Hongying Liu

East China Normal University, Shanghai, Shanghai Shi, China

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Publications (17)15.98 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Histological observation of dual-stained colon sections is usually performed by visual observation under a light microscope, or by viewing on a computer screen with the assistance of image processing software in both research and clinical settings. These traditional methods are usually not sufficient to reliably differentiate spatially overlapping chromogens generated by different dyes. Hyperspectral microscopic imaging technology offers a solution for these constraints as the hyperspectral microscopic images contain information that allows differentiation between spatially co-located chromogens with similar but different spectra. In this paper, a hyperspectral microscopic imaging (HMI) system is used to identify methyl green and nitrotetrazolium blue chloride in dual-stained colon sections. Hyperspectral microscopic images are captured and the normalized score algorithm is proposed to identify the stains and generate the co-expression results. Experimental results show that the proposed normalized score algorithm can generate more accurate co-localization results than the spectral angle mapper algorithm. The hyperspectral microscopic imaging technology can enhance the visualization of dual-stained colon sections, improve the contrast and legibility of each stain using their spectral signatures, which is helpful for pathologist performing histological analyses.
    Optics & Laser Technology 01/2014; 64:337–342. · 1.37 Impact Factor
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    ABSTRACT: The purpose of this study was to explore the possibility for analyzing and differentiating between motor and sensory functions of peripheral nerve axons using spectral technology. 10 μm slide section of S1 anterior and posterior rabbit spinal nerve roots were made and then stained with Karnovsky-Roots method for molecular hyperspectral imaging microscopy analysis. In addition, Raman spectra data of nerve axons on each slide was collected after Karnovsky-Roots staining for 30 minutes. Motor axons were differentiated from sensory axons in a nerve axon section hyperspectral image via Spectral angle mapper algorithm. Raman scatterings could be detected near 2110 cm(-1), and 2155 cm(-1) in motor axons after Karnvosky-Roots staining. The value of I2100/I1440 in motor axons are significantly different (P0.001) than in sensory axons after staining for 30 minutes. Motor and sensory nerve axons can be differentiated from their counterparts in 30 minutes by using Raman micro-spectroscopy analysis assisted with Karnovsky-Roots staining.
    International Journal of Clinical and Experimental Medicine 01/2014; 7(10):3253-3257. · 1.42 Impact Factor
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    ABSTRACT: To overcome the shortcomings in the traditional white blood cells (WBCs) identification methods based on the color or gray images captured by light microscopy, a microscopy hyperspectral imaging system was used to analyze the blood smears. The system was developed by coupling an acousto-optic tunable filter (AOTF) adapter to a microscopy and driven by a SPF Model AOTF controller, which can capture hyperspectral images from 550 nm to 1000 nm with the spectral resolution 2-5 nm. Moreover, a combined spatial-spectral algorithm is proposed to segment the nuclei and cytoplasm of WBCs from the microscopy hyperspectral images. The proposed algorithm is based on the pixel-wise improved spectral angle mapper (ISAM) segmentation, followed by the majority voting within the active contour model regions. Experimental results show that the accuracy of the proposed algorithm is 91.06% (nuclei) and 85.59% (cytoplasm), respectively, which is higher than that of the spectral information divergence (SID) algorithm because the new method can jointly use both the spectral and spatial information of blood cells.
    Optics & Laser Technology 12/2013; · 1.37 Impact Factor
  • Bin Gu, Qingli Li, Hongying Liu
    2013 6th International Congress on Image and Signal Processing (CISP); 12/2013
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    ABSTRACT: Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.
    Journal of Biomedical Optics 10/2013; 18(10):100901. · 2.75 Impact Factor
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    ABSTRACT: The neuroanatomical morphology of nerve fibers is an important description for understanding the pathological aspects of nerves. Different from the traditional automatic nerve morphometry methods, a molecular hyperspectral imaging system based on an acousto-optic tunable filter (AOTF) was developed and used to identify unstained nerve histological sections. The hardware, software, and system performance of the imaging system are presented and discussed. The gray correction coefficient was used to calibrate the system's spectral response and to remove the effects of noises and artifacts. A spatial-spectral kernel-based approach through the support vector machine formulation was proposed to identify nerve fibers. This algorithm can jointly use both the spatial and spectral information of molecular hyperspectral images for segmentation. Then, the morphological parameters such as fiber diameter, axon diameter, myelin sheath thickness, fiber area, and g-ratio were calculated and evaluated. Experimental results show that the hyperspectral-based method has the potential to recognize and measure the nerve fiber more accurately than traditional methods.
    Applied Optics 06/2013; 52(17):3891-901. · 1.69 Impact Factor
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    ABSTRACT: Leukocyte cells identification is one of the most frequently performed blood tests and plays an important role in the diagnosis of diseases. The quantitative observation of leukocyte cells is often complemented by morphological analysis in both research and clinical condition. Different from the traditional leukocyte cells morphometry methods, a molecular hyperspectral imaging system based on acousto-optic tunable filter (AOTF) was developed and used to observe the blood smears. A combined spatial and spectral algorithm is proposed to identify the cytoplasm and the nucleus of leukocyte cells by integrating the fuzzy C-means (FCM) with the spatial K-means algorithm. Then the morphological parameters such as the cytoplasm area, the nuclear area, the perimeter, the nuclear ratio, the form factor, and the solidity were calculated and evaluated. Experimental results show that the proposed algorithm has better performance than the spectral based algorithm as the new algorithm can jointly use the spatial and spectral information of leukocyte cells.
    Computerized medical imaging and graphics: the official journal of the Computerized Medical Imaging Society 01/2013; · 1.04 Impact Factor
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    ABSTRACT: Quantitative observation of nerve fiber sections is often complemented by morphological analysis in both research and clinical condition. However, existing manual or semi-automated methods are tedious and labour intensive, fully automated morphometry methods are complicated as the information of color or gray images captured by traditional microscopy is limited. Moreover, most of the methods are time-consuming as the nerve sections need to be stained with some reagents before observation. To overcome these shortcomings, a molecular hyperspectral imaging system is developed and used to observe the spinal nerve sections. The molecular hyperspectral images contain both the structural and biochemical information of spinal nerve sections which is very useful for automatic identification and quantitative morphological analysis of nerve fibers. This characteristic makes it possible for researchers to observe the unstained spinal nerve and live cells in their native environment. To evaluate the performance of the new method, the molecular hyperspectral images were captured and the improved spectral angle mapper algorithm was proposed and used to segment the myelin contours. Then the morphological parameters such as myelin thickness and myelin area were calculated and evaluated. With these morphological parameters, the three dimension surface view images were drawn to help the investigators observe spinal nerve at different angles. The experiment results show that the hyperspectral based method has the potential to identify the spinal nerve more accurate than the traditional method as the new method contains both the spectral and spatial information of nerve sections.
    Neurochemistry International 10/2012; · 2.66 Impact Factor
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    ABSTRACT: White blood cells (WBC) are comparatively significant components in the human blood system, and they have a pathological relationship with some blood-related diseases. To analyze the disease information accurately, the most essential work is to segment WBCs. We propose a new method for pathological WBC segmentation based on a hyperspectral imaging system. This imaging system is used to capture WBC images, which is characterized by acquiring 1-D spectral information and 2-D spatial information for each pixel. A spectral information divergence algorithm is presented to segment pathological WBCs into four parts. In order to evaluate the performance of the new approach, K-means and spectral angle mapper-based segmental methods are tested in contrast on six groups of blood smears. Experimental results show that the presented method can segment pathological WBCs more accurately, regardless of their irregular shapes, sizes, and gray-values.
    Optical Engineering 05/2012; 51(5):3202-. · 0.96 Impact Factor
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    ABSTRACT: An AOTF based microscopic hyperpsectral imaging system which can capture both spectral and spatial information of tissue sections is developed and used in histopathological rat skin analysis. This new type of imaging system has the advantage of having no moving parts and the spectra can be scanned at very high speed. This makes the structure of the new system more compact and more suitable for coupling with a microscope. To evaluate the performance of the new system, scenes of molecular hyperpsectral images of rat skin sections are captured by the new system. Preliminary experiment results show a great deal of potential of this system for histopathological analysis of tissue sections.
    Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on; 01/2012
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    ABSTRACT: To identify the nerve fibers more effectively, a molecular hyperspectral imaging system is used to capture the molecular hyperpsectral images of nerve sections. This new type of imaging system has the advantage of having no moving parts and the spectra can be scanned at very high speed. Then a spectral angle mapper algorithm for automatic nerve fibers identification is presented. To evaluate the performance of the new method, both the molecular hyperspectral images (before staining) and the traditional microscope image (after staining) were captured and compared. The experiment results demonstrate that the new method can utilizes both spectral and spatial information of nerves and identify the nerve fibers more accurately.
    Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on; 01/2012
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    ABSTRACT: A novel molecular hyperspectral imaging (MHSI) system based on AOTF (acousto-optic tunable filters) was presented. AOTF is a rapid wavelength-scanning solid-state device that operates as a tunable optical band pass filter. AOTF offers the advantage of having no moving parts and can be scanned at very high rates. The system consists of microscope, AOTF-based spectrometer, matrix CCD, image collection card and computer. The spectral range of the MHSI is from 550 to 1000 nm. The spectral resolution is less than 2 nm, and the spatial resolution is about 0.3 μm. The valid pixels are 1024×1024. The system can capture 30 frames per min in burst mode of CCD. The system not only can supply single band images in the visible range, but also spectrum curve of random pixel of sample image. Each pixel of the image has two properties: the spectral property and the luminance property. Initial experiment shows that molecular hyperspectral imaging system coupled with multivariate data analysis is a powerful new tool for understanding complex biological and biomedical samples.
    01/2011;
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    ABSTRACT: A new-styled molecular hyperspectral imaging system (MHIS) based on acousto-optic tunable filter (AOTF) was introduced in this paper. This system consists of a Charge-coupled Device (CCD) camera, microscopy, AOTF, and a RF driver. Real-time images are obtained both at multiple, continuous wavelengths and at relatively narrow spectral bandwidths to generate a 3D data including one spectral and two spatial dimensions. AOFT cell covers the spectral band from 550nm to 1000nm with a spectral resolution range of 2nm-6nm. This work presents principle and structure of MHIS as well as its characteristics. The analysis results show that MHIS is promising in biomedical and early diagnosis.
    01/2011;
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    ABSTRACT: Among the parts of the human tongue surface, the sublingual vein is one of the most important ones which may have pathological relationship with some diseases. To analyze this information quantitatively, one primitive work is to extract sublingual veins accurately from tongue body. In this paper, a hyperspectral tongue imaging system instead of a digital camera is used to capture sublingual images. A hidden Markov model approach is presented to extract the sublingual veins from the hyperspectral sublingual images. This approach characterizes the spectral correlation and the band-to-band variability using a hidden Markov process, where the model parameters are estimated by the spectra of the pixel vectors forming the observation sequences. The proposed algorithm, the pixel-based sublingual vein segmentation algorithm, and the spectral angle mapper algorithm are tested on a total of 150 scenes of hyperspectral sublingual veins images to evaluate the performance of the new method. The experimental results demonstrate that the proposed algorithm can extract the sublingual veins more accurately than the traditional algorithms and can perform well even in a noisy environment.
    Computerized medical imaging and graphics: the official journal of the Computerized Medical Imaging Society 10/2010; 35(3):179-85. · 1.04 Impact Factor
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    ABSTRACT: Tongue fissures, an important feature on the tongue surface, may be pathologically related to some diseases. Most existing tongue fissure extraction methods use tongue images captured by traditional charge coupled device cameras. However, these conventional methods cannot be used for an accurate analysis of the tongue surface due to limited information from the images. To solve this, a hyperspectral tongue imager is used to capture tongue images instead of a digital camera. New algorithms for automatic tongue fissure extraction and classification, based on hyperspectral images, are presented. Both spectral and spatial information of the tongue surface is used to segment the tongue body and extract tongue fissures. Then a classification algorithm based on a hidden Markov model is used to classify tongue fissures into 12 typical categories. Results of the experiment show that the new method has good performance in terms of the classification rates of correctness.
    Applied Optics 04/2010; 49(11):2006-13. · 1.69 Impact Factor
  • Qingli Li, Yiting Wang, Hongying Liu, Zhen Sun
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    ABSTRACT: An AOTF-based hyperpsectral tongue imaging system which can capture both spectral and spatial information of human tongue is developed and used in computerized tongue diagnosis. This new type of tongue imaging system has the advantage of having no moving parts and can be scanned at very high rates. This makes the structure of the new system more compact and more suitable for tongue images capture. A series of hyperspectral images of tongue surface and sublingual veins are captured by using the new system. The automatic tongue segmentation and tongue features extraction based on hyperspectral images are also discussed. Preliminary experiment results show a great deal of potential of this system for computerized tongue diagnosis.
    01/2010;
  • Qingli Li, Yiting Wang, Hongying Liu, Zhen Sun
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    ABSTRACT: Sublingual vein is one of the important features on tongue surface, which may have pathological relationship with some diseases. Extracting sublingual veins accurately is the primitive work of computer-aided tongue disease diagnosis. Most existing sublingual veins extraction methods are using sublingual images captured by traditional CCD cameras. However, these conversional methods impede the accurate analysis on the subjects of sublingual veins because of the limited information of the images. To solve these issues, a hyperspectral tongue imaging system instead of a digital camera is used to capture sublingual images. Then an improved spectral angle mapper (ISAM) algorithm for automatic sublingual veins extraction was presented. In this algorithm, the spectral of sublingual veins were extracted and the spectral angles of all bands and partial bands were calculated respectively. Finally, the sublingual veins were extracted according to the spectral angles. The experimental results demonstrate that this algorithm can extract the sublingual veins more accurately.
    01/2010;