Laser reflectance imaging of human organs and comparison with perfusion images View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1997-05

AUTHORS

S. Shanthi, M. Singh

ABSTRACT

Based on the principle of backscattering of laser radiation from tissues, a non-invasive PC-AT based reflectance imaging technique is developed. The laser beam from a semiconductor laser operating at 670 nm is guided to the tissue site by an optical fibre. The backscattered radiation is collected by another fibre placed in the same probe, and is detected by a photodiode-amplifier assembly. This probe is moved manually over the organs under observation, and the data after the ADC, interpolation and median filtering are displayed in the form of reflectance image of the organ along with grey scale. By this technique images of the human hands and forearms are obtained, which depend on the variations in their colour, composition and blood flow. A comparison is made with perfusion images, obtained by a Periflux laser Doppler flowmeter. These show that the reflectance images provide greater details of the tissue structure than the perfusion images. More... »

PAGES

253

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf02530046

DOI

http://dx.doi.org/10.1007/bf02530046

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1007184379

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/9246860


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0903", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biomedical Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Forearm", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hand", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Laser-Doppler Flowmetry", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Lasers", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Perfusion", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Regional Blood Flow", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Signal Processing, Computer-Assisted", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India", 
          "id": "http://www.grid.ac/institutes/grid.417969.4", 
          "name": [
            "Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shanthi", 
        "givenName": "S.", 
        "id": "sg:person.015434036347.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015434036347.77"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India", 
          "id": "http://www.grid.ac/institutes/grid.417969.4", 
          "name": [
            "Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Singh", 
        "givenName": "M.", 
        "id": "sg:person.01331040470.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01331040470.63"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf02442302", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033273925", 
          "https://doi.org/10.1007/bf02442302"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02446675", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021018287", 
          "https://doi.org/10.1007/bf02446675"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02441468", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048493138", 
          "https://doi.org/10.1007/bf02441468"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02441473", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036906702", 
          "https://doi.org/10.1007/bf02441473"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02522525", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038701715", 
          "https://doi.org/10.1007/bf02522525"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02441860", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032885305", 
          "https://doi.org/10.1007/bf02441860"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf02442712", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003211011", 
          "https://doi.org/10.1007/bf02442712"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1997-05", 
    "datePublishedReg": "1997-05-01", 
    "description": "Based on the principle of backscattering of laser radiation from tissues, a non-invasive PC-AT based reflectance imaging technique is developed. The laser beam from a semiconductor laser operating at 670 nm is guided to the tissue site by an optical fibre. The backscattered radiation is collected by another fibre placed in the same probe, and is detected by a photodiode-amplifier assembly. This probe is moved manually over the organs under observation, and the data after the ADC, interpolation and median filtering are displayed in the form of reflectance image of the organ along with grey scale. By this technique images of the human hands and forearms are obtained, which depend on the variations in their colour, composition and blood flow. A comparison is made with perfusion images, obtained by a Periflux laser Doppler flowmeter. These show that the reflectance images provide greater details of the tissue structure than the perfusion images.", 
    "genre": "article", 
    "id": "sg:pub.10.1007/bf02530046", 
    "inLanguage": "en", 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1005585", 
        "issn": [
          "1357-5481", 
          "1741-0444"
        ], 
        "name": "Medical & Biological Engineering & Computing", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "3", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "35"
      }
    ], 
    "keywords": [
      "Laser reflectance imaging", 
      "laser radiation", 
      "semiconductor lasers", 
      "laser beam", 
      "backscattered radiation", 
      "optical fiber", 
      "Periflux Laser Doppler Flowmeter", 
      "reflectance imaging", 
      "radiation", 
      "technique images", 
      "reflectance images", 
      "PC-AT", 
      "laser", 
      "beam", 
      "same probe", 
      "backscattering", 
      "probe", 
      "reflectance", 
      "greater detail", 
      "median filtering", 
      "images", 
      "tissue structure", 
      "imaging", 
      "fibers", 
      "structure", 
      "flow", 
      "gray scale", 
      "detail", 
      "flowmeter", 
      "technique", 
      "human hand", 
      "assembly", 
      "filtering", 
      "comparison", 
      "composition", 
      "principles", 
      "scale", 
      "color", 
      "interpolation", 
      "variation", 
      "ADC", 
      "human organs", 
      "data", 
      "observations", 
      "form", 
      "Doppler flowmeter", 
      "hand", 
      "perfusion images", 
      "tissue sites", 
      "laser Doppler flowmeter", 
      "sites", 
      "blood flow", 
      "tissue", 
      "forearm", 
      "organs", 
      "principle of backscattering", 
      "non-invasive PC-AT", 
      "photodiode-amplifier assembly"
    ], 
    "name": "Laser reflectance imaging of human organs and comparison with perfusion images", 
    "pagination": "253", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1007184379"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/bf02530046"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "9246860"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/bf02530046", 
      "https://app.dimensions.ai/details/publication/pub.1007184379"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2021-11-01T18:01", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211101/entities/gbq_results/article/article_272.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1007/bf02530046"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/bf02530046'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/bf02530046'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/bf02530046'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/bf02530046'


 

This table displays all metadata directly associated to this object as RDF triples.

203 TRIPLES      22 PREDICATES      104 URIs      89 LITERALS      19 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/bf02530046 schema:about N29979131b8bb46aa8b4977cb3dae9dd5
2 N2f25483295df49f38a09d1e9c91713a9
3 N3a2d509b4fd24ff6a56dc13ff35b5a8f
4 N3a75942ac6ba4926b801ffa4d15273a9
5 N3c116c217713472a9d3f5b89da95c84a
6 N3f95ad7fc03a4e6492a25d067becc2eb
7 N6554e19b691c411e86213ecc1bf3f262
8 N668d06f3d47b4fd48d47898ef1595e4d
9 N714ccaaf379246109982fc9d36b3648a
10 N8eb20344f7724789a3f0057a2d0f87b0
11 N9381ec4b8f064427b4efa704425380ba
12 Na4dc887d9b8747f085afb44662853e92
13 anzsrc-for:09
14 anzsrc-for:0903
15 schema:author Ne946b57d1cd9478f9efaac4e223bccc8
16 schema:citation sg:pub.10.1007/bf02441468
17 sg:pub.10.1007/bf02441473
18 sg:pub.10.1007/bf02441860
19 sg:pub.10.1007/bf02442302
20 sg:pub.10.1007/bf02442712
21 sg:pub.10.1007/bf02446675
22 sg:pub.10.1007/bf02522525
23 schema:datePublished 1997-05
24 schema:datePublishedReg 1997-05-01
25 schema:description Based on the principle of backscattering of laser radiation from tissues, a non-invasive PC-AT based reflectance imaging technique is developed. The laser beam from a semiconductor laser operating at 670 nm is guided to the tissue site by an optical fibre. The backscattered radiation is collected by another fibre placed in the same probe, and is detected by a photodiode-amplifier assembly. This probe is moved manually over the organs under observation, and the data after the ADC, interpolation and median filtering are displayed in the form of reflectance image of the organ along with grey scale. By this technique images of the human hands and forearms are obtained, which depend on the variations in their colour, composition and blood flow. A comparison is made with perfusion images, obtained by a Periflux laser Doppler flowmeter. These show that the reflectance images provide greater details of the tissue structure than the perfusion images.
26 schema:genre article
27 schema:inLanguage en
28 schema:isAccessibleForFree false
29 schema:isPartOf N996ee9c78c1d4e06bf899c471315d38e
30 Na97c3678f6304eeca498f8c3bb98876d
31 sg:journal.1005585
32 schema:keywords ADC
33 Doppler flowmeter
34 Laser reflectance imaging
35 PC-AT
36 Periflux Laser Doppler Flowmeter
37 assembly
38 backscattered radiation
39 backscattering
40 beam
41 blood flow
42 color
43 comparison
44 composition
45 data
46 detail
47 fibers
48 filtering
49 flow
50 flowmeter
51 forearm
52 form
53 gray scale
54 greater detail
55 hand
56 human hand
57 human organs
58 images
59 imaging
60 interpolation
61 laser
62 laser Doppler flowmeter
63 laser beam
64 laser radiation
65 median filtering
66 non-invasive PC-AT
67 observations
68 optical fiber
69 organs
70 perfusion images
71 photodiode-amplifier assembly
72 principle of backscattering
73 principles
74 probe
75 radiation
76 reflectance
77 reflectance images
78 reflectance imaging
79 same probe
80 scale
81 semiconductor lasers
82 sites
83 structure
84 technique
85 technique images
86 tissue
87 tissue sites
88 tissue structure
89 variation
90 schema:name Laser reflectance imaging of human organs and comparison with perfusion images
91 schema:pagination 253
92 schema:productId N258b1b568e794fcab28d0496296217f3
93 N6bd5fcb638204e08a3eb04fe191d45f5
94 Nad90ab523ca54185a31869ca1c70a802
95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007184379
96 https://doi.org/10.1007/bf02530046
97 schema:sdDatePublished 2021-11-01T18:01
98 schema:sdLicense https://scigraph.springernature.com/explorer/license/
99 schema:sdPublisher Nddbf88559c314d8bbc3590f1cc392d21
100 schema:url https://doi.org/10.1007/bf02530046
101 sgo:license sg:explorer/license/
102 sgo:sdDataset articles
103 rdf:type schema:ScholarlyArticle
104 N258b1b568e794fcab28d0496296217f3 schema:name doi
105 schema:value 10.1007/bf02530046
106 rdf:type schema:PropertyValue
107 N29979131b8bb46aa8b4977cb3dae9dd5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
108 schema:name Regional Blood Flow
109 rdf:type schema:DefinedTerm
110 N2f25483295df49f38a09d1e9c91713a9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
111 schema:name Middle Aged
112 rdf:type schema:DefinedTerm
113 N39e733a597e34fe2b4ce57ef4811f793 rdf:first sg:person.01331040470.63
114 rdf:rest rdf:nil
115 N3a2d509b4fd24ff6a56dc13ff35b5a8f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
116 schema:name Signal Processing, Computer-Assisted
117 rdf:type schema:DefinedTerm
118 N3a75942ac6ba4926b801ffa4d15273a9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
119 schema:name Perfusion
120 rdf:type schema:DefinedTerm
121 N3c116c217713472a9d3f5b89da95c84a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
122 schema:name Forearm
123 rdf:type schema:DefinedTerm
124 N3f95ad7fc03a4e6492a25d067becc2eb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Female
126 rdf:type schema:DefinedTerm
127 N6554e19b691c411e86213ecc1bf3f262 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Humans
129 rdf:type schema:DefinedTerm
130 N668d06f3d47b4fd48d47898ef1595e4d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Hand
132 rdf:type schema:DefinedTerm
133 N6bd5fcb638204e08a3eb04fe191d45f5 schema:name dimensions_id
134 schema:value pub.1007184379
135 rdf:type schema:PropertyValue
136 N714ccaaf379246109982fc9d36b3648a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
137 schema:name Male
138 rdf:type schema:DefinedTerm
139 N8eb20344f7724789a3f0057a2d0f87b0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name Adult
141 rdf:type schema:DefinedTerm
142 N9381ec4b8f064427b4efa704425380ba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Laser-Doppler Flowmetry
144 rdf:type schema:DefinedTerm
145 N996ee9c78c1d4e06bf899c471315d38e schema:volumeNumber 35
146 rdf:type schema:PublicationVolume
147 Na4dc887d9b8747f085afb44662853e92 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
148 schema:name Lasers
149 rdf:type schema:DefinedTerm
150 Na97c3678f6304eeca498f8c3bb98876d schema:issueNumber 3
151 rdf:type schema:PublicationIssue
152 Nad90ab523ca54185a31869ca1c70a802 schema:name pubmed_id
153 schema:value 9246860
154 rdf:type schema:PropertyValue
155 Nddbf88559c314d8bbc3590f1cc392d21 schema:name Springer Nature - SN SciGraph project
156 rdf:type schema:Organization
157 Ne946b57d1cd9478f9efaac4e223bccc8 rdf:first sg:person.015434036347.77
158 rdf:rest N39e733a597e34fe2b4ce57ef4811f793
159 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
160 schema:name Engineering
161 rdf:type schema:DefinedTerm
162 anzsrc-for:0903 schema:inDefinedTermSet anzsrc-for:
163 schema:name Biomedical Engineering
164 rdf:type schema:DefinedTerm
165 sg:journal.1005585 schema:issn 1357-5481
166 1741-0444
167 schema:name Medical & Biological Engineering & Computing
168 schema:publisher Springer Nature
169 rdf:type schema:Periodical
170 sg:person.01331040470.63 schema:affiliation grid-institutes:grid.417969.4
171 schema:familyName Singh
172 schema:givenName M.
173 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01331040470.63
174 rdf:type schema:Person
175 sg:person.015434036347.77 schema:affiliation grid-institutes:grid.417969.4
176 schema:familyName Shanthi
177 schema:givenName S.
178 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015434036347.77
179 rdf:type schema:Person
180 sg:pub.10.1007/bf02441468 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048493138
181 https://doi.org/10.1007/bf02441468
182 rdf:type schema:CreativeWork
183 sg:pub.10.1007/bf02441473 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036906702
184 https://doi.org/10.1007/bf02441473
185 rdf:type schema:CreativeWork
186 sg:pub.10.1007/bf02441860 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032885305
187 https://doi.org/10.1007/bf02441860
188 rdf:type schema:CreativeWork
189 sg:pub.10.1007/bf02442302 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033273925
190 https://doi.org/10.1007/bf02442302
191 rdf:type schema:CreativeWork
192 sg:pub.10.1007/bf02442712 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003211011
193 https://doi.org/10.1007/bf02442712
194 rdf:type schema:CreativeWork
195 sg:pub.10.1007/bf02446675 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021018287
196 https://doi.org/10.1007/bf02446675
197 rdf:type schema:CreativeWork
198 sg:pub.10.1007/bf02522525 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038701715
199 https://doi.org/10.1007/bf02522525
200 rdf:type schema:CreativeWork
201 grid-institutes:grid.417969.4 schema:alternateName Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India
202 schema:name Biomedical Engineering Division, Indian Institute of Technology, 600 036, Madras, India
203 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...