Molding a Positive Image

THE increased presence of Chinese companies, a majority of Kenyans and Nigerians believe, is positively impacting their economy.

Magnetoacoustic position imaging for liquid metal in animal interstitial structure

Magnetoacoustic tomography with magnetic induction(MAT-MI),as a new kind of in-vivo imaging method,has potential application value in interstitial fluid research.In this paper,we propose the application of MAT-MI with liquid metal serving as a tracer of the interstitial structure to study its fluid behavior,and use it to implement the positional imaging of the spatial distribution of liquid metal.Owing to the particularity of liquid metal magnetoacoustic pressure(MAP)signals,we propose an envelope analysis method to extract the rising edge of the amplitude envelope of the detected waveform as effective position data.And for the first time,we propose the method of superpositing pixel matrix to achieve the position imaging of liquid metal.Finally,the positional imaging of the liquid metal sample embedded in the gel is achieved to have relatively accurate results.This study provides a method of effectively extracting data and implementing the position imaging for liquid metal in the interstitial structure in the frame of MAT-MI.

Tracking of Labelled Stem Cells Using Molecular MR Imaging in a Mouse Burn Model <i>in Vivo</i>as an Approach to Regenerative Medicine

Therapies based on stem cell transplants offer significant potential in the field of regenerative medicine. Monitoring the fate of the transplanted stem cells in a timely manner is considered one of the main limitations for long-standing success of stem cell transplants. Imaging methods that visualize and track stem cells in vivo non-invasively in real time are helpful towards the development of successful cell transplantation techniques. Novel molecular imaging methods which are non-invasive particularly such as MRI have been of great recent interest. Hence, mouse models which are of clinical relevance have been studied by injecting contrast agents used for labelling cells such as super-paramagnetic iron-oxide (SPIO) nanoparticles for cellular imaging. The MR techniques which can be used to generate positive contrast images have been of much relevance recently for tracking of the labelled cells. Particularly when the off-resonance region in the vicinity of the labeled cells is selectively excited while suppressing the signals from the non-labeled regions by the method of spectral dephasing. Thus, tracking of magnetically labelled cells employing positive contrast in vivo MR imaging methods in a burn mouse model in a non-invasive way has been the scope of this study. The consequences have direct implications for monitoring labeled stem cells at some stage in wound healing. We suggest that our approach can be used in clinical trials in molecular and regenerative medicine.

Determining the imaging plane of a retinal capillary layer in adaptive optical imaging

Even in the early stage,endocrine metabolism disease may lead to micro aneurysms in retinal capillaries whose diameters are less than 10 μm.However,the fundus cameras used in clinic diagnosis can only obtain images of vessels larger than 20 μm in diameter.The human retina is a thin and multiple layer tissue,and the layer of capillaries less than10 μm in diameter only exists in the inner nuclear layer.The layer thickness of capillaries less than 10 μm in diameter is about 40 μm and the distance range to rod＆cone cell surface is tens of micrometers,which varies from person to person.Therefore,determining reasonable capillary layer（CL） position in different human eyes is very difficult.In this paper,we propose a method to determine the position of retinal CL based on the rod＆cone cell layer.The public positions of CL are recognized with 15 subjects from 40 to 59 years old,and the imaging planes of CL are calculated by the effective focal length of the human eye.High resolution retinal capillary imaging results obtained from 17 subjects with a liquid crystal adaptive optics system（LCAOS） validate our method.All of the subjects＇ CLs have public positions from 127 μm to 147 μm from the rod＆cone cell layer,which is influenced by the depth of focus.

Basic Study of Air Leakage Position Based on Thermography Mosaic Technology

When locating the leakage of thermal field of a certain container, it is hard for us to evaluate the leakage with one or several separate thermal infrared images. Instead, panoramic imagery with a wide visual angle and high distinguishability is always needed. However, we can only get images for part of the scene because of the limited visual field of thermography and the large size of the measured object in practical. What is more, the hardware that can be used to get panoramic images is always expensive and cannot be used in large scale. Therefore, this paper introduces image mosaic technology, which can be used to get the intact thermal infrared image of the measured and increase the efficiency of detection. The experiment results demonstrate its effectiveness.

Marine target detection based on Marine-Faster R-CNN for navigation radar plane position indicator images

As a classic deep learning target detection algorithm,Faster R-CNN(region convolutional neural network)has been widely used in high-resolution synthetic aperture radar(SAR)and inverse SAR(ISAR)image detection.However,for most common low-resolution radar plane position indicator(PPI)images,it is difficult to achieve good performance.In this paper,taking navigation radar PPI images as an example,a marine target detection method based on the Marine-Faster R-CNN algorithm is proposed in the case of complex background(e.g.,sea clutter)and target characteristics.The method performs feature extraction and target recognition on PPI images generated by radar echoes with the convolutional neural network(CNN).First,to improve the accuracy of detecting marine targets and reduce the false alarm rate,Faster R-CNN was optimized as the Marine-Faster R-CNN in five respects:new backbone network,anchor size,dense target detection,data sample balance,and scale normalization.Then,JRC(Japan Radio Co.,Ltd.)navigation radar was used to collect echo data under different conditions to build a marine target dataset.Finally,comparisons with the classic Faster R-CNN method and the constant false alarm rate(CFAR)algorithm proved that the proposed method is more accurate and robust,has stronger generalization ability,and can be applied to the detection of marine targets for navigation radar.Its performance was tested with datasets from different observation conditions(sea states,radar parameters,and different targets).