scholarly journals Intraoperative Guidance Using Hyperspectral Imaging: A Review for Surgeons

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2066
Author(s):  
Manuel Barberio ◽  
Sara Benedicenti ◽  
Margherita Pizzicannella ◽  
Eric Felli ◽  
Toby Collins ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Biochemical Analysis ◽  
Hybrid Imaging ◽  
Molecular Level ◽  
Imaging Modality ◽  
Tissue Composition ◽  
Medical Field ◽  
Future Directions ◽  
Non Destructive ◽  
Intraoperative Guidance

Hyperspectral imaging (HSI) is a novel optical imaging modality, which has recently found diverse applications in the medical field. HSI is a hybrid imaging modality, combining a digital photographic camera with a spectrographic unit, and it allows for a contactless and non-destructive biochemical analysis of living tissue. HSI provides quantitative and qualitative information of the tissue composition at molecular level in a contrast-free manner, hence making it possible to objectively discriminate between different tissue types and between healthy and pathological tissue. Over the last two decades, HSI has been increasingly used in the medical field, and only recently it has found an application in the operating room. In the last few years, several research groups have used this imaging modality as an intraoperative guidance tool within different surgical disciplines. Despite its great potential, HSI still remains far from being routinely used in the daily surgical practice, since it is still largely unknown to most of the surgical community. The aim of this study is to provide clinical surgeons with an overview of the capabilities, current limitations, and future directions of HSI for intraoperative guidance.

scholarly journals The Performances of Hyperspectral Sensors for Proximal Sensing of Nitrogen Levels in Wheat

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4550
Author(s):  
Huajian Liu ◽  
Brooke Bruning ◽  
Trevor Garnett ◽  
Bettina Berger
Keyword(s):  
Hyperspectral Imaging ◽  
High Throughput ◽  
Management Practices ◽  
Leaf Tissue ◽  
Plant Phenotyping ◽  
Proximal Sensing ◽  
N Content ◽  
Hyperspectral Sensors ◽  
Wheat Leaves ◽  
Non Destructive

The accurate and high throughput quantification of nitrogen (N) content in wheat using non-destructive methods is an important step towards identifying wheat lines with high nitrogen use efficiency and informing agronomic management practices. Among various plant phenotyping methods, hyperspectral sensing has shown promise in providing accurate measurements in a fast and non-destructive manner. Past applications have utilised non-imaging instruments, such as spectrometers, while more recent approaches have expanded to hyperspectral cameras operating in different wavelength ranges and at various spectral resolutions. However, despite the success of previous hyperspectral applications, some important research questions regarding hyperspectral sensors with different wavelength centres and bandwidths remain unanswered, limiting wide application of this technology. This study evaluated the capability of hyperspectral imaging and non-imaging sensors to estimate N content in wheat leaves by comparing three hyperspectral cameras and a non-imaging spectrometer. This study answered the following questions: (1) How do hyperspectral sensors with different system setups perform when conducting proximal sensing of N in wheat leaves and what aspects have to be considered for optimal results? (2) What types of photonic detectors are most sensitive to N in wheat leaves? (3) How do the spectral resolutions of different instruments affect N measurement in wheat leaves? (4) What are the key-wavelengths with the highest correlation to N in wheat? Our study demonstrated that hyperspectral imaging systems with satisfactory system setups can be used to conduct proximal sensing of N content in wheat with sufficient accuracy. The proposed approach could reduce the need for chemical analysis of leaf tissue and lead to high-throughput estimation of N in wheat. The methodologies here could also be validated on other plants with different characteristics. The results can provide a reference for users wishing to measure N content at either plant- or leaf-scales using hyperspectral sensors.

scholarly journals Hyperspectral Imaging for Bloodstain Identification

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3045
Author(s):  
Maheen Zulfiqar ◽  
Muhammad Ahmad ◽  
Ahmed Sohaib ◽  
Manuel Mazzara ◽  
Salvatore Distefano
Keyword(s):  
Hyperspectral Imaging ◽  
Dna Analysis ◽  
Forensic Sciences ◽  
Blood Protein ◽  
Chemical Methods ◽  
Acrylic Paint ◽  
Spectral Bands ◽  
Nail Polish ◽  
Spatial Dimensions ◽  
Non Destructive

Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification can help to confirm a suspect, and for that reason, several chemical methods are used to reconstruct the crime scene however, these methods can affect subsequent DNA analysis. Therefore, this study presents a non-destructive method for bloodstain identification using Hyperspectral Imaging (HSI, 397–1000 nm range). The proposed method is based on the visualization of heme-components bands in the 500–700 nm spectral range. For experimental and validation purposes, a total of 225 blood (different donors) and non-blood (protein-based ketchup, rust acrylic paint, red acrylic paint, brown acrylic paint, red nail polish, rust nail polish, fake blood, and red ink) samples (HSI cubes, each cube is of size 1000 × 512 × 224, in which 1000 × 512 are the spatial dimensions and 224 spectral bands) were deposited on three substrates (white cotton fabric, white tile, and PVC wall sheet). The samples are imaged for up to three days to include aging. Savitzky Golay filtering has been used to highlight the subtle bands of all samples, particularly the aged ones. Based on the derivative spectrum, important spectral bands were selected to train five different classifiers (SVM, ANN, KNN, Random Forest, and Decision Tree). The comparative analysis reveals that the proposed method outperformed several state-of-the-art methods.

scholarly journals Vis/NIR hyperspectral imaging for detection of hidden bruises on kiwifruits

2011 ◽  
Vol 29 (No. 6) ◽  
pp. 595-602 ◽  
Author(s):  
Q. Lü ◽  
M.-j. Tang ◽  
J.-r. Cai ◽  
J.-w. Zhao ◽  
S. Vittayapadung
Keyword(s):  
Hyperspectral Imaging ◽  
Hyperspectral Image ◽  
Detection System ◽  
Image Data ◽  
Principal Component ◽  
Quality Analysis ◽  
Economic Losses ◽  
Hyperspectral Image Data ◽  
Multispectral Detection ◽  
Non Destructive

It is necessary to develop a non-destructive technique for kiwifruit quality analysis because the machine injury could lower the quality of fruit and incur economic losses. Bruises are not visible externally owing to the special physical properties of kiwifruit peel.We proposed the hyperspectral imaging technique to inspect the hidden bruises on kiwifruit. The Vis/NIR (408–1117 nm) hyperspectral image data was collected. Multiple optimal wavelength (682, 723, 744, 810, and 852 nm) images were obtained using principal component analysis on the high dimension spectral image data (wavelength range from 600 nm to 900 nm). The bruise regions were extracted from the component images of the five waveband images using RBF-SVM classification. The experimental results showed that the error of hidden bruises detection on fruits by means of hyperspectral imaging was 12.5%. It was concluded that the multiple optimal waveband images could be used to constructs a multispectral detection system for hidden bruises on kiwifruits.

scholarly journals INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 2107-2111
Author(s):  
X. Yang ◽  
M. Hou ◽  
S. Lyu ◽  
S. Ma ◽  
Z. Gao ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Visual Experience ◽  
Hyperspectral Data ◽  
Shanxi Province ◽  
Bottom Surface ◽  
Archaeological Research ◽  
Reference Images ◽  
Research Findings ◽  
And Storage ◽  
Non Destructive

Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

scholarly journals Elements Identification in Golden Strawberries (Physalis Peruviana L.) using Wavelength Dispersive X-Ray Fluorescence

2019 ◽  
Vol 7 (6) ◽  
pp. 851
Author(s):  
Uğur Akbaba
Keyword(s):  
Weight Loss ◽  
Functional Food ◽  
Medical Field ◽  
X Ray ◽  
Physalis Peruviana ◽  
Food Properties ◽  
Wide Range ◽  
Important Health ◽  
Fluorescence Spectrometer ◽  
Non Destructive

Physalis peruviana (PP) is a popular exotic fruit due to its functional food properties. This product has a wide range of uses in the medical field, including treatments for cancer, malaria, hepatitis, dermatitis, rheumatism, weight loss, and diabetes. In this study, the PP element concentrations were investigated using a Wave Dispersive X-ray Fluorescence Spectrometer (WDXRF). Al, Ca, Fe, Mn, P, S, Zn, Cl, K, Mg, Na, F, Si, and B were detected, and the Ca, Fe, Zn, P, Na, Mg elements were found in significant amounts. Therefore, PP has some important health elements. For example, Mg and Mn may be associated with diabetes control. WDXRF is a cheap, quick, and non-destructive technique used in the elemental analysis of plant samples.

scholarly journals Cystatins — Inhibitors of Cysteine Proteinases

1992 ◽  
Vol 3 (4) ◽  
pp. 307-332 ◽  
Author(s):  
Libuse A. Bobek ◽  
Michael J. Levine
Keyword(s):  
Common Ancestor ◽  
Molecular Level ◽  
Proteinase Inhibitors ◽  
Cysteine Proteinase ◽  
Diverse Group ◽  
Cysteine Proteinases ◽  
Future Directions ◽  
Cysteine Proteinase Inhibitors ◽  
Physicochemical And Functional Properties

The cystatin superfamily of proteins, derived from a common ancestor, is comprised of a diverse group of potent cysteine proteinase inhibitors and antibacterial/viral agents grouped into several families. This review concentrates on family 2 cystatins, namely, the human salivary cystatins and cystatin C. Emphasis is given to their physicochemical and functional properties at both the protein and the molecular level. The role of cystatins in disease processes, including those in the oral cavity, is also discussed. Finally, future directions for cystatin research in oral biology are presented.

Non-destructive evaluation of bacteria-infected watermelon seeds using visible/near-infrared hyperspectral imaging

2016 ◽  
Vol 97 (4) ◽  
pp. 1084-1092 ◽  
Author(s):  
Hoonsoo Lee ◽  
Moon S. Kim ◽  
Yu-Rim Song ◽  
Chang-Sik Oh ◽  
Hyoun-Sub Lim ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Non Destructive Evaluation ◽  
Non Destructive
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