A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues
•Hyperspectral image system techniques.•HeLa cell line hyperspectral cube image in 17 channels.•Hyperspectral image preprocessing methods.•Hyperspectral image analysis.•Hyperspectral image diagnostic applications for malignant diseases. Hyperspectral fluorescence imaging (HFI) is a well-known techni...
Gespeichert in:
Veröffentlicht in: | Photodiagnosis and photodynamic therapy 2021-03, Vol.33, p.102165-102165, Article 102165 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 102165 |
---|---|
container_issue | |
container_start_page | 102165 |
container_title | Photodiagnosis and photodynamic therapy |
container_volume | 33 |
creator | Rehman, Aziz ul Qureshi, Shahzad Ahmad |
description | •Hyperspectral image system techniques.•HeLa cell line hyperspectral cube image in 17 channels.•Hyperspectral image preprocessing methods.•Hyperspectral image analysis.•Hyperspectral image diagnostic applications for malignant diseases.
Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed. |
doi_str_mv | 10.1016/j.pdpdt.2020.102165 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2474501568</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1572100020305196</els_id><sourcerecordid>2474501568</sourcerecordid><originalsourceid>FETCH-LOGICAL-c359t-6056115381093f260c9f69307050369f9bde6fc48fd6b710f446ca712ce48ebc3</originalsourceid><addsrcrecordid>eNp9kLlOxDAQhi0E4n4CJOSSJss4PpIUFAhxSUg0UFuJM971Khd2FtiO1-D1eBK8u0BJNYf-mV__R8gJgwkDps7nk6Ee6nGSQrrapEzJLbLP8ownTBbZduxlliYMAPbIQQhzAC4KELtkj3Oe8xTEPrGX1OOrwzfaWzrOkLZYO1M2dLYc0IcBzejj5Npy6ropDcswYhto2dV00bXufbUsm2nv3Thrw9fHJ3UdrVzf9NP1m9GFsMBwRHZs2QQ8_qmH5Pnm-unqLnl4vL2_unxIDJfFmCiQijHJcwYFt6kCU1hVcMhAAleFLaoalTUit7WqMgZWCGXKjKUGRY6V4YfkbPN38P1L9B1164LBpik77BdBpyITEphUeZTyjdT4PgSPVg8-xvRLzUCvAOu5XgPWK8B6Azhenf4YLKqI6u_ml2gUXGwEGGNGsF4H47AzEauPMHXdu38NvgE5ko6k</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2474501568</pqid></control><display><type>article</type><title>A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues</title><source>MEDLINE</source><source>ScienceDirect Journals (5 years ago - present)</source><creator>Rehman, Aziz ul ; Qureshi, Shahzad Ahmad</creator><creatorcontrib>Rehman, Aziz ul ; Qureshi, Shahzad Ahmad</creatorcontrib><description>•Hyperspectral image system techniques.•HeLa cell line hyperspectral cube image in 17 channels.•Hyperspectral image preprocessing methods.•Hyperspectral image analysis.•Hyperspectral image diagnostic applications for malignant diseases.
Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.</description><identifier>ISSN: 1572-1000</identifier><identifier>EISSN: 1873-1597</identifier><identifier>DOI: 10.1016/j.pdpdt.2020.102165</identifier><identifier>PMID: 33383204</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Algorithms ; Breast cancer ; Deep learning ; Hyper-spectral image classification ; Hyper-spectral imaging system ; Hyper-spectral imaging techniques hyperspectral image applications ; Hyperspectral Imaging ; Lung cancer ; Neural Networks, Computer ; Ophthalmology ; Photochemotherapy - methods ; Photosensitizing Agents ; Support vector machines ; Unmixing algorithms</subject><ispartof>Photodiagnosis and photodynamic therapy, 2021-03, Vol.33, p.102165-102165, Article 102165</ispartof><rights>2020 Elsevier B.V.</rights><rights>Copyright © 2020 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-6056115381093f260c9f69307050369f9bde6fc48fd6b710f446ca712ce48ebc3</citedby><cites>FETCH-LOGICAL-c359t-6056115381093f260c9f69307050369f9bde6fc48fd6b710f446ca712ce48ebc3</cites><orcidid>0000-0001-8605-5763 ; 0000-0001-8213-1431</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.pdpdt.2020.102165$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33383204$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rehman, Aziz ul</creatorcontrib><creatorcontrib>Qureshi, Shahzad Ahmad</creatorcontrib><title>A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues</title><title>Photodiagnosis and photodynamic therapy</title><addtitle>Photodiagnosis Photodyn Ther</addtitle><description>•Hyperspectral image system techniques.•HeLa cell line hyperspectral cube image in 17 channels.•Hyperspectral image preprocessing methods.•Hyperspectral image analysis.•Hyperspectral image diagnostic applications for malignant diseases.
Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.</description><subject>Algorithms</subject><subject>Breast cancer</subject><subject>Deep learning</subject><subject>Hyper-spectral image classification</subject><subject>Hyper-spectral imaging system</subject><subject>Hyper-spectral imaging techniques hyperspectral image applications</subject><subject>Hyperspectral Imaging</subject><subject>Lung cancer</subject><subject>Neural Networks, Computer</subject><subject>Ophthalmology</subject><subject>Photochemotherapy - methods</subject><subject>Photosensitizing Agents</subject><subject>Support vector machines</subject><subject>Unmixing algorithms</subject><issn>1572-1000</issn><issn>1873-1597</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kLlOxDAQhi0E4n4CJOSSJss4PpIUFAhxSUg0UFuJM971Khd2FtiO1-D1eBK8u0BJNYf-mV__R8gJgwkDps7nk6Ee6nGSQrrapEzJLbLP8ownTBbZduxlliYMAPbIQQhzAC4KELtkj3Oe8xTEPrGX1OOrwzfaWzrOkLZYO1M2dLYc0IcBzejj5Npy6ropDcswYhto2dV00bXufbUsm2nv3Thrw9fHJ3UdrVzf9NP1m9GFsMBwRHZs2QQ8_qmH5Pnm-unqLnl4vL2_unxIDJfFmCiQijHJcwYFt6kCU1hVcMhAAleFLaoalTUit7WqMgZWCGXKjKUGRY6V4YfkbPN38P1L9B1164LBpik77BdBpyITEphUeZTyjdT4PgSPVg8-xvRLzUCvAOu5XgPWK8B6Azhenf4YLKqI6u_ml2gUXGwEGGNGsF4H47AzEauPMHXdu38NvgE5ko6k</recordid><startdate>202103</startdate><enddate>202103</enddate><creator>Rehman, Aziz ul</creator><creator>Qureshi, Shahzad Ahmad</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8605-5763</orcidid><orcidid>https://orcid.org/0000-0001-8213-1431</orcidid></search><sort><creationdate>202103</creationdate><title>A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues</title><author>Rehman, Aziz ul ; Qureshi, Shahzad Ahmad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-6056115381093f260c9f69307050369f9bde6fc48fd6b710f446ca712ce48ebc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Breast cancer</topic><topic>Deep learning</topic><topic>Hyper-spectral image classification</topic><topic>Hyper-spectral imaging system</topic><topic>Hyper-spectral imaging techniques hyperspectral image applications</topic><topic>Hyperspectral Imaging</topic><topic>Lung cancer</topic><topic>Neural Networks, Computer</topic><topic>Ophthalmology</topic><topic>Photochemotherapy - methods</topic><topic>Photosensitizing Agents</topic><topic>Support vector machines</topic><topic>Unmixing algorithms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rehman, Aziz ul</creatorcontrib><creatorcontrib>Qureshi, Shahzad Ahmad</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Photodiagnosis and photodynamic therapy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rehman, Aziz ul</au><au>Qureshi, Shahzad Ahmad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues</atitle><jtitle>Photodiagnosis and photodynamic therapy</jtitle><addtitle>Photodiagnosis Photodyn Ther</addtitle><date>2021-03</date><risdate>2021</risdate><volume>33</volume><spage>102165</spage><epage>102165</epage><pages>102165-102165</pages><artnum>102165</artnum><issn>1572-1000</issn><eissn>1873-1597</eissn><abstract>•Hyperspectral image system techniques.•HeLa cell line hyperspectral cube image in 17 channels.•Hyperspectral image preprocessing methods.•Hyperspectral image analysis.•Hyperspectral image diagnostic applications for malignant diseases.
Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research field and is considered a non-invasive tool for tissue diagnosis. This review article gives a brief introduction to acquisition methods, including the image preprocessing methods, feature selection and extraction methods, data classification techniques and medical image analysis along with recent relevant references. The process of fusion of unsupervised unmixing techniques with other classification methods, like the combination of support vector machine with an artificial neural network, the latest snapshot Hyperspectral imaging (HSI) and vortex analysis techniques are also outlined. Finally, the recent applications of hyperspectral images in cellular differentiation of various types of cancer are discussed.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>33383204</pmid><doi>10.1016/j.pdpdt.2020.102165</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-8605-5763</orcidid><orcidid>https://orcid.org/0000-0001-8213-1431</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1572-1000 |
ispartof | Photodiagnosis and photodynamic therapy, 2021-03, Vol.33, p.102165-102165, Article 102165 |
issn | 1572-1000 1873-1597 |
language | eng |
recordid | cdi_proquest_miscellaneous_2474501568 |
source | MEDLINE; ScienceDirect Journals (5 years ago - present) |
subjects | Algorithms Breast cancer Deep learning Hyper-spectral image classification Hyper-spectral imaging system Hyper-spectral imaging techniques hyperspectral image applications Hyperspectral Imaging Lung cancer Neural Networks, Computer Ophthalmology Photochemotherapy - methods Photosensitizing Agents Support vector machines Unmixing algorithms |
title | A review of the medical hyperspectral imaging systems and unmixing algorithms’ in biological tissues |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T16%3A55%3A39IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20review%20of%20the%20medical%20hyperspectral%20imaging%20systems%20and%20unmixing%20algorithms%E2%80%99%20in%20biological%20tissues&rft.jtitle=Photodiagnosis%20and%20photodynamic%20therapy&rft.au=Rehman,%20Aziz%20ul&rft.date=2021-03&rft.volume=33&rft.spage=102165&rft.epage=102165&rft.pages=102165-102165&rft.artnum=102165&rft.issn=1572-1000&rft.eissn=1873-1597&rft_id=info:doi/10.1016/j.pdpdt.2020.102165&rft_dat=%3Cproquest_cross%3E2474501568%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2474501568&rft_id=info:pmid/33383204&rft_els_id=S1572100020305196&rfr_iscdi=true |