2014.bib
@article{Zhao2014,
author = {Zhao, Fengjun and Liu, Junting and Qu, Xiaochao and Xu, Xianhui and Chen, Xueli and Yang, Xiang and Cao, Feng and Liang, Jimin and Tian, Jie},
doi = {10.1088/0031-9155/59/24/7777},
file = {:E$\backslash$:/Mendeley Papers/2014/Unknown/2014 - Unknown - In vivo quantitative evaluation of vascular parameters for angiogenesis based on sparse principal component analysis an.pdf:pdf},
issn = {13616560},
journal = {Physics in Medicine and Biology},
keywords = {aggregated boosted trees,quantitative evaluation,sparse principal component analysis,vascular parameters},
number = {24},
pages = {7777--7791},
title = {{In vivo quantitative evaluation of vascular parameters for angiogenesis based on sparse principal component analysis and aggregated boosted trees}},
volume = {59},
year = {2014}
}
@article{Zhang2014,
abstract = {Combining two or more imaging modalities to provide complementary information has become commonplace in clinical practice and in preclinical and basic biomedical research. By incorporating the structural information provided by computed tomography (CT) or magnetic resonance imaging (MRI), the ill poseness nature of bioluminescence tomography (BLT) can be reduced significantly, thus improve the accuracies of reconstruction and in vivo quantification. In this paper, we present a small animal imaging system combining multi-view and multi-spectral BLT with MRI. The independent MRI-compatible optical device is placed at the end of the clinical MRI scanner. The small animal is transferred between the light tight chamber of the optical device and the animal coil of MRI via a guide rail during the experiment. After the optical imaging and MRI scanning procedures are finished, the optical images are mapped onto the MRI surface by interactive registration between boundary of optical images and silhouette of MRI. Then, incorporating the MRI structural information, a heterogeneous reconstruction algorithm based on finite element method (FEM) with L 1 normalization is used to reconstruct the position, power and region of the light source. In order to validate the feasibility of the system, we conducted experiments of nude mice model implanted with artificial light source and quantitative analysis of tumor inoculation model with MDA-231-GFP-luc. Preliminary results suggest the feasibility and effectiveness of the prototype system.},
author = {Zhang, Jun and Chen, Duofang and Liang, Jimin and Xue, Huadan and Lei, Jing and Wang, Qin and Chen, Dongmei and Meng, Ming and Jin, Zhengyu and Tian, Jie},
doi = {10.1364/BOE.5.001861},
file = {:E$\backslash$:/Mendeley Papers/2014/Unknown/2014 - Unknown - Incorporating MRI structural information into bioluminescence tomography system , heterogeneous reconstruction and in.pdf:pdf},
issn = {2156-7085},
journal = {Biomedical Optics Express},
number = {6},
pages = {1861},
pmid = {24940545},
title = {{Incorporating MRI structural information into bioluminescence tomography: system, heterogeneous reconstruction and in vivo quantification}},
url = {https://www.osapublishing.org/boe/abstract.cfm?uri=boe-5-6-1861},
volume = {5},
year = {2014}
}
@article{Cao2014,
author = {Cao, Xin and Chen, Xueli and Kang, Fei and Lin, Yenan and Liu, Muhan and Hu, Hao and Nie, Yongzhan and Wu, Kaichun and Wang, Jing and Liang, Jimin and Tian, Jie},
doi = {10.1364/BOE.5.003660},
file = {:E$\backslash$:/Mendeley Papers/2014/Unknown/2014 - Unknown - Performance evaluation of endoscopic Cerenkov luminescence imaging system in vitro and pseudotumor studies.pdf:pdf},
issn = {2156-7085},
journal = {Biomedical Optics Express},
number = {10},
pages = {3660},
pmid = {25360380},
title = {{Performance evaluation of endoscopic Cerenkov luminescence imaging system: in vitro and pseudotumor studies}},
url = {https://www.osapublishing.org/boe/abstract.cfm?uri=boe-5-10-3660},
volume = {5},
year = {2014}
}
@article{Zhang2013,
abstract = {Local energy pattern, a statistical histogram-based representation, is proposed for texture classification. First, we use normalized local-oriented energies to generate local feature vectors, which describe the local structures distinctively and are less sensitive to imaging conditions. Then, each local feature vector is quantized by self-adaptive quantization thresholds determined in the learning stage using histogram specification, and the quantized local feature vector is transformed to a number by N-nary coding, which helps to preserve more structure information during vector quantization. Finally, the frequency histogram is used as the representation feature. The performance is benchmarked by material categorization on KTH-TIPS and KTH-TIPS2-a databases. Our method is compared with typical statistical approaches, such as basic image features, local binary pattern (LBP), local ternary pattern, completed LBP, Weber local descriptor, and VZ algorithms (VZ-MR8 and VZ-Joint). The results show that our method is superior to other methods on the KTH-TIPS2-a database, and achieving competitive performance on the KTH-TIPS database. Furthermore, we extend the representation from static image to dynamic texture, and achieve favorable recognition results on the University of California at Los Angeles (UCLA) dynamic texture database.},
author = {Zhang, Jun and Liang, Jimin and Zhao, Heng},
doi = {10.1109/TIP.2012.2214045},
file = {:E$\backslash$:/Mendeley Papers/2013/IEEE Transactions on Image Processing/2013 - IEEE Transactions on Image Processing - Local energy pattern for texture classification using self-adaptive quantization threshol.pdf:pdf},
isbn = {1057-7149},
issn = {10577149},
journal = {IEEE Transactions on Image Processing},
keywords = {Dynamic texture,local energy pattern (LEP),self-adaptive quantization thresholds,steerable filter,texture representation},
number = {2},
pages = {31--42},
pmid = {22910113},
title = {{Local energy pattern for texture classification using self-adaptive quantization thresholds}},
volume = {22},
year = {2013}
}
@article{Chen2013,
abstract = {PURPOSE: The appearance of x-ray luminescence computed tomography (XLCT) opens new possibilities to perform molecular imaging by x ray. In the previous XLCT system, the sample was irradiated by a sequence of narrow x-ray beams and the x-ray luminescence was measured by a highly sensitive charge coupled device (CCD) camera. This resulted in a relatively long sampling time and relatively low utilization of the x-ray beam. In this paper, a novel cone beam x-ray luminescence computed tomography strategy is proposed, which can fully utilize the x-ray dose and shorten the scanning time. The imaging model and reconstruction method are described. The validity of the imaging strategy has been studied in this paper. METHODS: In the cone beam XLCT system, the cone beam x ray was adopted to illuminate the sample and a highly sensitive CCD camera was utilized to acquire luminescent photons emitted from the sample. Photons scattering in biological tissues makes it an ill-posed problem to reconstruct the 3D distribution of the x-ray luminescent sample in the cone beam XLCT. In order to overcome this issue, the authors used the diffusion approximation model to describe the photon propagation in tissues, and employed the sparse regularization method for reconstruction. An incomplete variables truncated conjugate gradient method and permissible region strategy were used for reconstruction. Meanwhile, traditional x-ray CT imaging could also be performed in this system. The x-ray attenuation effect has been considered in their imaging model, which is helpful in improving the reconstruction accuracy. RESULTS: First, simulation experiments with cylinder phantoms were carried out to illustrate the validity of the proposed compensated method. The experimental results showed that the location error of the compensated algorithm was smaller than that of the uncompensated method. The permissible region strategy was applied and reduced the reconstruction error to less than 2 mm. The robustness and stability were then evaluated from different view numbers, different regularization parameters, different measurement noise levels, and optical parameters mismatch. The reconstruction results showed that the settings had a small effect on the reconstruction. The nonhomogeneous phantom simulation was also carried out to simulate a more complex experimental situation and evaluated their proposed method. Second, the physical cylinder phantom experiments further showed similar results in their prototype XLCT system. With the discussion of the above experiments, it was shown that the proposed method is feasible to the general case and actual experiments. CONCLUSIONS: Utilizing numerical simulation and physical experiments, the authors demonstrated the validity of the new cone beam XLCT method. Furthermore, compared with the previous narrow beam XLCT, the cone beam XLCT could more fully utilize the x-ray dose and the scanning time would be shortened greatly. The study of both simulation experiments and physical phantom experiments indicated that the proposed method was feasible to the general case and actual experiments.},
author = {Chen, Dongmei and Zhu, Shouping and Yi, Huangjian and Zhang, Xianghan and Chen, Duofang and Liang, Jimin and Tian, Jie},
doi = {10.1118/1.4790694},
file = {:E$\backslash$:/Mendeley Papers/2013/Unknown/2013 - Unknown - Cone beam x-ray luminescence computed tomography A feasibility study.pdf:pdf},
issn = {00942405},
journal = {Medical Physics},
keywords = {3D reconstruction,X-ray luminescence,computed tomography,cone beam},
number = {3},
pages = {1--14},
pmid = {23464291},
title = {{Cone beam x-ray luminescence computed tomography: A feasibility study}},
volume = {40},
year = {2013}
}
@article{Yang2013,
abstract = {Modeling light propagation in the whole body is essential and necessary for optical imaging. However, non-scattering, low-scattering and high absorption regions commonly exist in biological tissues, which lead to inaccuracy of the existing light transport models. In this paper, a novel hybrid light transport model that couples the simplified spherical harmonics approximation (SPN) with the radiosity theory (HSRM) was presented, to accurately describe light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities. In the model, the radiosity theory was used to characterize the light transport in non-scattering regions and the SPN was employed to handle the scattering problems, including subsets of low-scattering and high absorption. A Neumann source constructed by the light transport in the non-scattering region and formed at the interface between the non-scattering and scattering regions was superposed into the original light source, to couple the SPN with the radiosity theory. The accuracy and effectiveness of the HSRM was first verified with both regular and digital mouse model based simulations and a physical phantom based experiment. The feasibility and applicability of the HSRM was then investigated by a broad range of optical properties. Lastly, the influence of depth of the light source on the model was also discussed. Primary results showed that the proposed model provided high performance for light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities.},
author = {Yang, Defu and Chen, Xueli and Peng, Zhen and Wang, Xiaorui and Ripoll, Jorge and Wang, Jing and Liang, Jimin},
doi = {10.1364/BOE.4.002209},
file = {:E$\backslash$:/Mendeley Papers/2013/Unknown/2013 - Unknown - Light transport in turbid media with non- scattering , low-scattering and high absorption heterogeneities based on hybr.pdf:pdf},
isbn = {doi:10.1364/BOE.4.002209},
issn = {2156-7085},
journal = {Biomedical Optics Express},
number = {10},
pages = {2209},
pmid = {24156077},
title = {{Light transport in turbid media with non-scattering, low-scattering and high absorption heterogeneities based on hybrid simplified spherical harmonics with radiosity model}},
url = {https://www.osapublishing.org/boe/abstract.cfm?uri=boe-4-10-2209},
volume = {4},
year = {2013}
}
@article{Zhu2012,
abstract = {In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion.},
author = {Zhu, Shouping and Dong, Di and Birk, Udo Jochen and Rieckher, Matthias and Tavernarakis, Nektarios and Qu, Xiaochao and Liang, Jimin and Tian, Jie and Ripoll, Jorge},
doi = {10.1109/TMI.2012.2188836},
file = {:E$\backslash$:/Mendeley Papers/2012/Unknown/2012 - Unknown - Automated Motion Correction for in-vivo Optical Projection Tomography.pdf:pdf},
isbn = {0278-0062 VO - 31},
issn = {02780062},
journal = {IEEE Transactions on Medical Imaging},
keywords = {Helgason-Ludwig consistency condition (HLCC),motion correction,optical projection tomography (OPT)},
number = {7},
pages = {1358--1371},
pmid = {22374352},
title = {{Automated motion correction for in vivo optical projection tomography}},
volume = {31},
year = {2012}
}
@article{Yang2012,
abstract = {The naturally occurring aurora phenomenon is a dynamically evolving process. Taking temporal information into consideration, the auroral image sequence analysis is more reasonable and desirable than using static images only. However, the enormous richness of space structures and temporal variations make automatic auroral sequence analysis a particularly challenging task. In this paper, a hidden Markov model (HMM) based representation method including features of spatial texture and dynamic evolution is presented to characterize auroral image sequences captured by all-sky imagers (ASIs). The uniform local binary patterns are employed to describe the 2-D space structures of ASI images. HMM is feasible to characterize the doubly stochastic process involved in the auroral evolution-measurable polar light activities and hidden dynamic plasma processes. We present an affine log-likelihood normalization technique to manage the sequences with different lengths. The proposed method is used in the automatic recognition of four primary categories of ASI auroral observations between the years 2003 and 2009 at the Yellow River Station, Ny-Alesund, Svalbard. The supervised classification results on manually labeled data in 2003 demonstrate the effectiveness of the proposed technique. Compared with frame-based classification, the higher accuracies and the lower rejection rates show the advantages of the sequence-based-method. The occurrence distributions of the four aurora categories were obtained through automatic classification of data gathered from 2004 to 2009. Their agreement with the multiple-wavelength intensity distribution of the dayside aurora and the conclusions made from the frame-based method further illustrate the validity of our method on auroral representation and classification.},
author = {Yang, Qiuju and Liang, Jimin and Hu, Zejun and Zhao, Heng},
doi = {10.1109/TGRS.2012.2195667},
file = {:E$\backslash$:/Mendeley Papers/2012/Unknown/2012 - Unknown - Auroral Sequence Representation and Classification Using Hidden Markov Models.pdf:pdf},
isbn = {0196-2892},
issn = {01962892},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
keywords = {Affine log-likelihood normalization,auroral sequence representation,frame-based classification,hidden Markov model (HMM),sequence-based classification},
number = {12},
pages = {5049--5060},
title = {{Auroral sequence representation and classification using hidden markov models}},
volume = {50},
year = {2012}
}
@article{Wang2010,
abstract = {A spatial texture based representation method including features of intensity, shape and texture, was utilized to characterize all-sky auroral images. The combination of the local binary pattern (LBP) operator and a delicately designed block partition scheme achieved both global shapes and local textures capabilities. The representation method was used in automatic recognition of four primary categories of discrete dayside aurora using observations between years 2003-2009 at the Yellow River Station, Nylesund, Svalbard. The supervised classification results on labeled data in 2003 were in accordance with the labeling by scientists considering both spectral and morphological information. The occurrence distributions of the four categories were obtained through automatic classification of data between 2004-2009, which confirm the multiple-wavelength intensity distribution of dayside aurora, and further provide morphological interpretation of auroral types.},
author = {Wang, Qian and Liang, Jimin and Hu, Ze Jun and Hu, Hai Hong and Zhao, Heng and Hu, Hong Qiao and Gao, Xinbo and Yang, Huigen},
doi = {10.1016/j.jastp.2010.01.011},
file = {:E$\backslash$:/Mendeley Papers/2010/Unknown/2010 - Unknown - Author ' s personal copy Spatial texture based automatic classification of dayside aurora in all-sky images.pdf:pdf},
issn = {13646826},
journal = {Journal of Atmospheric and Solar-Terrestrial Physics},
keywords = {Auroral morphology,Automatic classification,Dayside aurora,Local binary patterns},
number = {5-6},
pages = {498--508},
title = {{Spatial texture based automatic classification of dayside aurora in all-sky images}},
volume = {72},
year = {2010}
}