Journals >Journal of Innovative Optical Health Sciences
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2017
Volume: 10 Issue 3
13 Article(s)
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Monte Carlo and phantom study in the brain edema models
Yubing Liu, Hongke Wang, Yangyang Liu, Weitao Li, and Zhiyu Qian
Because the brain edema has a crucial impact on morbidity and mortality, it is important to develop a noninvasive method to monitor the process of the brain edema effectively. When the brain edema occurs, the optical properties of the brain will change. The goal of this study is to access the feasibility and reliabilitBecause the brain edema has a crucial impact on morbidity and mortality, it is important to develop a noninvasive method to monitor the process of the brain edema effectively. When the brain edema occurs, the optical properties of the brain will change. The goal of this study is to access the feasibility and reliability of using noninvasive near-infrared spectroscopy (NIRS) monitoring method to measure the brain edema. Specifically, three models, including the water content changes in the cerebrospinal fluid (CSF), gray matter and white matter, were explored. Moreover, these models were numerically simulated by the Monte Carlo studies. Then, the phantom experiments were performed to investigate the light intensity which was measured at different detecting radius on the tissue surface. The results indicated that the light intensity correlated well with the conditions of the brain edema and the detecting radius. Briefly, at the detecting radius of 3.0 cm and 4.0 cm, the light intensity has a high response to the change of tissue parameters and optical properties. Thus, it is possible to monitor the brain edema noninvasively by NIRS method and the light intensity is a reliable and simple parameter to assess the brain edema..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1650050 (2017)
Deep tissue near-infrared imaging for vascular network analysis
Kübra Seker, and Mehmet Engin
Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects. Despite developments of optical imaging technologies, still the di±culties about deep skin vascular imaging have been continued. On the other hand, since hemoglobin concentration of human blood Subcutaneous vein network plays important roles to maintain microcirculation that is related to some diagnostic aspects. Despite developments of optical imaging technologies, still the di±culties about deep skin vascular imaging have been continued. On the other hand, since hemoglobin concentration of human blood has key role in the veins imaging by optical manner, the used wavelength in vascular imaging, must be chosen considering absorption of hemoglobin. In this research, we constructed a near infrared (NIR) light source because of lower absorption of hemoglobin in this optical region. To obtain vascular image, reflectance geometry was used. Next, from recorded images, vascular network analysis, such as calculation of width of vascular of interest and complexity of selected region were implemented. By comparing with other modalities, we observed that proposed imaging system has great advantages including nonionized radiation, moderate penetration depth of 0.5–3mm and diameter of 1mm, cost-effective and algorithmic simplicity for analysis..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1650051 (2017)
Structural characterization of calcium glycinate, magnesium glycinate and zinc glycinate
Li-Hui Yin, Xu-Ping Liu, Lu-Yao Yi, Jin Wang, Ya-Jun Zhang, and Yu-Fei Feng
Metal glycinate chelates are formed by glycine and metal compounds through chemical reactions. Calcium glycinate, magnesium glycinate and zinc glycinate are kinds of new-type and ideal nutrient supplements, which have satisfactory physico-chemical properties and bioactivities. They are important for prophylaxis and treMetal glycinate chelates are formed by glycine and metal compounds through chemical reactions. Calcium glycinate, magnesium glycinate and zinc glycinate are kinds of new-type and ideal nutrient supplements, which have satisfactory physico-chemical properties and bioactivities. They are important for prophylaxis and treat metal deficiency. The structural characterization shows that the metal ion is bonded to the amino and carboxyl group to form two five-membered rings. This paper mainly studies the structure characterization of the metal chelated glycinates by their solubility, infrared spectrum, thermal analysis, mass spectrometry, polycrystal diffraction, the metal contents and glycine contents of calcium glycinate, magnesium glycinate and zinc glycinate..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1650052 (2017)
Nondestructive classification of mung bean seeds by single kernel near-infrared spectroscopy
Kaewkarn Phuangsombut, Nattaporn Suttiwijitpukdee, and Anupun Terdwongworakul
Near-infrared spectroscopy (NIRS) in the range 900–1700 nm was performed to develop a classifying model for dead seeds of mung bean using single kernel measurements. The use of the combination of transmission-absorption spectra and reflection-absorption spectra was determined to yield a better classification performancNear-infrared spectroscopy (NIRS) in the range 900–1700 nm was performed to develop a classifying model for dead seeds of mung bean using single kernel measurements. The use of the combination of transmission-absorption spectra and reflection-absorption spectra was determined to yield a better classification performance (87.88%) than the use of only transmissionabsorption spectra (81.31%). The effect of the orientation of the mung bean with respect to the light source on its absorbance was investigated. The results showed that hilum-down orientation exhibited the highest absorbance compared to the hilum-up and hilum-parallel-to-ground orientations. We subsequently examined the spectral information related to the seed orientation by developing a classifying model for seed orientation. The wavelengths associated with classification based on seed orientation were obtained. Finally, we determined that the re-developed classifying model excluding the wavelengths related to the seed orientation afforded better accuracy (89.39%) than that using the entire wavelength range (87.88%)..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1650053 (2017)
Comparative study on identification of healthy and osteoarthritic articular cartilages by fourier transform infrared imaging and chemometrics methods
Zhi-Hua Mao, Yue-Chao Wu, Xue-Xi Zhang, Hao Gao, and Jian-Hua Yin
Two discriminant methods, partial least squares-discriminant analysis (PLS-DA) and Fisher's discriminant analysis (FDA), were combined with Fourier transform infrared imaging (FTIRI) to differentiate healthy and osteoarthritic articular cartilage in a canine model. Osteoarthritic cartilage had been developed for upTwo discriminant methods, partial least squares-discriminant analysis (PLS-DA) and Fisher's discriminant analysis (FDA), were combined with Fourier transform infrared imaging (FTIRI) to differentiate healthy and osteoarthritic articular cartilage in a canine model. Osteoarthritic cartilage had been developed for up to two years after the anterior cruciate ligament (ACL) transection in one knee. Cartilage specimens were sectioned into 10 μm thickness for FTIRI. A PLS-DA model was developed after spectral pre-processing. All IR spectra extracted from FTIR images were calculated by PLS-DA with the discriminant accuracy of 90%. Prior to FDA, principal component analysis (PCA) was performed to decompose the IR spectral matrix into informative principal component matrices. Based on the di?erent discriminant mechanism, the discriminant accuracy (96%) of PCA-FDA with high convenience was higher than that of PLSDA. No healthy cartilage sample was mis-assigned by these two methods. The above mentioned suggested that both integrated technologies of FTIRI-PLS-DA and, especially, FTIRI-PCA-FDA could become a promising tool for the discrimination of healthy and osteoarthritic cartilage specimen as well as the diagnosis of cartilage lesion at microscopic level. The results of the study would be helpful for better understanding the pathology of osteoarthritics..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1650054 (2017)
A novel image fusion algorithm based on 2D scale-mixing complex wavelet transform and Bayesian MAP estimation for multimodal medical images
Abdallah Bengueddoudj, Zoubeida Messali, and Volodymyr Mosorov
In this paper, we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform (2D-SMCWT). The fusion of the detail 2D-SMCWT coefficients is performed via a Bayesian Maximum a Posteriori (MAP) approach by considering a trivariate statistical model for the local neighboring of 2D-In this paper, we propose a new image fusion algorithm based on two-dimensional Scale-Mixing Complex Wavelet Transform (2D-SMCWT). The fusion of the detail 2D-SMCWT coefficients is performed via a Bayesian Maximum a Posteriori (MAP) approach by considering a trivariate statistical model for the local neighboring of 2D-SMCWT coefficients. For the approximation coefficients, a new fusion rule based on the Principal Component Analysis (PCA) is applied. We conduct several experiments using three different groups of multimodal medical images to evaluate the performance of the proposed method. The obtained results prove the superiority of the proposed method over the state of the art fusion methods in terms of visual quality and several commonly used metrics. Robustness of the proposed method is further tested against different types of noise. The plots of fusion metrics establish the accuracy of the proposed fusion method..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750001 (2017)
Rapid monitoring the water extraction process of Radix Paeoniae Alba using near infrared spectroscopy
Tian Hu, Tongtong Li, Lei Nie, Lixuan Zang, Hengchang Zang, and Yingzi Zeng
Near infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide field of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoniflorin, albiflorin, gallic acid, and benzoyl paeonNear infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide field of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoniflorin, albiflorin, gallic acid, and benzoyl paeoniflorin during the water extraction process of Radix Paeoniae Alba was demonstrated and verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and/or derivative, and then quantitative models were built up using PLSR. Interval partial least squares (iPLS) method was used for the selection of spectral variables. Determination coe±cients (R2 cal and R2 pred), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC), and residual predictive deviation (RPD) were applied to verify the performance of the models, and the corresponding values were 0.9873 and 0.9855, 0.0487 mg/mL, 0.0545 mg/mL and 8.4 for paeoniflorin; 0.9879, 0.9888, 0.0303 mg/mL, 0.0321 mg/mL and 9.1 for albiflorin; 0.9696, 0.9644, 0.0140 mg/mL, 0.0145 mg/mL and 5.1 for gallic acid; 0.9794, 0.9781, 0.00169 mg/mL, 0.00171 mg/mL and 6.9 for benzoyl paeoniflorin, respectively. The results turned out that this approach was very e±cient and environmentally friendly for the quantitative monitoring of the water extraction process of Radix Paeoniae Alba..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750002 (2017)
Fast in vivo bioluminescence tomography using a novel pure optical imaging technique
Shuang Zhang, Chengcai Leng, Hongbo Liu, Kun Wang, and Jie Tian
Bioluminescence tomography (BLT) is a novel optical molecular imaging technique that advanced the conventional planar bioluminescence imaging (BLI) into a quantifiable three-dimensional (3D) approach in preclinical living animal studies in oncology. In order to solve the inverse problem and reconstruct tumor lesions inBioluminescence tomography (BLT) is a novel optical molecular imaging technique that advanced the conventional planar bioluminescence imaging (BLI) into a quantifiable three-dimensional (3D) approach in preclinical living animal studies in oncology. In order to solve the inverse problem and reconstruct tumor lesions inside animal body accurately, the prior structural information is commonly obtained from X-ray computed tomography (CT). This strategy requires a complicated hybrid imaging system, extensive post imaging analysis and involvement of ionizing radiation. Moreover, the overall robustness highly depends on the fusion accuracy between the optical and structural information. Here, we present a pure optical bioluminescence tomographic (POBT) system and a novel BLT workflow based on multi-view projection acquisition and 3D surface reconstruction. This method can reconstruct the 3D surface of an imaging subject based on a sparse set of planar white-light and bioluminescent images, so that the prior structural information can be offered for 3D tumor lesion reconstruction without the involvement of CT. The performance of this novel technique was evaluated through the comparison with a conventional dual-modality tomographic (DMT) system and a commercialized optical imaging system (IVIS Spectrum) using three breast cancer xenografts. The results revealed that the new technique offered comparable in vivo tomographic accuracy with the DMT system (P > 0:05) in much shorter data analysis time. It also offered significantly better accuracy comparing with the IVIS system (P < 0:04) without sacrificing too much time..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750003 (2017)
Multispectral imaging of acute wound tissue oxygenation
Audrey Huong, Sheena Philimon, and Xavier Ngu
This paper investigates the appropriate range of values for the transcutaneous blood oxygen saturation (StO2) of granulating tissues and the surrounding tissue that can ensure timely wound recovery. This work has used a multispectral imaging system to collect wound images at wavelengths ranging between 520 nm and 600 nThis paper investigates the appropriate range of values for the transcutaneous blood oxygen saturation (StO2) of granulating tissues and the surrounding tissue that can ensure timely wound recovery. This work has used a multispectral imaging system to collect wound images at wavelengths ranging between 520 nm and 600 nm with a resolution of 10 nm. As part of this research, a pilot study was conducted on three injured individuals with superficial wounds of different woundages at different skin locations. The StO2 value predicted for the examined wounds using the Extended Modified Lambert–Beer model revealed a mean StO2 of 61 ± 10.3% compared to 41.6 ± 6.2% at the surrounding tissues, and 50,1 ± 1,53% for control sites. These preliminary results contribute to the existing knowledge on the possible range and variation of wound bed StO2 that are to be used as indicators of the functioning of the vasomotion system and wound health. This study has concluded that a high StO2 of approximately 60% and a large fluctuation in this value should precede a good progression in wound healing..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750004 (2017)
Performance evaluation of the simplified spherical harmonics approximation for cone-beam X-ray luminescence computed tomography imaging
Haibo Zhang, Guohua Geng, Yanrong Chen, Fengjun Zhao, Yuqing Hou, Huangjian Yi, Shunli Zhang, Jingjing Yu, and Xiaowei He
As an emerging molecular imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) uses X-ray-excitable probes to produce near-infrared (NIR) luminescence and then reconstructs three-dimensional (3D) distribution of the probes from surface measurements. A proper photon-transportation model is criticaAs an emerging molecular imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) uses X-ray-excitable probes to produce near-infrared (NIR) luminescence and then reconstructs three-dimensional (3D) distribution of the probes from surface measurements. A proper photon-transportation model is critical to accuracy of XLCT. Here, we presented a systematic comparison between the common-used Monte Carlo model and simplified spherical harmonics (SPN). The performance of the two methods was evaluated over several main spectrums using a known XLCT material. We designed both a global measurement based on the cosine similarity and a locally-averaged relative error, to quantitatively assess these methods. The results show that the SP3 could reach a good balance between the modeling accuracy and computational e±ciency for all of the tested emission spectrums. Besides, the SP1 (which is equivalent to the diffusion equation (DE)) can be a reasonable alternative model for emission wavelength over 692 nm. In vivo experiment further demonstrates the reconstruction performance of the SP3 and DE. This study would provide a valuable guidance for modeling the photon-transportation in CB-XLCT..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750005 (2017)
Detection of primary RGB colors projected on a screen using fNIRS
Xiaolong Liu, and Keum-Shik Hong
In this study, functional near-infrared spectroscopy (fNIRS) is utilized to measure the hemodynamic responses (HRs) in the visual cortex of 14 subjects (aged 22–34 years) viewing the primary red, green, and blue (RGB) colors displayed on a white screen by a beam projector. The spatiotemporal characteristics of their oxIn this study, functional near-infrared spectroscopy (fNIRS) is utilized to measure the hemodynamic responses (HRs) in the visual cortex of 14 subjects (aged 22–34 years) viewing the primary red, green, and blue (RGB) colors displayed on a white screen by a beam projector. The spatiotemporal characteristics of their oxygenated and deoxygenated hemoglobins (HbO and HbR) in the visual cortex are measured using a 15-source and 15-detector optode configuration. To see whether the activation maps upon RGB-color stimuli can be distinguished or not, the t-values of individual channels are averaged over 14 subjects. To find the best combination of two features for classification, the HRs of activated channels are averaged over nine trials. The HbO mean, peak, slope, skewness and kurtosis values during 2–7 s window for a given 10 s stimulation period are analyzed. Finally, the linear discriminant analysis (LDA) for classifying three classes is applied. Individually, the best classification accuracy obtained with slope-skewness features was 74.07% (Subject 1), whereas the best overall over 14 subjects was 55.29% with peak-skewness combination. Noting that the chance level of 3-class classification is 33.33%, it can be said that RGB colors can be distinguished. The overall results reveal that fNIRS can be used for monitoring purposes of the HR patterns in the human visual cortex..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750006 (2017)
NDC-IVM: An automatic segmentation of optic disc and cup region from medical images for glaucoma detection
Umarani Balakrishnan
Glaucoma is an eye disease that usually occurs with the increased Intra-Ocular Pressure (IOP), which damages the vision of eyes. So, detecting and classifying Glaucoma is an important and demanding task in recent days. For this purpose, some of the clustering and segmentation techniques are proposed in the existing worGlaucoma is an eye disease that usually occurs with the increased Intra-Ocular Pressure (IOP), which damages the vision of eyes. So, detecting and classifying Glaucoma is an important and demanding task in recent days. For this purpose, some of the clustering and segmentation techniques are proposed in the existing works. But, it has some drawbacks that include ine±cient, inaccurate and estimates only the affected area. In order to solve these issues, a Neighboring Differential Clustering (NDC) - Intensity Variation Masking (IVM) are proposed in this paper. The main intention of this work is to extract and diagnose the abnormal retinal image by identifying the optic disc. This work includes three stages such as, preprocessing, clustering and segmentation. At first, the given retinal image is preprocessed by using the Gaussian Mask Updated (GMU) model for eliminating the noise and improving the quality of the image. Then, the cluster is formed by extracting the threshold and patterns with the help of NDC technique. In the segmentation stage, the weight is calculated for pixel matching and ROI extraction by using the proposed IVM method. Here, the novelty is presented in the clustering and segmentation processes by developing NDC and IVM algorithms for accurate Glaucoma identification. In experiments, the results of both existing and proposed techniques are evaluated in terms of sensitivity, specificity, accuracy, Hausdorff distance, Jaccard and dice metrics..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750007 (2017)
Cell counting for in vivo flow cytometry signals with baseline drift
Xiaoling Wang, Yuanzhen Suo, Dan Wei, Hao He, Fan Wu, and Xunbin We
In biomedical research fields, the in vivo flow cytometry (IVFC) is a widely used technology which is able to monitor target cells dynamically in living animals. Although the setup of IVFC system has been well established, baseline drift is still a challenge in the process of quantifying circulating cells. Previous metIn biomedical research fields, the in vivo flow cytometry (IVFC) is a widely used technology which is able to monitor target cells dynamically in living animals. Although the setup of IVFC system has been well established, baseline drift is still a challenge in the process of quantifying circulating cells. Previous methods, i.e., the dynamic peak picking method, counted cells by setting a static threshold without considering the baseline drift, leading to an inaccurate cell quantification. Here, we developed a method of cell counting for IVFC data with baseline drift by interpolation fitting, automatic segmentation and wavelet-based denoising. We demonstrated its performance for IVFC signals with three types of representative baseline drift. Compared with non-baseline-correction methods, this method showed a higher sensitivity and specificity, as well as a better result in the Pearson's correlation coe±cient and the mean-squared error (MSE)..
Journal of Innovative Optical Health Sciences
- Publication Date: Jan. 01, 1900
- Vol. 10, Issue 3, 1750008 (2017)
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