Automated and unsupervised detection of malarial parasites in microscopic images View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Yashasvi Purwar, Sirish L Shah, Gwen Clarke, Areej Almugairi, Atis Muehlenbachs

ABSTRACT

BACKGROUND: Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis) and prone to human error (leading to erroneous diagnosis), even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria. METHOD: A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives. RESULTS: The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites. CONCLUSION: Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method provides a consistent and robust way of generating the parasite clearance curves. More... »

PAGES

364

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1475-2875-10-364

DOI

http://dx.doi.org/10.1186/1475-2875-10-364

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1016604954

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22165867


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Automation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Clinical Laboratory Techniques", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Diagnostic Errors", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Image Processing, Computer-Assisted", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Malaria", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mass Screening", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Microscopy", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Parasitemia", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Parasitology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sensitivity and Specificity", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "University of Alberta", 
          "id": "https://www.grid.ac/institutes/grid.17089.37", 
          "name": [
            "Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Purwar", 
        "givenName": "Yashasvi", 
        "id": "sg:person.0651772170.76", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651772170.76"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Alberta", 
          "id": "https://www.grid.ac/institutes/grid.17089.37", 
          "name": [
            "Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shah", 
        "givenName": "Sirish L", 
        "id": "sg:person.016015511035.27", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016015511035.27"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Alberta Health Services", 
          "id": "https://www.grid.ac/institutes/grid.413574.0", 
          "name": [
            "Alberta Health Services, Province of Alberta, Edmonton, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Clarke", 
        "givenName": "Gwen", 
        "id": "sg:person.013154154342.15", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013154154342.15"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Alberta Health Services", 
          "id": "https://www.grid.ac/institutes/grid.413574.0", 
          "name": [
            "Alberta Health Services, Province of Alberta, Edmonton, Canada"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Almugairi", 
        "givenName": "Areej", 
        "id": "sg:person.01150562370.52", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01150562370.52"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Washington", 
          "id": "https://www.grid.ac/institutes/grid.34477.33", 
          "name": [
            "Departments of Pathology and Laboratory Medicine, University of Washington, Seattle, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Muehlenbachs", 
        "givenName": "Atis", 
        "id": "sg:person.01265010770.77", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265010770.77"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11517-006-0044-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001753486", 
          "https://doi.org/10.1007/s11517-006-0044-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11517-006-0044-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001753486", 
          "https://doi.org/10.1007/s11517-006-0044-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1475-2875-8-153", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013692985", 
          "https://doi.org/10.1186/1475-2875-8-153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cviu.2009.08.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019873942"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mimet.2006.05.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021552255"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1365-2257.1999.00220.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022677743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1475-2875-10-278", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039355196", 
          "https://doi.org/10.1186/1475-2875-10-278"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/83.902291", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061240267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1049/ic:20020290", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098721501"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-12", 
    "datePublishedReg": "2011-12-01", 
    "description": "BACKGROUND: Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis) and prone to human error (leading to erroneous diagnosis), even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria.\nMETHOD: A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives.\nRESULTS: The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites.\nCONCLUSION: Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method provides a consistent and robust way of generating the parasite clearance curves.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/1475-2875-10-364", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1030597", 
        "issn": [
          "1475-2875"
        ], 
        "name": "Malaria Journal", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "10"
      }
    ], 
    "name": "Automated and unsupervised detection of malarial parasites in microscopic images", 
    "pagination": "364", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "4f1e21d84763283cad552df88213b5a625cb529dd7acb6ac91813cae2e43212c"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "22165867"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101139802"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/1475-2875-10-364"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1016604954"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/1475-2875-10-364", 
      "https://app.dimensions.ai/details/publication/pub.1016604954"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T22:31", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8690_00000511.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2F1475-2875-10-364"
  }
]
 

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.10.1186/1475-2875-10-364'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1475-2875-10-364'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/1475-2875-10-364'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1475-2875-10-364'


 

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

173 TRIPLES      21 PREDICATES      48 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/1475-2875-10-364 schema:about N03d748d464b04dc3bfca76e3086bbb14
2 N32f151252f9c43bf8bc0fa7cc5170e8d
3 N50129a4f8b18402ca6b626f7ca4a4f6c
4 N53d49c968a554bc0a85cae35c5455630
5 N69274ab98fb646ad913b43bd8f6b5cbc
6 N6c38001a35664046a355d5f9bd11dba1
7 Nb98cce22d4934d2f90ddd45a9d347da9
8 Nd25ab617a8d842ef8e60a41cfb32e5cd
9 Nd77b99c3be5b46088c6fa10d5c0703eb
10 Ne31eb0b9889942659cad991d00fdbcac
11 Nf893050c0f45493991edee0e1cf6e3b6
12 anzsrc-for:08
13 anzsrc-for:0801
14 schema:author Na1803e72bd37499f929693ef1190a825
15 schema:citation sg:pub.10.1007/s11517-006-0044-2
16 sg:pub.10.1186/1475-2875-10-278
17 sg:pub.10.1186/1475-2875-8-153
18 https://doi.org/10.1016/j.cviu.2009.08.003
19 https://doi.org/10.1016/j.mimet.2006.05.017
20 https://doi.org/10.1046/j.1365-2257.1999.00220.x
21 https://doi.org/10.1049/ic:20020290
22 https://doi.org/10.1109/83.902291
23 schema:datePublished 2011-12
24 schema:datePublishedReg 2011-12-01
25 schema:description BACKGROUND: Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis) and prone to human error (leading to erroneous diagnosis), even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria. METHOD: A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives. RESULTS: The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites. CONCLUSION: Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method provides a consistent and robust way of generating the parasite clearance curves.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree true
29 schema:isPartOf N1a0fddc15de847a89963d69e44b8c6c4
30 N1d4a0454d71d4675af081fd89bddee65
31 sg:journal.1030597
32 schema:name Automated and unsupervised detection of malarial parasites in microscopic images
33 schema:pagination 364
34 schema:productId N15c5cd4a4ac147af8e3edfb158d16b7e
35 N1874886ee151477f848bdfc4d8cf2281
36 N317d29cc04d941459b5e4df9833cb84d
37 N85bfa60b135a429da46bce85e2f17d69
38 Nea7cc5b3c5fc42d39e4a38354626e04d
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016604954
40 https://doi.org/10.1186/1475-2875-10-364
41 schema:sdDatePublished 2019-04-10T22:31
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher Nfc04ef33f8604cae988de6513027270d
44 schema:url http://link.springer.com/10.1186%2F1475-2875-10-364
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N03d748d464b04dc3bfca76e3086bbb14 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
49 schema:name Parasitology
50 rdf:type schema:DefinedTerm
51 N15c5cd4a4ac147af8e3edfb158d16b7e schema:name nlm_unique_id
52 schema:value 101139802
53 rdf:type schema:PropertyValue
54 N1874886ee151477f848bdfc4d8cf2281 schema:name pubmed_id
55 schema:value 22165867
56 rdf:type schema:PropertyValue
57 N1928e29d04d84a279a8ef43376395a89 rdf:first sg:person.01150562370.52
58 rdf:rest Nc1a824bb56f64f4b87013e2fa9441f5c
59 N198dcee88ee24d89b9100c5b6653bc0e rdf:first sg:person.016015511035.27
60 rdf:rest Nced373d650684ae0bc67ce59fa38efba
61 N1a0fddc15de847a89963d69e44b8c6c4 schema:issueNumber 1
62 rdf:type schema:PublicationIssue
63 N1d4a0454d71d4675af081fd89bddee65 schema:volumeNumber 10
64 rdf:type schema:PublicationVolume
65 N317d29cc04d941459b5e4df9833cb84d schema:name readcube_id
66 schema:value 4f1e21d84763283cad552df88213b5a625cb529dd7acb6ac91813cae2e43212c
67 rdf:type schema:PropertyValue
68 N32f151252f9c43bf8bc0fa7cc5170e8d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
69 schema:name Malaria
70 rdf:type schema:DefinedTerm
71 N50129a4f8b18402ca6b626f7ca4a4f6c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Microscopy
73 rdf:type schema:DefinedTerm
74 N53d49c968a554bc0a85cae35c5455630 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
75 schema:name Mass Screening
76 rdf:type schema:DefinedTerm
77 N69274ab98fb646ad913b43bd8f6b5cbc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
78 schema:name Clinical Laboratory Techniques
79 rdf:type schema:DefinedTerm
80 N6c38001a35664046a355d5f9bd11dba1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
81 schema:name Image Processing, Computer-Assisted
82 rdf:type schema:DefinedTerm
83 N85bfa60b135a429da46bce85e2f17d69 schema:name doi
84 schema:value 10.1186/1475-2875-10-364
85 rdf:type schema:PropertyValue
86 Na1803e72bd37499f929693ef1190a825 rdf:first sg:person.0651772170.76
87 rdf:rest N198dcee88ee24d89b9100c5b6653bc0e
88 Nb98cce22d4934d2f90ddd45a9d347da9 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
89 schema:name Diagnostic Errors
90 rdf:type schema:DefinedTerm
91 Nc1a824bb56f64f4b87013e2fa9441f5c rdf:first sg:person.01265010770.77
92 rdf:rest rdf:nil
93 Nced373d650684ae0bc67ce59fa38efba rdf:first sg:person.013154154342.15
94 rdf:rest N1928e29d04d84a279a8ef43376395a89
95 Nd25ab617a8d842ef8e60a41cfb32e5cd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
96 schema:name Automation
97 rdf:type schema:DefinedTerm
98 Nd77b99c3be5b46088c6fa10d5c0703eb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
99 schema:name Parasitemia
100 rdf:type schema:DefinedTerm
101 Ne31eb0b9889942659cad991d00fdbcac schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
102 schema:name Sensitivity and Specificity
103 rdf:type schema:DefinedTerm
104 Nea7cc5b3c5fc42d39e4a38354626e04d schema:name dimensions_id
105 schema:value pub.1016604954
106 rdf:type schema:PropertyValue
107 Nf893050c0f45493991edee0e1cf6e3b6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
108 schema:name Humans
109 rdf:type schema:DefinedTerm
110 Nfc04ef33f8604cae988de6513027270d schema:name Springer Nature - SN SciGraph project
111 rdf:type schema:Organization
112 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
113 schema:name Information and Computing Sciences
114 rdf:type schema:DefinedTerm
115 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
116 schema:name Artificial Intelligence and Image Processing
117 rdf:type schema:DefinedTerm
118 sg:journal.1030597 schema:issn 1475-2875
119 schema:name Malaria Journal
120 rdf:type schema:Periodical
121 sg:person.01150562370.52 schema:affiliation https://www.grid.ac/institutes/grid.413574.0
122 schema:familyName Almugairi
123 schema:givenName Areej
124 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01150562370.52
125 rdf:type schema:Person
126 sg:person.01265010770.77 schema:affiliation https://www.grid.ac/institutes/grid.34477.33
127 schema:familyName Muehlenbachs
128 schema:givenName Atis
129 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265010770.77
130 rdf:type schema:Person
131 sg:person.013154154342.15 schema:affiliation https://www.grid.ac/institutes/grid.413574.0
132 schema:familyName Clarke
133 schema:givenName Gwen
134 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013154154342.15
135 rdf:type schema:Person
136 sg:person.016015511035.27 schema:affiliation https://www.grid.ac/institutes/grid.17089.37
137 schema:familyName Shah
138 schema:givenName Sirish L
139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016015511035.27
140 rdf:type schema:Person
141 sg:person.0651772170.76 schema:affiliation https://www.grid.ac/institutes/grid.17089.37
142 schema:familyName Purwar
143 schema:givenName Yashasvi
144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0651772170.76
145 rdf:type schema:Person
146 sg:pub.10.1007/s11517-006-0044-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001753486
147 https://doi.org/10.1007/s11517-006-0044-2
148 rdf:type schema:CreativeWork
149 sg:pub.10.1186/1475-2875-10-278 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039355196
150 https://doi.org/10.1186/1475-2875-10-278
151 rdf:type schema:CreativeWork
152 sg:pub.10.1186/1475-2875-8-153 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013692985
153 https://doi.org/10.1186/1475-2875-8-153
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1016/j.cviu.2009.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019873942
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1016/j.mimet.2006.05.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021552255
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1046/j.1365-2257.1999.00220.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1022677743
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1049/ic:20020290 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098721501
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1109/83.902291 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061240267
164 rdf:type schema:CreativeWork
165 https://www.grid.ac/institutes/grid.17089.37 schema:alternateName University of Alberta
166 schema:name Department of Chemical and Materials Engineering, University of Alberta, Edmonton, Canada
167 rdf:type schema:Organization
168 https://www.grid.ac/institutes/grid.34477.33 schema:alternateName University of Washington
169 schema:name Departments of Pathology and Laboratory Medicine, University of Washington, Seattle, USA
170 rdf:type schema:Organization
171 https://www.grid.ac/institutes/grid.413574.0 schema:alternateName Alberta Health Services
172 schema:name Alberta Health Services, Province of Alberta, Edmonton, Canada
173 rdf:type schema:Organization
 




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


...