free precession (PS-SSFP) is an efficient fat–water separation technique that detects the phase difference between neighboring bands in the bSSFP magnetization profile. However, large spatial variations in the sensitivity profiles of phased-array coils can lead to noisy phase estimates away from the coil centers, compromising tissue classification. Materials and Methods: We first perform region-growing phase correction in individual coil images via unsupervised selection of a fat-voxel seed near the peak of each coil's sensitivity profile. We then use an optimal linear combination of phase-corrected images to segregate fat and water signals. The proposed method was demonstrated on noncontrast-enhanced SSFP angiograms of the thigh, lower leg, and foot acquired at 1.5T using an 8-channel coil. Individual coil PS-SSFP with a common seed selection for all coils, individual coil PS-SSFP with coil-wise seed selection, PS-SSFP after coil combination, and IDEAL reconstructions were also performed. Water images reconstructed via PS-SSFP methods were compared in terms of the level of fat suppression and the similarity to reference IDEAL images (signed-rank test). Results: While tissue misclassification was broadly evident across regular PS-SSFP images, the proposed method achieved significantly higher levels of fat suppression (P < 0.005) and increased similarity to reference IDEAL images (P < 0.005). Conclusion: The proposed method enhances fat–water separation in phased-array acquisitions by producing improved phase estimates across the imaging volume. J. Magn. Reson. Imaging 2016;44:148–157. © 2015 Wiley Periodicals, Inc

Measuring cross-lingual semantic similarity across european languages

This paper studies cross-lingual semantic similarity (CLSS) between five European languages (i.e. English, French, German, Spanish and Italian) via unsupervised word embeddings from a cross-lingual lexicon. The vocabulary in each language is projected onto a separate high-dimensional vector space, and these vector spaces are then compared using several different distance measures (i.e., correlation, cosine etc.) to measure their pairwise semantic similarities between these languages. A substantial degree of similarity is observed between the vector spaces learned from corpora of the European languages. Null hypothesis testing and bootstrap methods (by resampling without replacement) are utilized to verify the results. © 2017 IEEE

Functional subdomains within scene-selective cortex: Parahippocampal place area, retrosplenial complex, and occipital place area

Functional MRI studies suggest that at least three brain regions in human visual cortex-the parahippocampal place area (PPA), retrosplenial complex (RSC), and occipital place area (OPA; often called the transverse occipital sulcus)-represent large-scale information in natural scenes. Tuning of voxels within each region is often assumed to be functionally homogeneous. To test this assumption, we recorded blood oxygenation level-dependent responses during passive viewing of complex natural movies. We then used a voxelwise modeling framework to estimate voxelwise category tuning profiles within each scene-selective region. In all three regions, cluster analysis of the voxelwise tuning profiles reveals two functional subdomains that differ primarily in their responses to animals, man-made objects, social communication, and movement. Thus, the conventional functional definitions of the PPA, RSC, and OPA appear to be too coarse. One attractive hypothesis is that this consistent functional subdivision of scene-selective regions is a reflection of an underlying anatomical organization into two separate processing streams, one selectively biased toward static stimuli and one biased toward dynamic stimuli. © 2016 the authors

Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging

Purpose: The scan-efficiency in multiple-acquisition balanced steady-state free precession imaging can be maintained by accelerating and reconstructing each phase-cycled acquisition individually, but this strategy ignores correlated structural information among acquisitions. Here, an improved acceleration framework is proposed that jointly processes undersampled data across N phase cycles. Methods: Phase-cycled imaging is cast as a profile-encoding problem, modeling each image as an artifact-free image multiplied with a distinct balanced steady-state free precession profile. A profile-encoding reconstruction (PE-SSFP) is employed to recover missing data by enforcing joint sparsity and total-variation penalties across phase cycles. PE-SSFP is compared with individual compressed-sensing and parallel-imaging (ESPIRiT) reconstructions. Results: In the brain and the knee, PE-SSFP yields improved image quality compared to individual compressed-sensing and other tested methods particularly for higher N values. On average, PE-SSFP improves peak SNR by 3.8 ± 3.0 dB (mean ± s.e. across N = 2–8) and structural similarity by 1.4 ± 1.2% over individual compressed-sensing, and peak SNR by 5.6 ± 0.7 dB and structural similarity by 7.1 ± 0.5% over ESPIRiT. Conclusion: PE-SSFP attains improved image quality and preservation of high-spatial-frequency information at high acceleration factors, compared to conventional reconstructions. PE-SSFP is a promising technique for scan-efficient balanced steady-state free precession imaging with improved reliability against field inhomogeneity. Magn Reson Med 78:1316–1329, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicin

Sparse representation of two- and three-dimensional images with fractional Fourier, Hartley, linear canonical, and Haar wavelet transforms

Sparse recovery aims to reconstruct signals that are sparse in a linear transform domain from a heavily underdetermined set of measurements. The success of sparse recovery relies critically on the knowledge of transform domains that give compressible representations of the signal of interest. Here we consider two- and three-dimensional images, and investigate various multi-dimensional transforms in terms of the compressibility of the resultant coefficients. Specifically, we compare the fractional Fourier (FRT) and linear canonical transforms (LCT), which are generalized versions of the Fourier transform (FT), as well as Hartley and simplified fractional Hartley transforms, which differ from corresponding Fourier transforms in that they produce real outputs for real inputs. We also examine a cascade approach to improve transform-domain sparsity, where the Haar wavelet transform is applied following an initial Hartley transform. To compare the various methods, images are recovered from a subset of coefficients in the respective transform domains. The number of coefficients that are retained in the subset are varied systematically to examine the level of signal sparsity in each transform domain. Recovery performance is assessed via the structural similarity index (SSIM) and mean squared error (MSE) in reference to original images. Our analyses show that FRT and LCT transform yield the most sparse representations among the tested transforms as dictated by the improved quality of the recovered images. Furthermore, the cascade approach improves transform-domain sparsity among techniques applied on small image patches. © 2017 Elsevier Lt

Targeted vessel reconstruction in non-contrast-enhanced steady-state free precession angiography

Image quality in non-contrast-enhanced (NCE) angiograms is often limited by scan time constraints. An effective solution is to undersample angiographic acquisitions and to recover vessel images with penalized reconstructions. However, conventional methods leverage penalty terms with uniform spatial weighting, which typically yield insufficient suppression of aliasing interference and suboptimal blood/background contrast. Here we propose a two-stage strategy where a tractographic segmentation is employed to auto-extract vasculature maps from undersampled data. These maps are then used to incur spatially adaptive sparsity penalties on vascular and background regions. In vivo steady-state free precession angiograms were acquired in the hand, lower leg and foot. Compared with regular non-adaptive compressed sensing (CS) reconstructions (CSlow), the proposed strategy improves blood/background contrast by 71.3±28.9% in the hand (mean±s.d. across acceleration factors 1-8), 30.6±11.3% in the lower leg and 28.1±7.0% in the foot (signed-rank test, P&lt; 0.05 at each acceleration). The proposed targeted reconstruction can relax trade-offs between image contrast, resolution and scan efficiency without compromising vessel depiction. © 2016 John Wiley & Sons, Ltd

Phase-sensitive reconstruction for fat-water separation in multi-coil acquisitions [Çok Kanalli Verilerde Faza Duyarli Su-Yaǧ Ayrimi için Geriçatim Tekniǧi]

Phase-sensitive steady-state free precession (PS-SSFP) is an effective technique for separating fat and water tissues, based on the phase difference between balanced steady-state free precession (bSSFP) bands. However, in phased-array coils, spatial sensitivity variations lead to noisy data away from coil centers and thereby degrade tissue classification. In this paper, we propose a new method to improve robustness of phase-sensitive fat-water separation against sensitivity variations. © 2016 IEEE