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| 1 | Chronic andenoid hypertrophy in children-Is steroid nasal spray beneficial显示文摘 | Anjali Lepcha Mary Kurien Anand Job | 2002 | Indian Journal of Otolar Ngology and Head and Neck Surgery2002，54，4： | 1 |
| 2 | Flunarizine in the prophylaxis of migrainous vertigo: a randomized controlled trial显示文摘 | Anjali Lepcha Sophia Amalanathan Ann Mary Augustine Amit Kumar Tyagi Achamma Balraj | 2014 | European Archives of Oto-Rhino-Laryngology2014，，11： | 1 |
| 3 | Flunarizine in the prophylaxis of migrainous vertigo:a ran-domized controlled trial显示文摘 | LEPCHA A AMALANATHAN S AUGUSTINE A M | 2014 | Eur Arch Otorhinolaryngol2014，271，： | 1 |
| 4 | Flunarizine in the prophylaxis of migrainous vertigo: a randomized controlled trial 显示文摘 | Lepcha A Amalanathan S Augustine A M | 2013 | Eur Arch Otorhinolaryngol2013，29，： | 1 |
| 5 | 显示文摘 | Robin yon Hagen Ashlsh Lepcha | 2013 | Nano Energy2013，2，11： | 1 |
| 6 | Effect of land use, season, and soil depth on soil microbial biomass carbon of Eastern Himalayas显示文摘Background:Soil microbial biomass,an important nutrient pool for ecosystem nutrient cycling is affected by several factors including climate,edaphic,and land-use change.Himalayan soils are young and unstable and prone to erosion and degradation due to its topography,bioclimatic conditions and anthropogenic activities such as frequent land-use change.Through this study,we tried to assess how soil parameters and microbial biomass carbon(MBC)of Eastern Himalayan soils originated from gneissic rock change with land-use type,soil depth and season.Chloroform fumigation extraction method was employed to determine MBC from different land-use types.Results:Soil physical and chemical properties varied significantly with season,land-use and soil depth(p<0.001).The maximum values of soil properties were observed in the rainy season followed by summer and winter season in all the study sites.Annual mean microbial biomass carbon was highest in the forest(455.03μg g−1)followed by cardamom agroforestry(392.86μg g−1)and paddy cropland(317.47μg g−1).Microbial biomass carbon exhibited strong significant seasonal difference(p<0.001)in all the land-use types with a peak value in the rainy season(forest-592.78μg g−1;agroforestry-499.84μg g−1 and cropland-365.21μg g−1)and lowest in the winter season(forest−338.46μg g−1;agroforestry-320.28μg g−1 and cropland−265.70μg g−1).The value of microbial biomass carbon decreased significantly with soil depth(p<0.001)but showed an insignificant increase in the second year which corresponds to a change in rainfall pattern.Besides,land-use type,season and soil depth,soil properties also strongly influenced microbial biomass carbon(p<0.001).Microbial quotient was highest in the agroforestry system(2.16%)and least in the subtropical forest(1.91%).Conclusions:Our results indicate that land-use,soil depth and season significantly influenced soil properties and microbial biomass carbon.The physical and chemical properties of soil and MBC exhibit strong seasonality while the type of land-use influenced the microbial activity and biomass of different soil layers in the study sites.Higher soil organic carbon content in cardamom agroforestry and forest in the present study indicates that restoration of the litter layer through retrogressive land-use change accelerates microbial C immobilization which further helps in the maintenance of soil fertility and soil organic carbon sequestration. | Nima Tshering Lepcha N.Bijayalaxmi Devi | 2020 | Ecological Processes2020，9，1： | 1 |
| 7 | Multimodality Medical Image Fusion Based on Pixel Significance with Edge-Preserving Processing for Clinical Applications显示文摘Multimodal medical image fusion has attained immense popularity in recent years due to its robust technology for clinical diagnosis.It fuses multiple images into a single image to improve the quality of images by retaining significant information and aiding diagnostic practitioners in diagnosing and treating many diseases.However,recent image fusion techniques have encountered several challenges,including fusion artifacts,algorithm complexity,and high computing costs.To solve these problems,this study presents a novel medical image fusion strategy by combining the benefits of pixel significance with edge-preserving processing to achieve the best fusion performance.First,the method employs a cross-bilateral filter(CBF)that utilizes one image to determine the kernel and the other for filtering,and vice versa,by considering both geometric closeness and the gray-level similarities of neighboring pixels of the images without smoothing edges.The outputs of CBF are then subtracted from the original images to obtain detailed images.It further proposes to use edge-preserving processing that combines linear lowpass filtering with a non-linear technique that enables the selection of relevant regions in detailed images while maintaining structural properties.These regions are selected using morphologically processed linear filter residuals to identify the significant regions with high-amplitude edges and adequate size.The outputs of low-pass filtering are fused with meaningfully restored regions to reconstruct the original shape of the edges.In addition,weight computations are performed using these reconstructed images,and these weights are then fused with the original input images to produce a final fusion result by estimating the strength of horizontal and vertical details.Numerous standard quality evaluation metrics with complementary properties are used for comparison with existing,well-known algorithms objectively to validate the fusion results.Experimental results from the proposed research article exhibit superior performance compared to other competing techniques in the case of both qualitative and quantitative evaluation.In addition,the proposed method advocates less computational complexity and execution time while improving diagnostic computing accuracy.Nevertheless,due to the lower complexity of the fusion algorithm,the efficiency of fusion methods is high in practical applications.The results reveal that the proposed method exceeds the latest state-of-the-art methods in terms of providing detailed information,edge contour,and overall contrast. | Bhawna Goyal Ayush Dogra Dawa Chyophel Lepcha Rajesh Singh Hemant Sharma Ahmed Alkhayyat Manob Jyoti Saikia | 2024 | Computers, Materials & Continua2024，78，3： | 0 |
| 8 | Medical Image Fusion Based on Anisotropic Diffusion and Non-Subsampled Contourlet Transform显示文摘The synthesis of visual information from multiple medical imaging inputs to a single fused image without any loss of detail and distortion is known as multimodal medical image fusion.It improves the quality of biomedical images by preserving detailed features to advance the clinical utility of medical imaging meant for the analysis and treatment of medical disor-ders.This study develops a novel approach to fuse multimodal medical images utilizing anisotropic diffusion(AD)and non-subsampled contourlet transform(NSCT).First,the method employs anisotropic diffusion for decomposing input images to their base and detail layers to coarsely split two features of input images such as structural and textural information.The detail and base layers are further combined utilizing a sum-based fusion rule which maximizes noise filtering contrast level by effectively preserving most of the structural and textural details.NSCT is utilized to further decompose these images into their low and high-frequency coefficients.These coefficients are then combined utilizing the principal component analysis/Karhunen-Loeve(PCA/KL)based fusion rule independently by substantiating eigenfeature reinforcement in the fusion results.An NSCT-based multiresolution analysis is performed on the combined salient feature information and the contrast-enhanced fusion coefficients.Finally,an inverse NSCT is applied to each coef-ficient to produce the final fusion result.Experimental results demonstrate an advantage of the proposed technique using a publicly accessible dataset and conducted comparative studies on three pairs of medical images from different modalities and health.Our approach offers better visual and robust performance with better objective measurements for research development since it excellently preserves significant salient features and precision without producing abnormal information in the case of qualitative and quantitative analysis. | Bhawna Goyal Ayush Dogra Rahul Khoond Dawa Chyophel Lepcha Vishal Goyal Steven LFernandes | 2023 | Computers, Materials & Continua2023，，7： | 0 |
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