Image Processing Approach for Detection of Leukocytes in Peripheral Blood Smears View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-05

AUTHORS

Roopa B. Hegde, Keerthana Prasad, Harishchandra Hebbar, Brij Mohan Kumar Singh

ABSTRACT

Peripheral blood smear analysis is a gold-standard method used in laboratories to diagnose many hematological disorders. Leukocyte analysis helps in monitoring and identifying health status of a person. Segmentation is an important step in the process of automation of analysis which would reduce the burden on hematologists and make the process simpler. The segmentation of leukocytes is a challenging task due to variations in appearance of cells across the slide. In the proposed study, an automated method to detect nuclei and to extract leukocytes from peripheral blood smear images with color and illumination variations is presented. Arithmetic and morphological operations are used for nuclei detection and active contours method is for leukocyte detection. The results demonstrate that the proposed method detects nuclei and leukocytes with Dice score of 0.97 and 0.96 respectively. The overall sensitivity of the method is around 96%. More... »

PAGES

114

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10916-019-1219-3

DOI

http://dx.doi.org/10.1007/s10916-019-1219-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112947256

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30903283


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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "School of Information Sciences, MAHE, Manipal, India", 
            "Department of Electronics and Communication, NMAMIT, Nitte, Karkala, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hegde", 
        "givenName": "Roopa B.", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "School of Information Sciences, MAHE, Manipal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Prasad", 
        "givenName": "Keerthana", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "School of Information Sciences, MAHE, Manipal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hebbar", 
        "givenName": "Harishchandra", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Kasturba Medical College", 
          "id": "https://www.grid.ac/institutes/grid.465547.1", 
          "name": [
            "Kasturba Medical College, MAHE, Manipal, India"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Singh", 
        "givenName": "Brij Mohan Kumar", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1155/2012/574184", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003225550"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2012/183879", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004265279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/2016/9514707", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007780825"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jss.2012.04.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011343748"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11760-014-0715-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014745789", 
          "https://doi.org/10.1007/s11760-014-0715-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00133570", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016330466", 
          "https://doi.org/10.1007/bf00133570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00133570", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016330466", 
          "https://doi.org/10.1007/bf00133570"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbe.2014.10.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026629648"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cmpb.2011.08.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026831292"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compmedimag.2011.01.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032674117"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12575-009-9011-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033826498", 
          "https://doi.org/10.1007/s12575-009-9011-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12575-009-9011-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033826498", 
          "https://doi.org/10.1007/s12575-009-9011-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3923/jas.2010.959.966", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034395601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.micron.2011.03.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038225855"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/s140916128", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039622884"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4103/2153-3539.109883", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043575597"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10916-011-9679-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047722557", 
          "https://doi.org/10.1007/s10916-011-9679-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1142/s1793545814500072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051544363"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11760-012-0393-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052271564", 
          "https://doi.org/10.1007/s11760-012-0393-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/access.2016.2636218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061252366"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/titb.2005.847515", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061656377"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/titb.2005.847515", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061656377"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1079048010", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1085764954", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbe.2017.07.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1090900359"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.measurement.2017.11.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092637516"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/sibgrapi.2007.33", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1094903105"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/icip.2011.6115881", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095282944"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/cicsyn.2015.36", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1095751857"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10916-018-0912-y", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1101079169", 
          "https://doi.org/10.1007/s10916-018-0912-y"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-05", 
    "datePublishedReg": "2019-05-01", 
    "description": "Peripheral blood smear analysis is a gold-standard method used in laboratories to diagnose many hematological disorders. Leukocyte analysis helps in monitoring and identifying health status of a person. Segmentation is an important step in the process of automation of analysis which would reduce the burden on hematologists and make the process simpler. The segmentation of leukocytes is a challenging task due to variations in appearance of cells across the slide. In the proposed study, an automated method to detect nuclei and to extract leukocytes from peripheral blood smear images with color and illumination variations is presented. Arithmetic and morphological operations are used for nuclei detection and active contours method is for leukocyte detection. The results demonstrate that the proposed method detects nuclei and leukocytes with Dice score of 0.97 and 0.96 respectively. The overall sensitivity of the method is around 96%.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10916-019-1219-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1088158", 
        "issn": [
          "0148-5598", 
          "1573-689X"
        ], 
        "name": "Journal of Medical Systems", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "5", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "43"
      }
    ], 
    "name": "Image Processing Approach for Detection of Leukocytes in Peripheral Blood Smears", 
    "pagination": "114", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "aca32e5acf6c5a5af6bd2ba8575718f48f3c73c6cd3d21a63a03b7c87ee48e4a"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30903283"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "7806056"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10916-019-1219-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112947256"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10916-019-1219-3", 
      "https://app.dimensions.ai/details/publication/pub.1112947256"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:17", 
    "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/v90/0000000368_0000000368/records_78934_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10916-019-1219-3"
  }
]
 

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/s10916-019-1219-3'

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/s10916-019-1219-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10916-019-1219-3'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10916-019-1219-3'


 

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

178 TRIPLES      21 PREDICATES      56 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10916-019-1219-3 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author Ne1f7198d3f3b4870a17c41d7aafbdbc7
4 schema:citation sg:pub.10.1007/bf00133570
5 sg:pub.10.1007/s10916-011-9679-0
6 sg:pub.10.1007/s10916-018-0912-y
7 sg:pub.10.1007/s11760-012-0393-2
8 sg:pub.10.1007/s11760-014-0715-7
9 sg:pub.10.1007/s12575-009-9011-2
10 https://app.dimensions.ai/details/publication/pub.1079048010
11 https://app.dimensions.ai/details/publication/pub.1085764954
12 https://doi.org/10.1016/j.bbe.2014.10.005
13 https://doi.org/10.1016/j.bbe.2017.07.003
14 https://doi.org/10.1016/j.cmpb.2011.08.004
15 https://doi.org/10.1016/j.compmedimag.2011.01.003
16 https://doi.org/10.1016/j.jss.2012.04.012
17 https://doi.org/10.1016/j.measurement.2017.11.002
18 https://doi.org/10.1016/j.micron.2011.03.009
19 https://doi.org/10.1109/access.2016.2636218
20 https://doi.org/10.1109/cicsyn.2015.36
21 https://doi.org/10.1109/icip.2011.6115881
22 https://doi.org/10.1109/sibgrapi.2007.33
23 https://doi.org/10.1109/titb.2005.847515
24 https://doi.org/10.1142/s1793545814500072
25 https://doi.org/10.1155/2012/183879
26 https://doi.org/10.1155/2012/574184
27 https://doi.org/10.1155/2016/9514707
28 https://doi.org/10.3390/s140916128
29 https://doi.org/10.3923/jas.2010.959.966
30 https://doi.org/10.4103/2153-3539.109883
31 schema:datePublished 2019-05
32 schema:datePublishedReg 2019-05-01
33 schema:description Peripheral blood smear analysis is a gold-standard method used in laboratories to diagnose many hematological disorders. Leukocyte analysis helps in monitoring and identifying health status of a person. Segmentation is an important step in the process of automation of analysis which would reduce the burden on hematologists and make the process simpler. The segmentation of leukocytes is a challenging task due to variations in appearance of cells across the slide. In the proposed study, an automated method to detect nuclei and to extract leukocytes from peripheral blood smear images with color and illumination variations is presented. Arithmetic and morphological operations are used for nuclei detection and active contours method is for leukocyte detection. The results demonstrate that the proposed method detects nuclei and leukocytes with Dice score of 0.97 and 0.96 respectively. The overall sensitivity of the method is around 96%.
34 schema:genre research_article
35 schema:inLanguage en
36 schema:isAccessibleForFree false
37 schema:isPartOf N668f1c083b66443998a86ccf9efb2a39
38 Na505b134da8f46f39a2f5fde01c44be0
39 sg:journal.1088158
40 schema:name Image Processing Approach for Detection of Leukocytes in Peripheral Blood Smears
41 schema:pagination 114
42 schema:productId N359b5f4a314c42c3b63841e6e7049278
43 N483eaa919ac74782ba7327738e1290a1
44 N4c2a0cd3a87145d8b0e0142fe9357cd9
45 Nea93721b849a40deb6214f37de70eede
46 Nf690c3f079a643afa77ce34b9e3cf1fb
47 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112947256
48 https://doi.org/10.1007/s10916-019-1219-3
49 schema:sdDatePublished 2019-04-11T13:17
50 schema:sdLicense https://scigraph.springernature.com/explorer/license/
51 schema:sdPublisher N3236c8de07324055ad8fde00ef7b5287
52 schema:url https://link.springer.com/10.1007%2Fs10916-019-1219-3
53 sgo:license sg:explorer/license/
54 sgo:sdDataset articles
55 rdf:type schema:ScholarlyArticle
56 N006eb16b70bd4e7f9d3037eb3a245c09 schema:affiliation https://www.grid.ac/institutes/grid.465547.1
57 schema:familyName Singh
58 schema:givenName Brij Mohan Kumar
59 rdf:type schema:Person
60 N2340b7762b34420a836b2c47fe5c41f2 rdf:first N006eb16b70bd4e7f9d3037eb3a245c09
61 rdf:rest rdf:nil
62 N2682bd96e3de4d579d724a96fbff5ab7 schema:affiliation Nec2fcfbca70b4a9bb89b21ca5c248f58
63 schema:familyName Hebbar
64 schema:givenName Harishchandra
65 rdf:type schema:Person
66 N2a810360a04545ecb5fe184a87cc9be2 rdf:first N2682bd96e3de4d579d724a96fbff5ab7
67 rdf:rest N2340b7762b34420a836b2c47fe5c41f2
68 N3236c8de07324055ad8fde00ef7b5287 schema:name Springer Nature - SN SciGraph project
69 rdf:type schema:Organization
70 N359b5f4a314c42c3b63841e6e7049278 schema:name pubmed_id
71 schema:value 30903283
72 rdf:type schema:PropertyValue
73 N483eaa919ac74782ba7327738e1290a1 schema:name doi
74 schema:value 10.1007/s10916-019-1219-3
75 rdf:type schema:PropertyValue
76 N4c2a0cd3a87145d8b0e0142fe9357cd9 schema:name dimensions_id
77 schema:value pub.1112947256
78 rdf:type schema:PropertyValue
79 N668f1c083b66443998a86ccf9efb2a39 schema:issueNumber 5
80 rdf:type schema:PublicationIssue
81 Na505b134da8f46f39a2f5fde01c44be0 schema:volumeNumber 43
82 rdf:type schema:PublicationVolume
83 Nd442fa7ac31e4e6387598a8c95f2262a schema:affiliation Nf70c544e98dd4a779ea77c9f1a5a4f74
84 schema:familyName Hegde
85 schema:givenName Roopa B.
86 rdf:type schema:Person
87 Ne1f7198d3f3b4870a17c41d7aafbdbc7 rdf:first Nd442fa7ac31e4e6387598a8c95f2262a
88 rdf:rest Nf48ccb00b5784bc39495866e32571fc5
89 Nea93721b849a40deb6214f37de70eede schema:name readcube_id
90 schema:value aca32e5acf6c5a5af6bd2ba8575718f48f3c73c6cd3d21a63a03b7c87ee48e4a
91 rdf:type schema:PropertyValue
92 Nec2fcfbca70b4a9bb89b21ca5c248f58 schema:name School of Information Sciences, MAHE, Manipal, India
93 rdf:type schema:Organization
94 Nf0cc00bc66ab4d7ca57dc5a33b6ade9e schema:name School of Information Sciences, MAHE, Manipal, India
95 rdf:type schema:Organization
96 Nf48ccb00b5784bc39495866e32571fc5 rdf:first Nfc45b0c02551483697188fcb15f82aaa
97 rdf:rest N2a810360a04545ecb5fe184a87cc9be2
98 Nf690c3f079a643afa77ce34b9e3cf1fb schema:name nlm_unique_id
99 schema:value 7806056
100 rdf:type schema:PropertyValue
101 Nf70c544e98dd4a779ea77c9f1a5a4f74 schema:name Department of Electronics and Communication, NMAMIT, Nitte, Karkala, India
102 School of Information Sciences, MAHE, Manipal, India
103 rdf:type schema:Organization
104 Nfc45b0c02551483697188fcb15f82aaa schema:affiliation Nf0cc00bc66ab4d7ca57dc5a33b6ade9e
105 schema:familyName Prasad
106 schema:givenName Keerthana
107 rdf:type schema:Person
108 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
109 schema:name Information and Computing Sciences
110 rdf:type schema:DefinedTerm
111 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
112 schema:name Artificial Intelligence and Image Processing
113 rdf:type schema:DefinedTerm
114 sg:journal.1088158 schema:issn 0148-5598
115 1573-689X
116 schema:name Journal of Medical Systems
117 rdf:type schema:Periodical
118 sg:pub.10.1007/bf00133570 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016330466
119 https://doi.org/10.1007/bf00133570
120 rdf:type schema:CreativeWork
121 sg:pub.10.1007/s10916-011-9679-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047722557
122 https://doi.org/10.1007/s10916-011-9679-0
123 rdf:type schema:CreativeWork
124 sg:pub.10.1007/s10916-018-0912-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1101079169
125 https://doi.org/10.1007/s10916-018-0912-y
126 rdf:type schema:CreativeWork
127 sg:pub.10.1007/s11760-012-0393-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052271564
128 https://doi.org/10.1007/s11760-012-0393-2
129 rdf:type schema:CreativeWork
130 sg:pub.10.1007/s11760-014-0715-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014745789
131 https://doi.org/10.1007/s11760-014-0715-7
132 rdf:type schema:CreativeWork
133 sg:pub.10.1007/s12575-009-9011-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033826498
134 https://doi.org/10.1007/s12575-009-9011-2
135 rdf:type schema:CreativeWork
136 https://app.dimensions.ai/details/publication/pub.1079048010 schema:CreativeWork
137 https://app.dimensions.ai/details/publication/pub.1085764954 schema:CreativeWork
138 https://doi.org/10.1016/j.bbe.2014.10.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026629648
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/j.bbe.2017.07.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090900359
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/j.cmpb.2011.08.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026831292
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/j.compmedimag.2011.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032674117
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/j.jss.2012.04.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011343748
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1016/j.measurement.2017.11.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092637516
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1016/j.micron.2011.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038225855
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1109/access.2016.2636218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061252366
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1109/cicsyn.2015.36 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095751857
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1109/icip.2011.6115881 schema:sameAs https://app.dimensions.ai/details/publication/pub.1095282944
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1109/sibgrapi.2007.33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1094903105
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1109/titb.2005.847515 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061656377
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1142/s1793545814500072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051544363
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1155/2012/183879 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004265279
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1155/2012/574184 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003225550
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1155/2016/9514707 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007780825
169 rdf:type schema:CreativeWork
170 https://doi.org/10.3390/s140916128 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039622884
171 rdf:type schema:CreativeWork
172 https://doi.org/10.3923/jas.2010.959.966 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034395601
173 rdf:type schema:CreativeWork
174 https://doi.org/10.4103/2153-3539.109883 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043575597
175 rdf:type schema:CreativeWork
176 https://www.grid.ac/institutes/grid.465547.1 schema:alternateName Kasturba Medical College
177 schema:name Kasturba Medical College, MAHE, Manipal, India
178 rdf:type schema:Organization
 




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


...