scholarly journals Development of a Novel Embedded Relay Lens Microscopic Hyperspectral Imaging System for Cancer Diagnosis: Use of the Mice with Oral Cancer to Be the Example

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Yao-Fang Hsieh ◽  
Mang Ou-Yang ◽  
Jeng-Ren Duann ◽  
Jin-Chern Chiou ◽  
Nai-Wen Chang ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Hyperspectral Imaging ◽  
Cancer Diagnosis ◽  
Spectral Resolution ◽  
Imaging System ◽  
Early Stage ◽  
High Spectral Resolution ◽  
Normal Cells ◽  
M 10

This paper develops a novel embedded relay lens microscopic hyperspectral imaging system (ERL-MHSI) with high spectral resolution (nominal spectral resolution of 2.8 nm) and spatial resolution (30 μm × 10 μm) for cancer diagnosis. The ERL-MHSI system has transmittance and fluorescence mode. The transmittance can provide the morphological information for pathological diagnosis, and the fluorescence of cells or tissue can provide the characteristic signature for identification of normal and abnormal. In this work, the development of the ERL-MHSI system is discussed and the capability of the system is demonstrated by diagnosing early stage oral cancer of twenty mice in vitro. The best sensitivity for identifying normal cells and squamous cell carcinoma (SCC) was 100%. The best specificity for identifying normal cells and SCC was 99%. The best sensitivity for identifying normal cells and dysplasia was 99%. The best specificity for identifying normal cells and dysplasia was 97%. This work also utilizes fractal dimension to analyze the morphological information and find the significant different values between normal and SCC.

scholarly journals Study of the best decocting time of sun dried ginseng by using the hyperspectral imaging technology

2016 ◽  
Vol 09 (06) ◽  
pp. 1650006
Author(s):  
Qing He ◽  
Lan Liang ◽  
Zhenqiang Chen ◽  
Qichang Pang ◽  
Jing Zhao
Keyword(s):  
Fluorescence Imaging ◽  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Equilibrium Condition ◽  
Imaging System ◽  
Test Sample ◽  
Tissue Fluid ◽  
Active Ingredients ◽  
Spectral Curves ◽  
Fluorescence Imaging System

In this research, a new method based on the hyperspectral imaging for searching the best decocting time of sun dried ginseng is reported. The spectral images at different decocting time of test sample have been taken by the staring hyperspectral fluorescence imaging system and the solubility of active ingredients have been discussed by analyzing the changes on the spectral curves. The spectral range of the system is 400–720[Formula: see text]nm and the spectral resolution is 5[Formula: see text]nm. In the decocting process, the active ingredients of nonsoaked ginseng was dissolved in the tissue fluid at first, and reached equilibrium condition at last after the precipitation–dissolution reciprocating process of boiling. At last, the experimental results show that the best decoction time of sun dried ginseng is about 60[Formula: see text]min after boiling.

High Spatial and High Spectral Resolution FTIR Spectroscopic Imaging of Biological Materials

1997 ◽  
Vol 3 (S2) ◽  
pp. 831-832
Author(s):  
E.N. Lewis ◽  
L.H. Kidder ◽  
I.W. Levin
Keyword(s):  
Spectral Resolution ◽  
Imaging System ◽  
Spectroscopic Imaging ◽  
Quantitative Information ◽  
High Spectral Resolution ◽  
Spectroscopic Techniques ◽  
Structure And Dynamics ◽  
Spatial Domains ◽  
Infrared Wavelengths

Infrared spectroscopy has been used to probe a variety of biological systems including for example, the determination of diseased states and the investigation of foreign inclusions in biologicals. The technique generates qualitative and quantitative information on the structure and dynamics of samples, including lipids, proteins, and non-biological constituents. The coupling of imaging modalities with spectroscopic techniques adds a new dimension to sample analysis in both the spectroscopic and spatial domains. Using a spectroscopic imaging system that incorporates a step-scan interferometer, microscope, and infrared sensitive arrays, we have investigated a variety of biological samples. This seamless combination of spectroscopy for molecular analysis with the power of visualization generates chemically specific images while simultaneously obtaining high resolution spectra for each detector pixel. The spatial resolution of the images approaches the diffraction limit for mid-infrared wavelengths, while the spectral resolution is determined by the interferometer and can be 4 cm−1 or higher.

scholarly journals Wide Swath and High Resolution Airborne HyperSpectral Imaging System and Flight Validation

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1667 ◽  
Author(s):  
Dong Zhang ◽  
Liyin Yuan ◽  
Shengwei Wang ◽  
Hongxuan Yu ◽  
Changxing Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Spectral Resolution ◽  
High Efficiency ◽  
High Spatial Resolution ◽  
Imaging System ◽  
High Sensitivity ◽  
Field Of View ◽  
High Spectral Resolution ◽  
Wide Swath

Wide Swath and High Resolution Airborne Pushbroom Hyperspectral Imager (WiSHiRaPHI) is the new-generation airborne hyperspectral imager instrument of China, aimed at acquiring accurate spectral curve of target on the ground with both high spatial resolution and high spectral resolution. The spectral sampling interval of WiSHiRaPHI is 2.4 nm and the spectral resolution is 3.5 nm (FWHM), integrating 256 channels coving from 400 nm to 1000 nm. The instrument has a 40-degree field of view (FOV), 0.125 mrad instantaneous field of view (IFOV) and can work in high spectral resolution mode, high spatial resolution mode and high sensitivity mode for different applications, which can adapt to the Velocity to Height Ratio (VHR) lower than 0.04. The integration has been finished, and several airborne flight validation experiments have been conducted. The results showed the system’s excellent performance and high efficiency.

scholarly journals Measurement of Early Disease Blueberries Based on Vis/NIR Hyperspectral Imaging System

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5783
Author(s):  
Yuping Huang ◽  
Dezhen Wang ◽  
Ying Liu ◽  
Haiyan Zhou ◽  
Ye Sun
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Range ◽  
Imaging System ◽  
Early Stage ◽  
Partial Least Square ◽  
Least Square ◽  
Early Disease ◽  
Spectral Correlation ◽  
Fungal Damage ◽  
Optimal Classification

Blueberries, which are rich in nutrition, are susceptible to fungal infection during postharvest or storage. However, early detection of diseases in blueberry is challenging because of their opaque appearance and the inconspicuousness of spots in the early stage of disease. The goal of this study was to investigate the potential of hyperspectral imaging over the spectral range of 400–1000 nm to discriminate early disease in blueberries. Scanning electron microscope observation verified that fungal damage to the cellular structure takes place during the early stages. A total of 400 hyperspectral images, 200 samples each of healthy and early disease groups, were collected to obtain mean spectra of each blueberry samples. Spectral correlation analysis was performed to select an effective spectral range. Partial least square discrimination analysis (PLSDA) models were developed using two types of spectral range (i.e., full wavelength range of 400–1000 nm and effective spectral range of 685–1000 nm). The results showed that the effective spectral range made it possible to provide better classification results due to the elimination of the influence of irrelevant variables. Moreover, the effective spectral range combined with an autoscale preprocessing method was able to obtain optimal classification accuracies, with recognition rates of 100% and 99% for healthy and early disease blueberries. This study demonstrated that it is feasible to use hyperspectral imaging to measure early disease blueberries.

scholarly journals Compressive spectral image fusion via a single aperture high throughput imaging system

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hoover Rueda-Chacon ◽  
Fernando Rojas ◽  
Henry Arguello
Keyword(s):  
Image Fusion ◽  
Spectral Resolution ◽  
Spatial Information ◽  
Imaging System ◽  
Research Work ◽  
Visible Spectral Range ◽  
Computational Imaging ◽  
High Spectral Resolution ◽  
Spectral Image ◽  
The Rich

AbstractSpectral image fusion techniques combine the detailed spatial information of a multispectral (MS) image and the rich spectral information of a hyperspectral (HS) image into a high-spatial and high-spectral resolution image. Due to the data deluge entailed by such images, new imaging modalities have exploited their intrinsic correlations in such a way that, a computational algorithm can fuse them from few multiplexed linear projections. The latter has been coined compressive spectral image fusion. State-of-the-art research work have focused mainly on the algorithmic part, simulating instrumentation characteristics and assuming independently registered sensors to conduct compressed MS and HS imaging. In this manuscript, we report on the construction of a unified computational imaging framework that includes a proof-of-concept optical testbed to simultaneously acquire MS and HS compressed projections, and an alternating direction method of multipliers algorithm to reconstruct high-spatial and high-spectral resolution images from the fused compressed measurements. The testbed employs a digital micro-mirror device (DMD) to encode and split the input light towards two compressive imaging arms, which collect MS and HS measurements, respectively. This strategy entails full light throughput sensing since no light is thrown away by the coding process. Further, different resolutions can be dynamically tested by binning the DMD and sensors pixels. Real spectral responses and optical characteristics of the employed equipment are obtained through a per-pixel point spread function calibration approach to enable accurate compressed image fusion performance. The proposed framework is demonstrated through real experiments within the visible spectral range using as few as 5% of the data.

scholarly journals DMD-based hyperspectral imaging system with tunable spatial and spectral resolution

2019 ◽  
Vol 27 (12) ◽  
pp. 16995 ◽  
Author(s):  
Xue Dong ◽  
Xingchen Xiao ◽  
Yining Pan ◽  
Guangyao Wang ◽  
Yiting Yu
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Imaging System

scholarly journals Target detection algorithm for airborne thermal hyperspectral data

2014 ◽  
Vol XL-8 ◽  
pp. 827-832 ◽  
Author(s):  
R. Marwaha ◽  
A. Kumar ◽  
P. L. N. Raju ◽  
Y. V. N. Krishna Murthy
Keyword(s):  
Spectral Resolution ◽  
Hyperspectral Image ◽  
Imaging System ◽  
Hyperspectral Data ◽  
High Spectral Resolution ◽  
Infrared Range ◽  
Digital Photograph ◽  
Minimum Noise Fraction ◽  
Noise Fraction ◽  
Minimum Noise

Airborne hyperspectral imaging is constantly being used for classification purpose. But airborne thermal hyperspectral image usually is a challenge for conventional classification approaches. The Telops Hyper-Cam sensor is an interferometer-based imaging system that helps in the spatial and spectral analysis of targets utilizing a single sensor. It is based on the technology of Fourier-transform which yields high spectral resolution and enables high accuracy radiometric calibration. The Hypercam instrument has 84 spectral bands in the 868 cm<sup>&minus;1</sup> to 1280 cm<sup>&minus;1</sup> region (7.8 μm to 11.5 μm), at a spectral resolution of 6 cm<sup>&minus;1</sup> (full-width-half-maximum) for LWIR (long wave infrared) range. Due to the Hughes effect, only a few classifiers are able to handle high dimensional classification task. MNF (Minimum Noise Fraction) rotation is a data dimensionality reducing approach to segregate noise in the data. In this, the component selection of minimum noise fraction (MNF) rotation transformation was analyzed in terms of classification accuracy using constrained energy minimization (CEM) algorithm as a classifier for Airborne thermal hyperspectral image and for the combination of airborne LWIR hyperspectral image and color digital photograph. On comparing the accuracy of all the classified images for airborne LWIR hyperspectral image and combination of Airborne LWIR hyperspectral image with colored digital photograph, it was found that accuracy was highest for MNF component equal to twenty. The accuracy increased by using the combination of airborne LWIR hyperspectral image with colored digital photograph instead of using LWIR data alone.

scholarly journals Hyperspectral system trade-offs for illumination, hardware and analysis methods: a case study of seed mix ingredient discrimination

2020 ◽  
Author(s):  
Carolina Blanch-Pérez del Notario ◽  
Carlos López-Molina ◽  
Andy Lambrechts ◽  
Wouter Saeys
Keyword(s):  
Hyperspectral Imaging ◽  
Spectral Resolution ◽  
Food Industry ◽  
Near Infrared ◽  
Imaging System ◽  
Infrared Range ◽  
Analysis Methods ◽  
Trade Offs ◽  
The Impact

The discrimination power of a hyperspectral imaging system for image segmentation or object detection is determined by the illumination, the camera spatial–spectral resolution, and both the pre-processing and analysis methods used for image processing. In this study, we methodically reviewed the alternatives for each of those factors for a case study from the food industry to provide guidance in the construction and configuration of hyperspectral imaging systems in the visible near infrared range for food quality inspection. We investigated both halogen- and LED-based illuminations and considered cameras with different spatial–spectral resolution trade-offs. At the level of the data analysis, we evaluated the impact of binning, median filtering and bilateral filtering as pre- or post-processing and compared pixel-based classifiers with convolutional neural networks for a challenging application in the food industry, namely ingredient identification in a flour–seed mix. Starting from a basic configuration and by modifying the combination of system aspects we were able to increase the mean accuracy by at least 25 %. In addition, different trade-offs in performance-complexity were identified for different combinations of system parameters, allowing adaptation to diverse application requirements.

scholarly journals Ion Channel Targeting with Antibodies and Antibody Fragments for Cancer Diagnosis

Antibodies ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 33 ◽  
Author(s):  
Claudia Duranti ◽  
Annarosa Arcangeli
Keyword(s):  
Monoclonal Antibodies ◽  
Ion Channel ◽  
Cancer Diagnosis ◽  
Early Stage ◽  
Scientific Evidence ◽  
Antibody Fragments ◽  
Solid Cancer ◽  
Cancer Management

The antibody era has greatly impacted cancer management in recent decades. Indeed, antibodies are currently applied for both cancer diagnosis and therapy. For example, monoclonal antibodies are the main constituents of several in vitro diagnostics, which are applied at many levels of cancer diagnosis. Moreover, the great improvement provided by in vivo imaging, especially for early-stage cancer diagnosis, has traced the path for the development of a complete new class of antibodies, i.e., engineered antibody fragments. The latter embody the optimal characteristics (e.g., low renal retention, rapid clearance, and small size) which make them ideal for in vivo applications. Furthermore, the present review focuses on reviewing the main applications of antibodies and antibody fragments for solid cancer diagnosis, both in vitro and in vivo. Furthermore, we review the scientific evidence showing that ion channels represent an almost unexplored class of ideal targets for both in vitro and in vivo diagnostic purposes. In particular, we review the applications, in solid cancers, of monoclonal antibodies and engineered antibody fragments targeting the voltage-dependent ion channel Kv 11.1, also known as hERG1.

scholarly journals Current Insights into Oral Cancer Diagnostics

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1287
Author(s):  
Yee-Fun Su ◽  
Yi-Ju Chen ◽  
Fa-Tzu Tsai ◽  
Wan-Chun Li ◽  
Ming-Lun Hsu ◽  
...  
Keyword(s):  
Oral Cancer ◽  
Early Stage ◽  
Rapid Development ◽  
High Risk Patient ◽  
Cancer Diagnostics ◽  
Diagnostic Methods ◽  
Diagnostic Systems ◽  
Oral Potentially Malignant Disorders ◽  
Severe Stage

Oral cancer is one of the most common head and neck malignancies and has an overall 5-year survival rate that remains below 50%. Oral cancer is generally preceded by oral potentially malignant disorders (OPMDs) but determining the risk of OPMD progressing to cancer remains a difficult task. Several diagnostic technologies have been developed to facilitate the detection of OPMD and oral cancer, and some of these have been translated into regulatory-approved in vitro diagnostic systems or medical devices. Furthermore, the rapid development of novel biomarkers, electronic systems, and artificial intelligence may help to develop a new era where OPMD and oral cancer are detected at an early stage. To date, a visual oral examination remains the routine first-line method of identifying oral lesions; however, this method has certain limitations and as a result, patients are either diagnosed when their cancer reaches a severe stage or a high-risk patient with OPMD is misdiagnosed and left untreated. The purpose of this article is to review the currently available diagnostic methods for oral cancer as well as possible future applications of novel promising technologies to oral cancer diagnosis. This will potentially increase diagnostic options and improve our ability to effectively diagnose and treat oral cancerous-related lesions.

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