2022
2022
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Record 313 of
Title:Intelligent detection method for seeding timing in sapphire processing
Author(s):Cao, Jingyang(1,2); Qiao, Tiezhu(1,2); Zhang, Haifeng(3); Yan, Gaowei(4); Dong, Huijie(1)Source: Measurement: Journal of the International Measurement Confederation Volume: 201 Issue: DOI: 10.1016/j.measurement.2022.111745 Published: September 30, 2022Abstract:In sapphire processing by the Kyropoulos method, the detection of seeding timing is the core technology. Existing detection methods are incapable of tracking spoke feature motion on the liquid surface and cannot effectively guide sapphire seeding. Therefore, this paper proposes an innovative visual-perturbation-velocity-fitting method for sapphire seeding timing detection. First, the concept of perturbation velocity, which can reflect the flow state of the melt surface, is presented. Then, the position of spoke feature points is obtained by computer vision and calculated by multi-frame interactive periodic detection. The fitting function model corresponding to the perturbation velocity in different flow states is established. Finally, the seeding timing is determined by the transition of the flow state and the stability of the flow. The experimental results show that the proposed method can improve the seeding success rate from 76.7% to 93.3% and the average successful seeding time from 5.6 h to 4.5 h. ? 2022 Elsevier LtdAccession Number: 20223512630818 -
Record 314 of
Title:Development of a flat-field-response, four-channel x-ray imaging instrument for hotspot asymmetry studies
Author(s):Xu, Jie(1,2); Zhang, Xing(3); Mu, Baozhong(1,2); Chen, Liang(1,2); Li, Wenjie(1,2); Xu, Xinye(1,2); Li, Mingtao(1,2); Wang, Xin(1,2); Dong, Jianjun(3); Wang, Feng(3); He, Junhua(4)Source: Review of Scientific Instruments Volume: 93 Issue: 10 DOI: 10.1063/5.0106990 Published: October 1, 2022Abstract:Here, we describe a flat-field-response, four-channel x-ray imaging instrument developed to study hotspot asymmetries in inertial-confinement fusion experiments. We discuss the details of its design and optical characterization, the diagnostic deployment of the device, and experiments with it. We achieved a spatial-response flatness better than ～8.4% within a ±200 μm field of view (FOV), with a spatial resolution of ～4 μm at the center of the FOV. We used the system to characterize the low-order asymmetry of the implosion hotspot, and we obtained improved results after adjustments to improve the irradiation symmetry. Due to the flat-field-response characteristic, the versatile instrument also has the potential to be applied to diagnostics for the hotspot electron temperature and the Rayleigh-Taylor instability. ? 2022 Author(s).Accession Number: 20224513057503 -
Record 315 of
Title:RF and microwave photonic signal generation and processing based on Kerr micro-combs
Author(s):Sun, Yang(1); Tan, Mengxi(2); Wu, Jiayang(1); Xu, Xingyuan(3); Li, Yang(1); Chu, Sai T.(4); Little, Brent E.(5); Morandotti, Roberto(6); Mitchell, Arnan(2); Moss, David J.(1)Source: Proceedings of SPIE - The International Society for Optical Engineering Volume: 12000 Issue: DOI: 10.1117/12.2607905 Published: 2022Abstract:We demonstrate a radio frequency (RF) phase-encoded signal generator as well as a user-defined RF arbitrary waveform generator (AWG) based on a soliton crystal micro-comb generated by an integrated MRR with a free spectral range of ~49 GHz. Owing to the soliton crystal's robust and stable generation as well as the high intrinsic efficiency, RF phase-encoded signal generators and AWGs with simple operation and fast reconfiguration are realized. The soliton crystal micro-comb provides 60 wavelengths for RF phase-encoded signal generators, achieving a phase encoding speed of 5.95 Gb/s and a high pulse compression ratio of 29.6. Over 80 wavelengths are employed for the AWGs, achieving tunable square waveforms with a duty cycle ratio ranging from 10% to 90%, sawtooth waveforms with tunable slope ratios from 0.2 to 1, and symmetric concave quadratic chirp waveforms. Our system has great potential to achieve RF and microwave photonic signal generation and processing with low cost and footprint. ? 2022Accession Number: 20221912073737 -
Record 316 of
Title:Transformer-based factorized encoder for classification of pneumoconiosis on 3D CT images
Author(s):Huang, Yingying(1,2,3); Si, Yang(4,5); Hu, Bingliang(3); Zhang, Yan(6); Wu, Shuang(6); Wu, Dongsheng(6,7); Wang, Quan(1,3)Source: Computers in Biology and Medicine Volume: 150 Issue: DOI: 10.1016/j.compbiomed.2022.106137 Published: November 2022Abstract:In the past decade, deep learning methods have been implemented in the medical image fields and have achieved good performance. Recently, deep learning algorithms have been successful in the evaluation of diagnosis on lung images. Although chest radiography (CR) is the standard data modality for diagnosing pneumoconiosis, computed tomography (CT) typically provides more details of the lesions in the lung. Thus, a transformer-based factorized encoder (TBFE) was proposed and first applied for the classification of pneumoconiosis depicted on 3D CT images. Specifically, a factorized encoder consists of two transformer encoders. The first transformer encoder enables the interaction of intra-slice by encoding feature maps from the same slice of CT. The second transformer encoder explores the inter-slice interaction by encoding feature maps from different slices. In addition, the lack of grading standards on CT for labeling the pneumoconiosis lesions. Thus, an acknowledged CR-based grading system was applied to mark the corresponding pneumoconiosis CT stage. Then, we pre-trained the 3D convolutional autoencoder on the public LIDC-IDRI dataset and fixed the parameters of the last convolutional layer of the encoder to extract CT feature maps with underlying spatial structural information from our 3D CT dataset. Experimental results demonstrated the superiority of the TBFE over other 3D-CNN networks, achieving an accuracy of 97.06%, a recall of 89.33%, precision of 90%, and an F1-score of 93.33%, using 10-fold cross-validation. ? 2022 Elsevier LtdAccession Number: 20224012836419 -
Record 317 of
Title:Investigating on Wideband Phase-Modulation to Amplitude-Modulation Conversion Based on Chromatic Dispersion in Fiber
Author(s):Jin, Ya(1,2); Chen, Yinfang(3); Xie, Zhuang(1,2); Xu, Changda(1,2); Zhu, Huatao(4); Zhu, Ninghua(1)Source: IEEE Photonics Journal Volume: 14 Issue: 4 DOI: 10.1109/JPHOT.2022.3197209 Published: August 1, 2022Abstract:We investigate on the wideband phase-modulation to amplitude-modulation (PM-AM) conversion based on the chromatic dispersion in fiber. To overcome the shortcomings of the single-tone or dual-tone modulation-based model in previous researches, we present a more intuitive time-frequency analysis method for the propagation of phase-modulated signals in dispersive fibers, and give the physical picture for the temporal waveform changes. By analyzing the amplitude variation near the transition zone, we establish a bit-by-bit correspondence between the pulse waveforms and the actual modulated data, and realized the non-return-to-zero (NRZ) differential phase-shift keying (DPSK) demodulation. Furthermore, the effect of fiber length and bit rate on PM-AM conversion is also investigated quantitatively and experimentally. ? 2009-2012 IEEE.Accession Number: 20223412601244 -
Record 318 of
Title:Infrared dim and small target detection: A review
Author(s):Han, Jinhui(1); Wei, Yantao(2); Peng, Zhenming(3); Zhao, Qian(1); Chen, Yaohong(4); Qin, Yao(5); Li, Nan(1)Source: Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering Volume: 51 Issue: 4 DOI: 10.3788/IRLA20210393 Published: April 25, 2022Abstract:Infrared dim and small target detection systems can be installed into a wide range of platforms, and has important practical value in the fields of infrared early warning, guidance and so on. However, it is challenging to detect dim and small target in complex background due to the low signal to noise ratio and radical change of background. Consequently, dim and small target detection in complex background is hotspot and hard pot of related field. In this paper, the previous works on IR dim and small target detection were divided into single-frame based (including methods based on local information and nonlocal information) and multi-frame based (including methods based on associated checking and directed calculation), and further the principles, advantages and drawbacks of these methods were analyzed. Finally, the comments and predictions on the development of IR dim and small target detection in the future were provided. Our work is not only a tutorial for the beginner in terms of current works and development trends, but also a reference for other researchers. Copyright ?2022 Infrared and Laser Engineering. All rights reserved.Accession Number: 20221912084173 -
Record 319 of
Title:Identification and separation of chiral particles by focused circularly polarized vortex beams
Author(s):Zhang, Yanan(1,2); Li, Manman(1); Yan, Shaohui(1); Zhou, Yuan(1,2); Gao, Wenyu(1,2); Yao, Baoli(1,2,3)Source: Journal of the Optical Society of America A: Optics and Image Science, and Vision Volume: 39 Issue: 8 DOI: 10.1364/JOSAA.462817 Published: August 2022Abstract:The identification and separation of chiral substances are of importance in the biological, chemical, and pharmaceutical industries. Here, we demonstrate that a focused circularly polarized vortex beam can, in the focal plane, selectively trap and rotate chiral dipolar particles via radial and azimuthal optical forces. The handedness and topological charge of the incident beam have strong influence on identifying and separating behavior: left- and right-handed circular polarizations lead to opposite effects on the particle of trapping and rotating, while the sign of topological charge will change the particle’s rotation direction. Such effects are a direct result of the handedness and topological charge manifesting themselves in the directions of the spin angular momentum (SAM) and Poynting vector. The research provides insight into the chiral light–matter interaction and may find potential application in the identification and separation of chiral nanoparticles. ? 2022 Optica Publishing GroupAccession Number: 20223112459408 -
Record 320 of
Title:Reconstruction of weak near-infrared images in methyl red-doped nematic liquid crystals via stochastic resonance
Author(s):Ji, Wentong(1,2); Wang, Zhaolu(1); Huang, Nan(1); Liu, Hongjun(1,3)Source: Optics Express Volume: 30 Issue: 17 DOI: 10.1364/OE.462740 Published: August 15, 2022Abstract:We propose a near-infrared (NIR) image reconstruction method based on molecular reorientation of nematic liquid crystals (NLCs) doped with the azo-dye methyl red (MR). The signal can be recovered at the expense of noise via stochastic resonance. The numerical results show that image reconstruction based on the molecular reorientation in a magnetic field can be achieved when the input light intensity is 0.9W/cm2, this is due to the strong enhancement of the nonlinear optical response in MR doped-NLCs. The cross-correlation coefficient is increased from 0.26 to 0.54, and the maximum cross-correlation gain is 2.25. The results suggest a potential method in NIR weak optical image processing under noisy environments. ? 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.Accession Number: 20223312556529 -
Record 321 of
Title:Cross-modality Multi-encoder Hybrid Attention U-Net for Lung Tumors Images Segmentation
Author(s):Zhou, Tao(1,2); Dong, Yali(1); Liu, Shan(1); Lu, Huiling(3); Ma, Zongjun(4); Hou, Senbao(1); Qiu, Shi(5)Source: Guangzi Xuebao/Acta Photonica Sinica Volume: 51 Issue: 4 DOI: 10.3788/gzxb20225104.0410006 Published: April 25, 2022Abstract:The lung lesions segmentation in medical imaging is an important task. However, there are still some challenges. The lesions delineation relies on manual segmentation by experienced clinicians, which is time-consuming and labor-intensive due to the complex anatomical structure of the human body; Lung tumor images have the characteristics of low contrast, different size and shape of the lesions, and variable location of the lesions, and are characterized by unbalanced data distribution. U-Net can segment lesions under a small number of datasets and has been widely used in medical image segmentation of lesions and organs. However, U-Net has the following three problems. First, U-Net uses uniform parameters for each feature map. For lesions of different sizes and complex shapes, the network may have poor spatial perception, which leads to the decline of segmentation performance. Second, U-Net channel dimension doubles with the number of down-sampling, and the feature map of the encoder layer is concatenated to the decoding layer through skip connection. However, in the segmentation task, the importance of different channels to the segmentation task is different. Third, most of the current multi-encoder segmentation networks extract the features of the single-modal target slice and their continuous slices to improve the network segmentation performance, but ignore the ability of different modal medical images to express the characteristics of the lesion. To solve the above problems, this paper proposes the MEAU-Net network to extract complementary features of multi-modals images. First, for the unbalanced data distribution, the Hough transform is used to detect the line of the lung Computed Tomography (CT) image marked by the doctor to obtain the region of interest, and cropped image size from 356 pixel×356 pixel to 50 pixel×50 pixel. Then, for the low contrast of medical image, use exposure fusion image contrast enhancement method improves the contrast between lesion and the background of lung CT image. To extract the features of lesions in multi-modal medical images, this paper proposes a multi-encoder hybrid attention mechanism network MEAU-Net. Positron Emission Tomography (PET) images provide metabolic information of lesions, CT images provide anatomical information of lesions, and Positron Emission Tomography/ Computed Tomography (PET/CT) images combine their advantages and utilize their complementarity and redundancy. MEAU-Net encoder path includes three branches of PET/CT, PET and CT, which are used to extract corresponding modal image features. In the skip connection of the network, hybrid attention mechanism is used, including spatial attention mechanism and channel attention mechanism. The features of PET/CT and CT are used in the spatial attention mechanism to emphasize key areas in the feature map and suppress irrelevant background. The channel attention mechanism extracts the weight value of each channel for the three branches of PET/CT, CT and PET, and then selects the maximum weight value after the three branches sigmoid to multiply the corresponding channel, and assign a higher value to the important channel. The weighting coefficient realizes the selection of important channels. The network inputs the feature map through the hybrid attention mechanism into the corresponding decoder layer, so that the network focuses on the lesion part in medical image, suppresses useless background information, and achieves accurate segmentation of the image lesion. Finally, for the semantic features of different scales of the decoding path, this paper uses a multi-scale feature aggregation block to perform feature mapping on the features of the decoding path, and refine the segmentation of the lesion. We compared our model with 4 classical segmentation model on our dataset, including SegNet, Attention Unet and Wnet. The experiment results show that our model uses multi-modal medical image features to effectively segment lung lesions with complex shapes, and outperforms all other methods in our dataset. The average DSC, Recall, VOE and RVD of MEAU-Net segmentation results are 96.4%, 97.27%, 7.0% and 6.94%, respectively. ? 2022, Science Press. All right reserved.Accession Number: 20221912096717 -
Record 322 of
Title:Underwater imaging system of pulse modulated lidar
Author(s):Xu, Guoquan(1); Li, Guangying(2); Wan, Jianwei(1); Xu, Ke(1); Dong, Guangyan(3); Cheng, Guanghua(4); Wang, Xing(2); Han, Wenjie(3); Ma, Yanxin(5)Source: Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering Volume: 51 Issue: 3 DOI: 10.3788/IRLA20210204 Published: March 25, 2022Abstract:According to the application of underwater target detection, the corresponding 532 nm wavelength lidar system parameters were given. Combining the advantages of streak tube lidar and subcarrier modulated lidar, a prototype of underwater 3D imaging extended range lidar was designed. Compared with the common scheme of microwave modulated laser to generate high frequency pulse, the prototype adopted Q-switch technology to compress laser pulse, and then combined the characteristics of F-P cavity to generate high frequency laser pulse, which had the advantages of high peak power and high output energy. The experimental results show that the imaging distance of the prototype in clear water environment is better than 20 m, and it can capture the target details with a diameter of 9 mm at 13 m. In the turbid water environment, the range-extended capability of signal processing is 81.4%, and the range resolution error is 0.01 m. The experimental results provide a foundation for further improving the imaging range and resolution of underwater lidar and developing underwater imaging equipment. Copyright ?2022 Infrared and Laser Engineering. All rights reserved.Accession Number: 20221511959683 -
Record 323 of
Title:Simulation of the impact of using a novel neutron conversion screen on detector time characteristics and efficiency
Author(s):Liu, Yiheng(1,2,3); He, Kai(1); Wang, Gang(1,2); Gao, Guilong(1); Yan, Xin(1); Xue, Yanhua(1); Chen, Ping(1,3); Yao, Dong(1); Yue, Mengmeng(1); Sheng, Liang(4); Yuan, Xiaohui(5); Tian, Jinshou(1,3)Source: AIP Advances Volume: 12 Issue: 4 DOI: 10.1063/5.0073025 Published: April 1, 2022Abstract:To directly measure the DT neutrons from inertial confinement fusion with a high time resolution, a new type of neutron conversion composed of a CH2 conversion layer, a metal moderation layer, and a CsI secondary electron emission layer is proposed. The conversion screen is based on the principle that recoil protons produced by elastic scattering of the neutrons in CH2 interact with CsI to generate secondary electrons. The moderation layer can filter the energy spectrum of protons to prevent low-energy protons from reaching CsI, which shortens the duration of the secondary electron pulse and improves the temporal resolution of the conversion screen. Based on the Monte Carlo method, both the neutron impulse and background γ-rays response of this conversion screen were calculated. The simulation indicates that the temporal resolution of the conversion screen can reach up to 4.9 ps when the thickness of the gold layer is 100 μm. The detection efficiency of secondary electrons/neutrons can reach 7.4 × 10-3. The detection efficiency of the neutron conversion screen for secondary electrons/γ-rays is an order of magnitude lower than the neutron impulse response, and the response time of γ-rays is 20 ps earlier than the neutron pulses. This means that using this conversion screen is beneficial to distinguish between neutrons and γ-rays and has a good signal-to-noise ratio. ? 2022 Author(s).Accession Number: 20221712039946 -
Record 324 of
Title:Noise reduction and 3D image restoration of single photon counting LiDAR using adaptive gating
Author(s):Chen, Song-Mao(1,2,4); Su, Xiu-Qin(1,2); Hao, Wei(1,2); Zhang, Zhen-Yang(1,2,3); Wang, Shu-Chao(1,2,3); Zhu, Wen-Hua(1,2,3); Wang, Jie(1,2,3)Source: Wuli Xuebao/Acta Physica Sinica Volume: 71 Issue: 10 DOI: 10.7498/aps.71.20211697 Published: May 20, 2022Abstract:Single photon LiDAR is considered as one of the most important tools in acquiring target information with high accuracy under extreme imaging conditions, as it offers single photon sensitivity and picosecond timing resolution. However, such technique sense the scene with the photons reflected by the target, thus resulting in severe degradation of image in presence of strong noise. Range gating with high-speed electronics is an effective way to suppress the noise, unfortunately, such technique suffers from manually selecting the parameters and limited gating width. This paper presents a target information extracting and image restoration method under large observation window, which first obtain the depth distribution of the target and extract the information within the range by analyzing the model of signal and noise, then further improve the image quality by adopting advanced image restoration algorithm and henceforth shows better results than those denoising method that purely relying on hardware. In the experiment, photon-per-pixel (PPP) was as low as 3.020 and signal-to-background ratio (SBR) was as low as 0.106, the proposed method is able to improve SBR with a factor of 19.330. Compared to classical algorithm named cross correlation, the reconstruction signal to noise ratio (RSNR) increased 33.520dB by further cooperating with advanced image restoration algorithm, thus improved the ability of sensing accurate target information under extreme cases. Copyright ? 2022 Acta Physica Sinica. All rights reserved.Accession Number: 20222312193194