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Parallel K-Means Clustering for Brain Cancer Detection Using Hyperspectral Images
摘要： The precise delineation of brain cancer is a crucial task during surgery. There are several techniques employed during surgical procedures to guide neurosurgeons in the tumor resection. However, hyperspectral imaging (HSI) is a promising non-invasive and non-ionizing imaging technique that could improve and complement the currently used methods. The HypErspectraL Imaging Cancer Detection (HELICoiD) European project has addressed the development of a methodology for tumor tissue detection and delineation exploiting HSI techniques. In this approach, the K-means algorithm emerged in the delimitation of tumor borders, which is of crucial importance. The main drawback is the computational complexity of this algorithm. This paper describes the development of the K-means clustering algorithm on different parallel architectures, in order to provide real-time processing during surgical procedures. This algorithm will generate an unsupervised segmentation map that, combined with a supervised classification map, will offer guidance to the neurosurgeon during the tumor resection task. We present parallel K-means clustering based on OpenMP, CUDA and OpenCL paradigms. These algorithms have been validated through an in-vivo hyperspectral human brain image database. Experimental results show that the CUDA version can achieve a speed-up of ~150× with respect to a sequential processing. The remarkable result obtained in this paper makes possible the development of a real-time classification system.
关键词： unsupervised clustering,brain cancer detection,Graphics Processing Units (GPUs),OpenCL,CUDA,K-means,OpenMP,hyperspectral imaging
更新于2025-09-23 15:21:01
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Detection of mites <i>Tyrophagus putrescentiae</i> and <i>Cheyletus eruditus</i> in flour using hyperspectral imaging system coupled with chemometrics
摘要： An automatic method for detecting mites in flour has been established using hyperspectral imaging (HSI) system coupled with chemometrics. Reflectance differences among flour, Tyrophagus putrescentiae, and Cheyletus eruditus were relatively distinct. Majority of the shape features, including area, perimeter, the major, and minor axis in C. eruditus were remarkably larger than flour and T. putrescentiae. Textural features reached the level of the maximum significance except for contrast with one-way analysis of variance. Images under the ant colony optimization (ACO) wavebands in random forests (RF) classification showed at least 89% recognition rates, better than the successive projections algorithm wavebands. Artificial neural networks (ANN) with ACO wavebands gave higher recognition accuracies in training and validation sets than RF. Further analysis verified hyperspectrum with ACO-PCA-ANN (PCA, principal component analysis), which showed over 98% accuracy. This study revealed the promising potential of HSI coupled with ACO-PCA-ANN as an accurate and rapid method for detecting mites in flour.
关键词： hyperspectral imaging,chemometrics,flour,Tyrophagus putrescentiae,Cheyletus eruditus,mites detection
更新于2025-09-23 15:19:57
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Determination of Drying Patterns of Radish Slabs under Different Drying Methods Using Hyperspectral Imaging Coupled with Multivariate Analysis
摘要： Drying kinetics and the moisture distribution map of radish slabs under different drying methods (hot-air drying (HAD), microwave drying (MD), and hot-air and microwave combination drying (HMCD)) were determined and visualized by hyperspectral image (HSI) processing coupled with a partial least square regression (PLSR)-variable importance in projection (VIP) model, respectively. Page model was the most suitable in describing the experimental moisture loss data of radish slabs regardless of the drying method. Dielectric properties (DP, ε) of radish slices decreased with the decrease in moisture content (MC) during MD, and the penetration depth of microwaves in radish was between 0.81 and 1.15 cm. The PLSR-VIP model developed with 38 optimal variables could result in the high prediction accuracies for both the calibration (R2 = 0.967 and RMSEC = 4.32%) and validation (R2 = 0.962 and RMSEC = 4.45%). In visualized drying patterns, the radish slabs dried by HAD had a higher moisture content at the center than at the edges; however, the samples dried by MD contained higher moisture content at the edges. The nearly uniform drying pattern of radish slabs under HMCD was observed in hyperspectral images. Drying uniformity of radish slabs could be improved by the combination drying method, which significantly reduces drying time.
关键词： multivariate analysis,moisture content,drying pattern,hyperspectral imaging,radish
更新于2025-09-23 15:19:57
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The Encyclopedia of Archaeological Sciences || Multispectral and Hyperspectral Imaging
摘要： In the field of archaeology (and heritage in general), many documentation and examination methods are based on imaging techniques that characterize and depict artifacts in a nondestructive and mechanically noninvasive way. Multi- and hyperspectral imaging (together denoted spectral imaging) are two possible forms of such noninvasive imaging. Both are based on the detection of reflected or emitted optical electromagnetic radiation, the latter being defined as electromagnetic waves with wavelengths between 10 nm (0.01 μm) and 1 mm (1,000 μm). This detection can be better understood when considering that optical digital imaging usually generates a signal that is the outcome of a three-variable process: electromagnetic radiation of a radiation source falls onto the object; this radiation is partly absorbed, transmitted, and reflected by the object, with the interaction being wavelength dependent; and the imager detects and digitizes the incoming radiance in specific spectral regions. Spectral imaging extends traditional trichromatic digital camera approaches by capturing data in at least four different spectral bands, with hyperspectral imaging featuring higher spectral resolution and more contiguous spectra. Applications include archaeological prospection, color-accurate documentation, material identification, and enhancing the reading of old documents. Drawbacks involve data quantity, noise proneness, and reliance on specialized hardware and software, with future research focusing on active systems like multi-wavelength laser scanners.
关键词： multispectral imaging,archaeology,hyperspectral imaging,data cube,spectral signature,future research,drawbacks,electromagnetic radiation,noninvasive imaging,applications,spectral imaging,heritage
更新于2025-09-19 17:15:36
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[Advances in Food and Nutrition Research] || Advanced Analysis of Roots and Tubers by Hyperspectral Techniques
摘要： Hyperspectral techniques in terms of spectroscopy and hyperspectral imaging have become reliable analytical tools to effectively describe quality attributes of roots and tubers (such as potato, sweet potato, cassava, yam, taro, and sugar beet). In addition to the ability for obtaining rapid information about food external or internal defects including sprout, bruise, and hollow heart, and identifying different grades of food quality, such techniques have also been implemented to determine physical properties (such as color, texture, and specific gravity) and chemical constituents (such as protein, vitamins, and carotenoids) in root and tuber products with avoidance of extensive sample preparation. Developments of related quality evaluation systems based on hyperspectral data that determine food quality parameters would bring about economic and technical values to the food industry. Consequently, a comprehensive review of hyperspectral literature is carried out in this chapter. The spectral data acquired, the multivariate statistical methods used, and the main breakthroughs of recent studies on quality determinations of root and tuber products are discussed and summarized. The conclusion elaborates the promise of how hyperspectral techniques can be applied for non-invasive and rapid evaluations of tuber quality properties.
关键词： Gradation,Physical properties,Chemometric analyses,Multivariate statistics,Hyperspectral imaging,Chemical constituents,Authentication,Vibrational spectroscopy,Potato tuber,Food quality
更新于2025-09-19 17:15:36
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ALK positive lung cancer identification and targeted drugs evaluation using microscopic hyperspectral imaging technique
摘要： It is important to distinguish ALK positive lung cancer from ALK negative lung cancer and to monitor the efficacy of targeted drugs. This paper applies a microscopic hyperspectral imaging technique to identify ALK positive lung cancer cells and evaluate the therapeutic effect. The hyperspectral images of five groups of lung tissues are captured by the home-made microscopic hyperspectral imaging system. A preprocessing algorithm is proposed to reduce obvious banding noise and noise particles from original data. Then a segmentation algorithm, which assembles Supported Vector Machine (SVM) and Majority analysis together with the Clumping processing, is presented. The ALK positive and negative lung cancers can be distinguished by both the fluctuation of spectral curves and the relative proportion between cytoplasm and cell nucleus. In addition, the treatment efficacy can be surveyed in the same way. The experimental results show that the relative proportion of cytoplasm in Group ALK-neg is 77.3%, while that in Group ALK-pos is 40.6%. It is obvious that there exist differences in contents and spectra between Group ALK-neg and Group ALK-pos. Moreover, the experimental results of quantitative analysis and spectral curves analysis show that ALK positive lung cancer cells treated with the low concentration of targeted drugs will be developed towards the ALK negative lung cancer. This paper shows the potential of using hyperspectral images to detect the ALK positive lung cancer cells and evaluate the therapeutic effect of targeted drugs.
关键词： Spectral analysis,Therapeutic effect evaluation,Microscopic hyperspectral imaging,ALK positive lung cancer
更新于2025-09-19 17:15:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - An Experiment of Geothermal Exploration with an Uas-Tir in Xiaoyoukeng Area of Tatun Volcanoes, Taiwan
摘要： Geothermal exploration requires thermal images for obtaining the temperature on ground surface for characterizing surface geology and modeling the temperature at the depth. The purpose of this study is to integrate a thermal sensor with a wind-resistant UAV for detecting geothermal anomalies suitable for conducting exploration in a mountainous terrain. The specifications of the UAS-TIR, the experiment at XiaoYoukeng, and the results are presented. It is proved that such a system can be effectively applied in assisting quantitative assessment of geothermal reserves when compared with airborne thermal systems.
关键词： remote sensing,green energy,thermography,hyperspectral imaging
更新于2025-09-19 17:15:36
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Study of modeling optimization for hyperspectral imaging quantitative determination of naringin content in pomelo peel
摘要： With the development of modern computational science and data metrology, hyperspectral imaging technology has been utilized in the field of remote sensing for the application in precision agriculture and crop quality testing. In this paper, the near infrared hyperspectral imaging (NIRHSI) technique was applied to quantitatively determine the naringin content in pomelo peel samples. Model optimization was studied by investigating the influence of system measuring conditions and parameters of the built-up HSI instrumental system. The HSI data acquisition was built up using a prevalent pushbroom scanner in the near infrared region. Calibration models were established using the partial least squares (PLS) regression in the mode of cross validation, in combined use of the Savitzky-Golay smoother (SGS) for data pretreatment. These multivariate analytical models were optimized in comparison about the region of interest (ROI) for NIRHSI model optimization. In the process of NIRHSI data acquisition, the rational values of some system measurement parameters were also tuned and tested, such as the use of different watts for light intensity, different lenses and different materials as the scanning backgrounds. Results showed that the cross-validation PLS regression methods performed well in the calibration and prediction processes, working well together with the parameter tuning of the SGS pretreatment. In addition to the fact that different materials as the scanning backgrounds obviously affected the quantitative result, there is no apparent difference in the comparing cases of different light intensities and different lenses. This work validates the capability of applying NIRHSI technique to quantitative determine the content of naringin in pomelo peel samples. The test for model optimization by comparing the measurement parameters and the system properties has prospective application ability in fields of other spectral/hyperspectral data analysis. It is an important lab simulation of remote sensing. It contributes significant theoretical reference to the design of the large-scale online hyperspectral data acquisition systems.
关键词： Pomelo peel Naringin,Near infrared hyperspectral imaging,Pushbroom scanner,Modeling optimization,Region of interest
更新于2025-09-19 17:15:36
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Rapid identification of wood species by near-infrared spatially resolved spectroscopy (NIR-SRS) based on hyperspectral imaging (HSI)
摘要： Conventional near-infrared (NIR) spectroscopy has shown its potential to separate wood species non-destructively based on the aggregate effect of light absorption and scattering values. However, wood has an aligned microstructure, and there is a large refractive index (RI) mismatch between the wood cell wall substance (n≈1.55) and the cell lumen (air≈1.0, water≈1.33). Light scattering is dominant over absorption μ′ (cid:31)( ) a in wood, and this fact can be utilized for complex classification purposes. In this study, an NIR hyperspectral imaging (HSI) camera combined with one focused halogen light source (? 1 mm) was designed to evaluate the light scattering patterns of five softwood (SW) and 10 hardwood (HW) species in the wavelength range from 1002 to 2130 nm. Several parameters were combined to improve the data quality, such as image histogram plots of defined spaced bins (associated with diffuse reflectance values of light), variance calculation on the frequency (the number of pixels in each bin) of each histogram and the principal component analysis (PCA) of all the variance values at each wavelength. The identification accuracy of the quadratic discriminant analysis (QDA) under the five-fold cross-validation method was 94.1%, based on the first three principal component (PC) scores.
关键词： spatially resolved spectroscopy,light scattering characteristics,wood species identification,hardwood,quadratic discriminant analysis (QDA),near-infrared hyperspectral imaging camera,principal component analysis (PCA),softwood,halogen spot-light source
更新于2025-09-19 17:15:36
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Hyperspectral Imaging for Evaluating Impact Damage to Mango According to Changes in Quality Attributes
摘要： Evaluation of impact damage to mango (Mangifera indica Linn) as a result of dropping from three different heights, namely, 0.5, 1.0 and 1.5 m, was conducted by hyperspectral imaging (HSI). Reflectance spectra in the 900–1700 nm region were used to develop prediction models for pulp firmness (PF), total soluble solids (TSS), titratable acidity (TA) and chroma (?b*) by a partial least squares (PLS) regression algorithm. The results showed that the changes in the mangoes’ quality attributes, which were also reflected in the spectra, had a strong relationship with dropping height. The best predictive performance measured by coefficient of determination (R2) and root mean square errors of prediction (RMSEP) values were: 0.84 and 31.6 g for PF, 0.9 and 0.49 oBrix for TSS, 0.65 and 0.1% for TA, 0.94 and 0.96 for chroma, respectively. Classification of the degree of impact damage to mango achieved an accuracy of more than 77.8% according to ripening index (RPI). The results show the potential of HSI to evaluate impact damage to mango by combining with changes in quality attributes.
关键词： partial least squares regression,quality attributes,impact damage,mango,hyperspectral imaging
更新于2025-09-19 17:15:36