Amadeus Holmer, C. Hornberger, Thomas Wild, F. Siemers
{"title":"Hyperspectral imaging of the degradation of meat and comparison with necrotic tissue in human wounds","authors":"Amadeus Holmer, C. Hornberger, Thomas Wild, F. Siemers","doi":"10.1255/JSI.2019.A9","DOIUrl":null,"url":null,"abstract":"The objective evaluation of scattering tissue and the discrimination of tissue types is an issue that cannot be\nsolved with colour cameras and image processing alone in many cases. Examples can be found in the determination of\nfreshness and ageing of meat, and the discrimination of tissue types in food technology. In medical applications tissue\ndiscrimination is also an issue, e.g. in wound diagnostics. A novel hyperspectral imaging setup with powerful signal\nanalysis algorithms is presented which is capable of addressing these topics. The spectral approach allows the chemical\nanalysis of material and tissues and the measurement of their temporal change. We present a method of hyperspectral\nimaging in the visible-near infrared range which allows both the separation and spatial allocation of different tissue types\nin a sample, as well as the temporal changes of the tissue as an effect of ageing. To prove the capability of the method,\nthe ageing of meat (slices of pork) was measured and, as a medical example, the application of the hyperspectral imaging\nsetup for the recording of wound tissue is presented. The method shows the ability to discriminate the different tissue\ncomponents of pork meat, and the ageing of the meat is observable as changes in spectral features. An additional result of\n our study is the fact that some spectral features, which seem to be typical for the ageing of the meat, are similar to those\nobserved in the necrotic tissue from wound diagnostics in medicine.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spectral Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1255/JSI.2019.A9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Chemistry","Score":null,"Total":0}
引用次数: 5
Abstract
The objective evaluation of scattering tissue and the discrimination of tissue types is an issue that cannot be
solved with colour cameras and image processing alone in many cases. Examples can be found in the determination of
freshness and ageing of meat, and the discrimination of tissue types in food technology. In medical applications tissue
discrimination is also an issue, e.g. in wound diagnostics. A novel hyperspectral imaging setup with powerful signal
analysis algorithms is presented which is capable of addressing these topics. The spectral approach allows the chemical
analysis of material and tissues and the measurement of their temporal change. We present a method of hyperspectral
imaging in the visible-near infrared range which allows both the separation and spatial allocation of different tissue types
in a sample, as well as the temporal changes of the tissue as an effect of ageing. To prove the capability of the method,
the ageing of meat (slices of pork) was measured and, as a medical example, the application of the hyperspectral imaging
setup for the recording of wound tissue is presented. The method shows the ability to discriminate the different tissue
components of pork meat, and the ageing of the meat is observable as changes in spectral features. An additional result of
our study is the fact that some spectral features, which seem to be typical for the ageing of the meat, are similar to those
observed in the necrotic tissue from wound diagnostics in medicine.
期刊介绍:
JSI—Journal of Spectral Imaging is the first journal to bring together current research from the diverse research areas of spectral, hyperspectral and chemical imaging as well as related areas such as remote sensing, chemometrics, data mining and data handling for spectral image data. We believe all those working in Spectral Imaging can benefit from the knowledge of others even in widely different fields. We welcome original research papers, letters, review articles, tutorial papers, short communications and technical notes.