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Importance-aware 3D volume visualization for medical content-based image retrieval-a preliminary study

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虚拟现实与智能硬件（中英文） 2024年第1期6卷 71-81页

作者： Mingjian LI Younhyun JUNG Michael FULHAM Jinman KIM School of Computer Science The University of SydneySydneyNSW 2006Australia School of Computing Gachon UniversitySeongnam 13120South Korea Department of Molecular Imaging Royal Prince Alfred HospitalSydneyNSW 2050Australia

Background A medical content-based image retrieval(CBIR)system is designed to retrieve images from large imaging repositories that are visually similar to a user′s query image.CBIR is widely used in evidence-based diagnosis,teaching,and research.Although the retrieval accuracy has largely improved,there has been limited development toward visualizing important image features that indicate the similarity of retrieved images.Despite the prevalence of 3D volumetric data in medical imaging such as computed tomography(CT),current CBIR systems still rely on 2D cross-sectional views for the visualization of retrieved images.Such 2D visualization requires users to browse through the image stacks to confirm the similarity of the retrieved images and often involves mental reconstruction of 3D information,including the size,shape,and spatial relations of multiple structures.This process is time-consuming and reliant on users'experience.Methods In this study,we proposed an importance-aware 3D volume visualization method.The rendering parameters were automatically optimized to maximize the visibility of important structures that were detected and prioritized in the retrieval process.We then integrated the proposed visualization into a CBIR system,thereby complementing the 2D cross-sectional views for relevance feedback and further analyses.Results Our preliminary results demonstrate that 3D visualization can provide additional information using multimodal positron emission tomography and computed tomography(PETCT)images of a non-small cell lung cancer dataset.

关键词： Volume visualization DVR Medical CBIR retrieval Medical images

retrieval strategy for failed satellite on tether’s optimal balance swing angle

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Journal of Systems Engineering and Electronics 2019年第4期30卷 749-759页

作者： HAN Yanhua HONG Junting College of Astronautics Nanjing University of Aeronautics and Astronautics

A retrieval control strategy for failed satellite,which is connected to a servicing spacecraft by a tether,is studied.The Lagrange analytical mechanics based dynamics modeling for the system composed of a servicing spacecraft,a tether and a failed satellite,is presented under the earth center inertia coordinate system,then model simplification is conducted under the assumption that the failed satellite’s mass is far smaller than the servicing spacecraft’s,meanwhile the tether’s length is far smaller than the size of the servicing spacecraft’s orbit.Analysis shows that the retrieval process is intrinsically unstable as the Coriolis force functions is a negative damping.A retrieval strategy based on only the tether’s tension is designed,resulting in the fastest retrieval speed.In the proposed strategy,firstly,the tether’s swing angle amplitude is adjusted to 45?by deploying/retrieving the tether;then the tether swings freely with fixed length until it reaches negative maximum angle–45?;finally,the tether is retrieved by the pre-assigned exponential law.For simplicity,only the coplanar situation,that the tether swings in the plane of the servicing spacecraft’s orbit,is studied.Numerical simulation verifies the effectiveness of the strategy proposed.

关键词： tethered space tug(TST) retrieval control strategy failed satellite space debris on-orbit service

Investigating the impact of Glyoxal retrieval from MAX-DOAS observations during haze and non-haze conditions in Beijing

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Journal of Environmental Sciences 2019年第6期31卷 296-305页

作者： Zeeshan Javed Cheng Liu Muhammad Fahim Khokhar Chengzhi Xing Wei Tan Muhammad Ahmed Subhani Abdul Rehman Aimon Tanvir School of Earth and Space Sciences University of Science and Technology of China Center for Excellence in Regional Atmospheric Environment Institute of Urban Environment Chinese Academy of Sciences Key Lab of Environmental Optics & Technology Anhui Institute of Optics and Fine Mechanics Chinese Academy of Sciences Anhui Province Key Laboratory of Polar Environment and Global Change USTC Institute of Environmental Sciences and Engineering National University of Sciences and Technology

This study presents the Multi Axis Differential Optical Absorption Spectroscopy(MAXDOAS) measurements for Glyoxal(CHOCHO) in Beijing, China(39.95°N, 116.32°E). CHOCHO is the smallest compound of di-carbonyl group. As a primary sink of CHOCHO, its photolysis with NOx(oxides of nitrogen) results in the production of tropospheric ozone. Therefore,the focus of CHOCHO DOAS measurements is increasing in trend. We did the measurements from 09 May 2017 to 09 September 2017. The study was conducted to compare different retrieval settings in order to reveal best DOAS fit settings for CHOCHO;furthermore, effect of haze and non-haze days on CHOCHO concentration was examined.The root mean square of residual and Differential Slant Column density(dSCD) error was reduced when measurements were done with lower wavelength limit around 432–438 nm and upper intervals around 455–460 nm. Thus, lower wavelength intervals around432–438 nm and upper intervals around 457–460 nm were best for the retrieval of dSCDs for CHOCHO. Meteorological conditions like haze or non-haze days did not have significant effect on DOAS fit parameters. The CHOCHO vertical column densities range from 1.33 E +14 to 9.77 E + 14 molecules/cm2 during the study period with average of 6.16 E +14 molecules/cm2. The results indicated that during haze days CHOCHO concentration was higher because of lower rate of photolysis and atmospheric oxidation potential. Our results did not show any significant weekend effect on CHOCHO atmospheric concentration.

关键词： Glyoxal DOAS retrieval settings Photolysis Haze days

Zero-Shot Medical Image retrieval for Emerging Infectious Diseases Based on Meta-Transfer Learning--Worldwide,2020

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China CDC weekly 2020年第52期2卷 1004-1008页

作者： Yuying Zhao Hanjiang Lai Jian Yin Yewu Zhang Shigui Yang Zhongwei Jia Jiaqi Ma School of Computer Science and Engineering Sun Yat-Sen UniversityGuangzhouGuangdongChina Center for Public Health Surveillance and Information Service Chinese Center for Disease Control and PreventionBeijingChina State Key Laboratory for Diagnosis and Treatment of Infectious Diseases Collaborative Innovation Center for Diagnosis and Treatment of Infectious DiseasesThe First Affiliated HospitalCollege of MedicineZhejiang UniversityHangzhouZhejiangChina School of Public Health Peking UniversityBeijingChina

Introduction:Due to the increasing number of medical images,image retrieval has become an important technique for medical image analytics.Although many content-based image retrieval methods have been proposed,the retrieval of images in datasets related to emerging/new infectious diseases still remain a challenge-mostly due to the lack of historical data.As a result,the current retrieval models have limited functionality in helping doctors make accurate diagnoses of new diseases.Methods:In this paper,we propose a zero-shot retrieval model based on meta-learning and ensemble learning,which can obtain a model with stronger generalizability without using any relevant training data,and thus performs well on new types of test data.Results:The experimental results showed that the proposed method is 3% to 5% higher than the traditional method,which means that our model can retrieve relevant medical images more accurately for newly emerging data types and provide doctors with more effective assistance.Discussion:When a new infectious disease occurs,doctors can use the proposed zero-shot retrieval model to retrieve all relevant cases,quickly find the common problems of patients,find the locations of the new infections,and determine its infectivity as soon as possible.The proposed method is a new computeraided decision support technology for emerging infectious diseases.

关键词： Image image retrieval

retrieval of Atmospheric Temperature and Moisture Vertical Profiles from Satellite Advanced Infrared Sounder Radiances with a New Regularization Parameter Selecting Method

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Journal of Meteorological Research 2016年第3期30卷 356-370页

作者：张堃吴春强李俊 Chinese Academy of Meteorological Sciences Beijing 100081China National Satellite Meteorological Center Beijing 100081China Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-MadisonMadisonWI 53706USA

Considering the characteristics of nonlinear problems,a new method based on the L-curve method and including the concept of entropy was designed to select the regularization parameter in the one-dimensional variational analysis-based sounding retrieval method.In the first iteration,this method uses an empirical regularization parameter derived by minimizing the entropy of variables.During subsequent iterations,it uses the L-curve method to select the regularization parameter in the vicinity of the regularization parameter selected in the last iteration.The new method was employed to select the regularization parameter in retrieving atmospheric temperature and moisture profiles from Atmospheric Infrared Sounder radiance measurements selected from the first day of each month in 2008.The results show that compared with the original L-curve method,the new method yields 5.5%and 2.5%improvements on temperature and relative humidity profiles,respectively.Compared with the discrepancy principle method,the improvements on temperature and relative humidity profiles are 1.6%and 2.0%,respectively.

关键词： Atmospheric Infrared Sounder retrieval entropy L-curve regularization parameter

Fast and robust phase retrieval for masked coherent diffractive imaging

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Photonics Research 2022年第3期10卷 758-768页

作者： Li Song Edmund Y.Lam Department of Electrical and Electronic Engineering The University of Hong KongPokfulamHong KongChina

Conventional phase retrieval algorithms for coherent diffractive imaging(CDI)require many iterations to deliver reasonable results,even using a known mask as a strong constraint in the imaging setup,an approach known as masked CDI.This paper proposes a fast and robust phase retrieval method for masked CDI based on the alternating direction method of multipliers(ADMM).We propose a plug-and-play ADMM to incorporate the prior knowledge of the mask,but note that commonly used denoisers are not suitable as regularizers for complex-valued latent images directly.Therefore,we develop a regularizer based on the structure tensor and Harris corner detector.Compared with conventional phase retrieval methods,our technique can achieve comparable reconstruction results with less time for the masked CDI.Moreover,validation experiments on real in situ CDI data for both intensity and phase objects show that our approach is more than 100 times faster than the baseline method to reconstruct one complex-valued image,making it possible to be used in challenging situations,such as imaging dynamic objects.Furthermore,phase retrieval results for single diffraction patterns show the robustness of the proposed ADMM.

关键词： coherent phase retrieval

retrieval of Liquid Water Path Inside Nonprecipitating Clouds Using TMI Measurements

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Acta meteorologica Sinica 2008年第3期22卷 342-350页

作者：王雨傅云飞王自发刘国胜 Laboratory of Satellite Remote Sensing and Climate Environment School of Earth and Space SciencesUniversity of Science and Technology of China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of Sciences Department of Meteorology Florida State University

Quantitative estimates of liquid water path （LWP） in clouds using satellite measurements are critical to understanding of cloud properties and the assessment of global climate change. In this paper, the relationship between microwave brightness temperature （TB） and LWP in the nonprecipitating clouds is studied by using satellite microwave measurements from the TRMM Microwave Imager （TMI） onboard the Tropical Rainfall Measuring Mission （TRMM）, together with a radiative transfer model for microwave radiance calculations. Radiative transfer modeling shows that the sensitivity is higher at both 37.0- and 85.5-GHz horizontal polarization channels for the LWP retrievals. Also, the differences between the retrieved values responding to TBs of various channels and the theoretical values are displayed by the model. Based upon above simulations, with taking into account the factor of resolution and retrieval bias for a single,channel, a nonprecipitating cloud LWP in the summer subtropical marine environment retrieval algorithm is formulated by the combination of the two TMI horizontal polarization channels, 37.0 and 85.5 GHz. Moreover,by using TMI measurements （1Bll）, this algorithm is applied to retrieving respectively LWPs for clear sky, nonprecipitating clouds, and typhoon precipitating clouds. In the clear sky case, the LWP cl^anges from -1 to 1 g m-2, and its mean value is about 10^-5 g m^-2. It indicates that, using this combination retrieval algorithm, there are no obvious systemic deviations when the LWP is low enough. The LWP values varying from 0 to 1000 g m^-2 in nonprecipitating clouds are reasonable, and its distribution pattern is very similar to the detected results in the visible channel of Visible and Infrared Scanner （VIRS） on the TRMM. In typhoon precipitating clouds, there is much more proportion of high LWP in the mature phase than the early stage. When surface rainfall rate is lower than 5 mm h^-1, the LWP increases with increasing rainfall rate.

关键词： liquid water path （LWP） TRMM Microwave Imager （TMI） nonprecipitating cloud retrieval

Web3D Learning Framework for 3D Shape retrieval Based on Hybrid Convolutional Neural Networks

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Tsinghua Science and Technology 2020年第1期25卷 93-102页

作者： Wen Zhou Jinyuan Jia Chengxi Huang Yongqing Cheng School of Computer and Information Anhui Normal UniversityWuhu 241002China School of Software Engineering Tongji UniversityShanghai 201804China College of Electronics and Information Engineering Tongji UniversityShanghai 201804China School of Engineering and Computer Science University of HullHullHU6 7RXUK.

With the rapid development of Web3 D technologies, sketch-based model retrieval has become an increasingly important challenge, while the application of Virtual Reality and 3 D technologies has made shape retrieval of furniture over a web browser feasible. In this paper, we propose a learning framework for shape retrieval based on two Siamese VGG-16 Convolutional Neural Networks(CNNs), and a CNN-based hybrid learning algorithm to select the best view for a shape. In this algorithm, the AlexNet and VGG-16 CNN architectures are used to perform classification tasks and to extract features, respectively. In addition, a feature fusion method is used to measure the similarity relation of the output features from the two Siamese networks. The proposed framework can provide new alternatives for furniture retrieval in the Web3 D environment. The primary innovation is in the employment of deep learning methods to solve the challenge of obtaining the best view of 3 D furniture,and to address cross-domain feature learning problems. We conduct an experiment to verify the feasibility of the framework and the results show our approach to be superior in comparison to many mainstream state-of-the-art approaches.

关键词： Web3D sketch-based model retrieval Convolutional Neural Networks(CNNs) best view cross-domain

Non-negative locality-constrained vocabulary tree for finger vein image retrieval

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Frontiers of Computer Science 2019年第2期13卷 318-332页

作者： Kun SU Gongping YANG Lu YANG Peng SU Yilong YIN School of Computer Science and Technology Shandong University Jinan 250101 China School of Mechanical Electrical and Information Engineering Shandong University (Weihai)Weihai 264209 China School of Computer Science and Tech no logy Shandong University of Finance and Econo mics Jinan 250014 China School of Mathematics Dali University Dali 671000 China

Finger vein image retrieval is a biometric identification technology that has recently attracted a lot of attention. It has the potential to reduce the search space and has attracted a considerable amount of research effort recently. It is a challenging problem owing to the large number of images in biometric databases and the lack of efficient retrieval schemes. We apply a hierarchical vocabulary tree modelbased image retrieval approach because of its good scalability and high efficiency. However, there is a large accumulative quantization error in the vocabulary tree (VT) model that may degrade the retrieval precision. To solve this problem, we improve the vector quantization coding in the VT model by introducing a non-negative locality-constrained constraint: the non-negative locality-constrained vocabulary tree-based image retrieval model. The proposed method can effectively improve coding performanee and the discriminative power of local features. Extensive experiments on a large fused finger vein database demonstrate the superiority of our encoding method. Experimental results also show that our retrieval strategy achieves better performanee than other state-of-theart methods, while maintaining low time complexity.

关键词： non-negative locality-constrained vocabulary tree finger vein image retrieval large scale inverted indexing