A rapid micro-magnetic resonance imaging scanning for three-dimensional reconstruction of peripheral nerve fascicles

The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual workload and poor image registration. Micro-magnetic resonance imaging（Micro-MRI）, an emerging radiology technique, has been used to report results in the brain, liver and tumor tissues. However, micro-MRI usage for obtaining intraneural structures has not been reported. The aim of this study was to present a new imaging method for three-dimensional reconstruction of peripheral nerve fascicles by ~1T micro-MRI. Freshly harvested sciatic nerve samples from an amputated limb were divided into four groups. Two different scanning conditions（Mannerist Solution/GD-DTPA contrast agent, distilled water） were selected, and both T1 and T2 phases programmed for each scanning condition. Three clinical surgeons evaluated the quality of the images via a standardized scale. Moreover, to analyze deformation of the two-dimensional image, the nerve diameter and total area of the micro-MRI images were compared after hematoxylin-eosin staining. The results show that rapid micro-MRI imaging method can be used for three-dimensional reconstruction of the fascicle structure. Nerve sample immersed in contrast agent（Mannerist Solution/GD-DTPA） and scanned in the T1 phase was the best. Moreover, the nerve sample was scanned freshly and can be recycled for other procedures. MRI images show better stability and smaller deformation compared with histological images. In conclusion, micro-MRI provides a feasible and rapid method for three-dimensional reconstruction of peripheral nerve fascicles, which can clearly show the internal structure of the peripheral nerve.

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning(RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional(3D)imaging with nanometer-sized resolvable features.The size of the volume that can be imaged is almost arbitrary,limited only by the penetration depth and the available scanning time.Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors.The proposed 3D reconstruction method“RAPID”relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth.It is then trained to reproduce equal fidelity from much fewer angles.After training,it performs with similar fidelity on the hitherto unexamined portions of the object,previously not shown during training,with a limited set of acquisitions.In our experimental demonstration,the nominal number of angles was 349 and the reduced number of angles was 21,resulting in a×140 aggregate speedup over a volume of 4.48×93.18×3.92μm^(3) and with(14 nm)^(3) feature size,i.e.-10^(8) voxels.RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way.We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

In-service Structural Health Monitoring of a Full-scale Composite Horizontal Tail

In-service structural health monitoring（SHM） technologies are critical for the utilization of composite aircraft structures. We developed a Lamb wave-based in-service SHM technology using built-in piezoelectric actuator/sensor networks to monitor delamination extension in a full-scale composite horizontal tail. The in-service SHM technology combine of damage rapid monitoring（DRM） stage and damage imaging diagnosis（DID） stage allows for real-time monitoring and long term tracking of the structural integrity of composite aircraft structures. DRM stage using spearman rank correlation coeffi cient was introduced to generate a damage index which can be used to monitor the trend of damage extension. The DID stage based on canonical correlation analysis aimed at intuitively highlighting structural damage regions in two-dimensional images. The DRM and DID stages were trialed by an in-service SHM experiment of CFRP T-joint. Finally, the detection capability of the in-service SHM technology was verified in the SHM experiment of a full-scale composite horizontal tail. Experimental results show that the rapid monitoring method effectively monitors the damage occurrence and extension tendency in real time; damage imaging diagnosis results are consistent with those from the failure model of the composite horizontal tail structure.

Rapid and robust medical image elastic registration using mean shift algorithm

In landmark-based image registration, estimating the landmark correspondence plays an important role. In this letter, a novel landmark correspondence estimation technique using mean shift algorithm is proposed. Image corner points are detected as landmarks and mean shift iterations are adopted to find the most probable corresponding point positions in two images. Mutual information between intensity of two local regions is computed to eliminate mis-matching points to improve the stability of corresponding estimation correspondence landmarks is exact. The proposed experiments of various mono-modal medical images. Multi-level estimation （MLE） technique is proposed Experiments show that the precision in location of technique is shown to be feasible and rapid in the