Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment
The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue (RGB) wound images grabbed by normal digital came...
Saved in:
Published in | BioMed research international Vol. 2014; no. 2014; pp. 1 - 9 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Cairo, Egypt
Hindawi Puplishing Corporation
01.01.2014
Hindawi Publishing Corporation John Wiley & Sons, Inc Hindawi Limited |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue (RGB) wound images grabbed by normal digital camera were first transformed into HSI (hue, saturation, and intensity) color space and subsequently the “S” component of HSI color channels was selected as it provided higher contrast. Wound areas from 6 different types of CW were segmented from whole images using fuzzy divergence based thresholding by minimizing edge ambiguity. A set of color and textural features describing granulation, necrotic, and slough tissues in the segmented wound area were extracted using various mathematical techniques. Finally, statistical learning algorithms, namely, Bayesian classification and support vector machine (SVM), were trained and tested for wound tissue classification in different CW images. The performance of the wound area segmentation protocol was further validated by ground truth images labeled by clinical experts. It was observed that SVM with 3rd order polynomial kernel provided the highest accuracies, that is, 86.94%, 90.47%, and 75.53%, for classifying granulation, slough, and necrotic tissues, respectively. The proposed automated tissue classification technique achieved the highest overall accuracy, that is, 87.61%, with highest kappa statistic value (0.793). |
---|---|
AbstractList | The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue (RGB) wound images grabbed by normal digital camera were first transformed into HSI (hue, saturation, and intensity) color space and subsequently the "S" component of HSI color channels was selected as it provided higher contrast. Wound areas from 6 different types of CW were segmented from whole images using fuzzy divergence based thresholding by minimizing edge ambiguity. A set of color and textural features describing granulation, necrotic, and slough tissues in the segmented wound area were extracted using various mathematical techniques. Finally, statistical learning algorithms, namely, Bayesian classification and support vector machine (SVM), were trained and tested for wound tissue classification in different CW images. The performance of the wound area segmentation protocol was further validated by ground truth images labeled by clinical experts. It was observed that SVM with 3rd order polynomial kernel provided the highest accuracies, that is, 86.94%, 90.47%, and 75.53%, for classifying granulation, slough, and necrotic tissues, respectively. The proposed automated tissue classification technique achieved the highest overall accuracy, that is, 87.61%, with highest kappa statistic value (0.793). The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation using medical image processing and statistical machine learning techniques. The red-green-blue ( RGB ) wound images grabbed by normal digital camera were first transformed into HSI (hue, saturation, and intensity) color space and subsequently the “ S ” component of HSI color channels was selected as it provided higher contrast. Wound areas from 6 different types of CW were segmented from whole images using fuzzy divergence based thresholding by minimizing edge ambiguity. A set of color and textural features describing granulation, necrotic, and slough tissues in the segmented wound area were extracted using various mathematical techniques. Finally, statistical learning algorithms, namely, Bayesian classification and support vector machine (SVM), were trained and tested for wound tissue classification in different CW images. The performance of the wound area segmentation protocol was further validated by ground truth images labeled by clinical experts. It was observed that SVM with 3rd order polynomial kernel provided the highest accuracies, that is, 86.94%, 90.47%, and 75.53%, for classifying granulation, slough, and necrotic tissues, respectively. The proposed automated tissue classification technique achieved the highest overall accuracy, that is, 87.61%, with highest kappa statistic value (0.793). |
Audience | Academic |
Author | Das, Dev Kumar Achar, Arun Mukherjee, Rashmi Mitra, Analava Manohar, Dhiraj Dhane Chakraborty, Chandan |
AuthorAffiliation | 1 School of Medical Science & Technology, Indian Institute of Technology, Kharagpur, West Bengal 721302, India 2 Department of Dermatology, Midnapore Medical College Hospital, Midnapore, West Bengal 721101, India |
AuthorAffiliation_xml | – name: 2 Department of Dermatology, Midnapore Medical College Hospital, Midnapore, West Bengal 721101, India – name: 1 School of Medical Science & Technology, Indian Institute of Technology, Kharagpur, West Bengal 721302, India |
Author_xml | – sequence: 1 fullname: Manohar, Dhiraj Dhane – sequence: 2 fullname: Mukherjee, Rashmi – sequence: 3 fullname: Das, Dev Kumar – sequence: 4 fullname: Achar, Arun – sequence: 5 fullname: Mitra, Analava – sequence: 6 fullname: Chakraborty, Chandan |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25114925$$D View this record in MEDLINE/PubMed |
BookMark | eNqN0s9rFDEUB_AgFfvDnjwrA15EWZuXXzNzEZbFqlAQtOIxZJM33dSZZJvMWPrfm2Xq-uOiuSSQD9_kJe-YHIQYkJAnQF8DSHnGKIizRoJs2ANyxDiIhQIBB_s154fkNOdrWkYDirbqETlkEkC0TB6Rz8tpjIMZ0VWXPucJq1Vvcvadt2b0MVTnyQx4G9O3qoup-oTbFN1k_bovcpNi8Lb6GqfgqmXOmPOAYXxMHnamz3h6P5-QL-dvL1fvFxcf331YLS8WVrJ6XDDV8ZYBk05xdJ0TslHK1lAboEwybK3DVjaWlzprdGvRYQONKW7N10IYfkLezLnbaT2gs-XoZHq9TX4w6U5H4_WfO8Fv9FX8rgUwoNCUgBf3ASneTJhHPfhsse9NwDhlDQpAccHa_6BScqBKNFDo87_odZxSKC-xU6yBtpbtL3VletQ-dLFc0e5C9VKwmjJR07qoV7OyKeacsNtXB1TvGkDvGkDPDVD0s98fZG9_fncBL2ew8cGZW_-PtKczxkKwM3ssKeeM8x8eA8F9 |
CitedBy_id | crossref_primary_10_1080_13682199_2019_1663083 crossref_primary_10_1109_ACCESS_2019_2925689 crossref_primary_10_1109_ACCESS_2022_3194529 crossref_primary_10_1007_s00521_022_07274_6 crossref_primary_10_1007_s42600_022_00213_3 crossref_primary_10_1089_wound_2021_0091 crossref_primary_10_2196_diabetes_8316 crossref_primary_10_1049_iet_ipr_2018_5899 crossref_primary_10_1016_j_cmpb_2019_105079 crossref_primary_10_3389_fmed_2020_00100 crossref_primary_10_1007_s10916_016_0554_x crossref_primary_10_1007_s11042_020_08768_y crossref_primary_10_1109_TBME_2016_2632522 crossref_primary_10_1097_GOX_0000000000003638 crossref_primary_10_1080_1206212X_2017_1395108 crossref_primary_10_1111_jmi_12595 crossref_primary_10_1364_JOSAA_394985 crossref_primary_10_1007_s11042_022_12555_2 crossref_primary_10_1007_s11517_014_1240_0 crossref_primary_10_1109_ACCESS_2020_3035327 crossref_primary_10_3390_app10217613 crossref_primary_10_1016_j_burns_2021_07_007 crossref_primary_10_1093_jamia_ocab113 crossref_primary_10_1089_sur_2019_154 crossref_primary_10_1093_jbcr_irz103 crossref_primary_10_3390_biomedicines11092457 crossref_primary_10_1111_iwj_13011 crossref_primary_10_1109_ACCESS_2020_3014175 crossref_primary_10_2196_52880 crossref_primary_10_52198_21_STI_38_WH1450 crossref_primary_10_3389_fmed_2023_1278232 crossref_primary_10_1089_wound_2019_0967 crossref_primary_10_1089_wound_2021_0144 crossref_primary_10_1016_j_enfcli_2019_10_021 crossref_primary_10_1109_ACCESS_2019_2959027 crossref_primary_10_25259_IJDVL_518_19 crossref_primary_10_1016_j_compbiomed_2017_04_004 crossref_primary_10_1097_PRS_0000000000002654 crossref_primary_10_1007_s10916_015_0424_y crossref_primary_10_25259_JSSTD_49_2020 crossref_primary_10_1155_2018_4149103 crossref_primary_10_1016_j_artmed_2019_101742 |
Cites_doi | 10.1023/B:VISI.0000046591.79973.6f 10.1007/11559573_123 10.1109/EMB.2007.901786 10.1016/j.burns.2004.11.019 10.12968/jowc.2004.13.8.26657 10.1109/42.896789 10.1117/1.3378149 10.1117/1.1557159 10.1109/42.897812 10.1111/j.1524-475X.2009.00543.x 10.1016/S0167-8655(03)00007-2 10.1016/j.micron.2010.04.017 10.1177/001316446002000104 |
ContentType | Journal Article |
Contributor | Das, Dev Kumar Achar, Arun Mukherjee, Rashmi Mitra, Analava Manohar, Dhiraj Dhane Chakraborty, Chandan |
Contributor_xml | – sequence: 1 fullname: Manohar, Dhiraj Dhane – sequence: 2 fullname: Mukherjee, Rashmi – sequence: 3 fullname: Das, Dev Kumar – sequence: 4 fullname: Achar, Arun – sequence: 5 fullname: Mitra, Analava – sequence: 6 fullname: Chakraborty, Chandan |
Copyright | Copyright © 2014 Rashmi Mukherjee et al. COPYRIGHT 2014 John Wiley & Sons, Inc. Copyright © 2014 Rashmi Mukherjee et al. Rashmi Mukherjee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright © 2014 Rashmi Mukherjee et al. 2014 |
Copyright_xml | – notice: Copyright © 2014 Rashmi Mukherjee et al. – notice: COPYRIGHT 2014 John Wiley & Sons, Inc. – notice: Copyright © 2014 Rashmi Mukherjee et al. Rashmi Mukherjee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. – notice: Copyright © 2014 Rashmi Mukherjee et al. 2014 |
DBID | ADJCN RHU RHW RHX CGR CUY CVF ECM EIF NPM AAYXX CITATION 3V. 7QL 7QO 7T7 7TK 7U7 7U9 7X7 7XB 88E 8FD 8FE 8FG 8FH 8FI 8FJ 8FK ABUWG AFKRA ARAPS AZQEC BBNVY BENPR BGLVJ BHPHI C1K CCPQU CWDGH DWQXO FR3 FYUFA GHDGH GNUQQ H94 HCIFZ K9. LK8 M0S M1P M7N M7P P5Z P62 P64 PIMPY PQEST PQQKQ PQUKI PRINS 7X8 5PM |
DOI | 10.1155/2014/851582 |
DatabaseName | الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals Hindawi Publishing Complete Hindawi Publishing Subscription Journals Hindawi Publishing Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed CrossRef ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Biotechnology Research Abstracts Industrial and Applied Microbiology Abstracts (Microbiology A) Neurosciences Abstracts Toxicology Abstracts Virology and AIDS Abstracts ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Technology Research Database ProQuest SciTech Collection ProQuest Technology Collection ProQuest Natural Science Collection Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central Advanced Technologies & Aerospace Collection ProQuest Central Essentials Biological Science Collection AUTh Library subscriptions: ProQuest Central Technology Collection ProQuest Natural Science Collection Environmental Sciences and Pollution Management ProQuest One Community College Middle East & Africa Database ProQuest Central Korea Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student AIDS and Cancer Research Abstracts SciTech Premium Collection (Proquest) (PQ_SDU_P3) ProQuest Health & Medical Complete (Alumni) Biological Sciences Health & Medical Collection (Alumni Edition) PML(ProQuest Medical Library) Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database ProQuest Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection Biotechnology and BioEngineering Abstracts Publicly Available Content Database ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) CrossRef Publicly Available Content Database ProQuest Central Student Technology Collection Technology Research Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Natural Science Collection ProQuest Central China Environmental Sciences and Pollution Management ProQuest Central Health Research Premium Collection Middle East & Africa Database Biotechnology Research Abstracts Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Collection AIDS and Cancer Research Abstracts Industrial and Applied Microbiology Abstracts (Microbiology A) ProQuest Medical Library (Alumni) Advanced Technologies & Aerospace Collection Virology and AIDS Abstracts ProQuest Biological Science Collection Toxicology Abstracts ProQuest One Academic Eastern Edition ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Advanced Technologies & Aerospace Database ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition Engineering Research Database ProQuest One Academic ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | MEDLINE CrossRef Engineering Research Database Publicly Available Content Database |
Database_xml | – sequence: 1 dbid: RHX name: Hindawi Publishing (Open access) url: http://www.hindawi.com/journals/ sourceTypes: Publisher – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 4 dbid: 8FG name: ProQuest Technology Collection url: https://search.proquest.com/technologycollection1 sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 2314-6141 |
Editor | Cohn, Stephen M. |
Editor_xml | – sequence: 1 givenname: Stephen M. surname: Cohn fullname: Cohn, Stephen M. |
EndPage | 9 |
ExternalDocumentID | 3400520881 A427024707 10_1155_2014_851582 25114925 503323 |
Genre | Research Support, Non-U.S. Gov't Journal Article |
GeographicLocations | India |
GeographicLocations_xml | – name: India |
GroupedDBID | 04C 24P 3V. 4.4 53G 5VS 7X7 88E 8FE 8FG 8FH 8FI 8FJ AAFWJ AAJEY AAWTL ABDBF ABUWG ACIWK ACPRK ADBBV ADJCN ADOJX ADRAZ AENEX AFKRA AFRAH AHMBA ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS ARAPS BAWUL BBNVY BCNDV BENPR BGLVJ BHPHI BMSDO BPHCQ BVXVI CCPQU CWDGH DIK EAD EAP EAS EBD EBS ECF ECT EIHBH EJD EMB EMK EMOBN ESX FYUFA GROUPED_DOAJ H13 HCIFZ HMCUK HYE IAG IAO IEA IHR INH INR IOF ISR ITC KQ8 LK8 M1P M48 M7P ML0 ML~ OK1 P62 PGMZT PIMPY PQQKQ PROAC PSQYO RHX RPM SV3 TUS UKHRP RHU RHW CGR CUY CVF ECM EIF NPM AAYXX CITATION 7QL 7QO 7T7 7TK 7U7 7U9 7XB 8FD 8FK AZQEC C1K DWQXO FR3 GNUQQ H94 K9. M7N P64 PQEST PQUKI PRINS 7X8 5PM |
ID | FETCH-LOGICAL-c527t-26f392125d63edfd45866c717a10252e9cde958c31557edb4fe818ad45b3b44a3 |
IEDL.DBID | RPM |
ISSN | 2314-6133 |
IngestDate | Tue Sep 17 21:25:56 EDT 2024 Fri Aug 16 01:04:34 EDT 2024 Fri Aug 16 01:45:52 EDT 2024 Thu Oct 10 22:12:25 EDT 2024 Wed Oct 16 18:05:47 EDT 2024 Thu Sep 26 19:12:48 EDT 2024 Sat Sep 28 08:06:12 EDT 2024 Sun Jun 02 18:54:26 EDT 2024 Thu Sep 12 21:31:01 EDT 2024 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 2014 |
Language | English |
License | This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c527t-26f392125d63edfd45866c717a10252e9cde958c31557edb4fe818ad45b3b44a3 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Academic Editor: Stephen M. Cohn |
OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121018/ |
PMID | 25114925 |
PQID | 1552819759 |
PQPubID | 237798 |
PageCount | 9 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_4121018 proquest_miscellaneous_1611634298 proquest_miscellaneous_1553106481 proquest_journals_1552819759 gale_infotracmisc_A427024707 crossref_primary_10_1155_2014_851582 pubmed_primary_25114925 hindawi_primary_10_1155_2014_851582 emarefa_primary_503323 |
PublicationCentury | 2000 |
PublicationDate | 2014-01-01 |
PublicationDateYYYYMMDD | 2014-01-01 |
PublicationDate_xml | – month: 01 year: 2014 text: 2014-01-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | Cairo, Egypt |
PublicationPlace_xml | – name: Cairo, Egypt – name: United States – name: New York |
PublicationTitle | BioMed research international |
PublicationTitleAlternate | Biomed Res Int |
PublicationYear | 2014 |
Publisher | Hindawi Puplishing Corporation Hindawi Publishing Corporation John Wiley & Sons, Inc Hindawi Limited |
Publisher_xml | – name: Hindawi Puplishing Corporation – name: Hindawi Publishing Corporation – name: John Wiley & Sons, Inc – name: Hindawi Limited |
References | (27) 1960; 20 (28) 2010; 19 Wannous H. Treuillet S. Lucas Y. Supervised tissue classification from color images for a complete wound assessment tool Proceedings of the 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society (EMBC '07) August 2007 6031 6034 10.1109/IEMBS.2007.4353723 2-s2.0-57649238027 Sussman C. Bates-Jensen B. M. Wound Care: A Collaborative Practice Manual 2007 3rd Lippincott Williams & Wilkins (6) 2000; 19 Perez A. A. Gonzaga A. Alves J. M. Segmentation and analysis of leg ulcers color images Proceedings of International Workshop on Medical Imaging and Augmented Reality 2001 262 266 10.1109/MIAR.2001.930300 Zar J. H. Biostatistical Analysis 2010 5th New York, NY, USA Prentice Hall Cutting K. Tong A. Wound Physiology and Moist Wound Healing 2003 Holsworthy, UK Medical Communications Ltd (2) 2009; 17 (14) 2005; 31 (7) 2003; 12 Nayak R. Kumar P. Galigekere R. R. Towards a comprehensive assessment of wound-composition using color-image processing Proceedings of the IEEE International Conference on Image Processing (ICIP '09) November 2009 4185 4188 10.1109/ICIP.2009.5414527 2-s2.0-77951947828 (3) 2004; 13 (13) 2007; 26 Galushka M. Zheng H. Patterson D. Bradley L. Case-based tissue classification for monitoring leg ulcer healing Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems June 2005 353 358 2-s2.0-27544513008 10.1109/CBMS.2005.39 (20) 2008 Cover T. M. Thomas J. A. Elements of Information Theory 1991 Wiley-Interscience Willey Series in Telecommunication Han J. Kamber M. Data Mining: Concepts and Techniques 2006 2nd Morgan Kaufmann Dorileo É. A. G. Frade M. A. C. Rangayyan R. M. Azevedo-Marques P. M. Segmentation and analysis of the tissue composition of dermatological ulcers Proceedings of the 23rd Canadian Conference on Electrical and Computer Engineering (CCECE '10) May 2010 Calgary, Canada 2 5 10.1109/CCECE.2010.5575143 2-s2.0-78049322885 Thomas S. Rovee D. T. Maibach H. I. Wound dressings The Epidermis in Wound Healing 2004 Boca Raton, Fla, USA CRC Press (22) 2010; 41 (4) 2002; 14 (8) 2000; 19 Kolesnik M. Fexa A. Multi-dimensional color histograms for segmentation of wounds in images Image Analysis and Recognition 2005 3656 1014 1022 Lecture Notes in Computer Science 10.1007/11559573_123 (21) 2003; 24 Gonzalez R. C. Woods R. E. Digital Image Processing 2002 2nd New York, NY, USA Prentice Hall (9) 2005; 62 Webb A. R. Statistical Pattern Recognition 2002 2nd John Wiley & Sons 18003389 - Conf Proc IEEE Eng Med Biol Soc. 2007;2007:6032-5 15774281 - Burns. 2005 May;31(3):275-81 11212368 - IEEE Trans Med Imaging. 2000 Dec;19(12):1202-10 20554209 - Micron. 2010 Oct;41(7):840-6 19903300 - Wound Repair Regen. 2009 Nov-Dec;17(6):763-71 15469216 - J Wound Care. 2004 Sep;13(8):323-5 17941318 - IEEE Eng Med Biol Mag. 2007 Sep-Oct;26(5):18-22 11204850 - IEEE Trans Med Imaging. 2000 Nov;19(11):1128-43 13 14 (24) 2006 26 (23) 2010 19 (22) 2002 (1) 2003 (28) 2007 (21) 1991 (25) 1960; 20 2 3 (18) 2008 5 (27) 2004 6 7 (17) 2002 8 9 20 |
References_xml | – volume: 17 start-page: 763 issue: 6 year: 2009 end-page: 771 ident: 2 article-title: Human skin wounds: a major and snowballing threat to public health and the economy publication-title: – volume: 62 start-page: 97 issue: 1-2 year: 2005 end-page: 119 ident: 9 article-title: Skin texture modeling publication-title: – volume: 14 start-page: 58 issue: 2 year: 2002 end-page: 66 ident: 4 article-title: Technological advances in wound bed measurements publication-title: – volume: 19 start-page: 1128 issue: 11 year: 2000 end-page: 1143 ident: 8 article-title: Border detection on digitized skin tumor images publication-title: – volume: 20 start-page: 37 year: 1960 end-page: 46 ident: 27 article-title: A coefficient of agreement for nominal scales publication-title: – volume: 41 start-page: 840 issue: 7 year: 2010 end-page: 846 ident: 22 article-title: Automated leukocyte recognition using fuzzy divergence publication-title: – volume: 13 start-page: 323 issue: 8 year: 2004 end-page: 325 ident: 3 article-title: An Indian community-based epidemiological study of wounds publication-title: – start-page: 212 year: 2008 end-page: 216 ident: 20 article-title: Watershed segmentation of cervical images using multiscale morpholigcal gradient and HSI color space publication-title: – volume: 31 start-page: 275 issue: 3 year: 2005 end-page: 281 ident: 14 article-title: A computer assisted diagnosis tool for the classification of burns by depth of injury publication-title: – volume: 24 start-page: 1837 issue: 12 year: 2003 end-page: 1844 ident: 21 article-title: Segmentation using fuzzy divergence publication-title: – volume: 26 start-page: 18 issue: 5 year: 2007 end-page: 22 ident: 13 article-title: Automated pressure ulcer lesion diagnosis for telemedicine systems publication-title: – volume: 12 start-page: 317 issue: 2 year: 2003 end-page: 326 ident: 7 article-title: Improved active contour models with application to measurement of leg ulcers publication-title: – volume: 19 start-page: 1202 issue: 12 year: 2000 end-page: 1210 ident: 6 article-title: An active contour model for measuring the area of leg ulcers publication-title: – volume: 19 issue: 2 year: 2010 ident: 28 article-title: Robust tissue classification for reproducible wound assessment in telemedicine environments publication-title: – ident: 9 doi: 10.1023/B:VISI.0000046591.79973.6f – ident: 5 doi: 10.1007/11559573_123 – ident: 13 doi: 10.1109/EMB.2007.901786 – ident: 14 doi: 10.1016/j.burns.2004.11.019 – ident: 3 doi: 10.12968/jowc.2004.13.8.26657 – year: 1991 ident: 21 – year: 2002 ident: 22 – ident: 8 doi: 10.1109/42.896789 – year: 2010 ident: 23 – ident: 26 doi: 10.1117/1.3378149 – year: 2006 ident: 24 – start-page: 212 year: 2008 ident: 18 publication-title: International Journal of Imaging Science and Engineering – year: 2003 ident: 1 – ident: 7 doi: 10.1117/1.1557159 – volume-title: Wound dressings year: 2004 ident: 27 – year: 2007 ident: 28 – year: 2002 ident: 17 – ident: 6 doi: 10.1109/42.897812 – ident: 2 doi: 10.1111/j.1524-475X.2009.00543.x – ident: 19 doi: 10.1016/S0167-8655(03)00007-2 – volume: 14 start-page: 58 issue: 2 year: 2002 ident: 4 publication-title: Wounds – ident: 20 doi: 10.1016/j.micron.2010.04.017 – volume: 20 start-page: 37 year: 1960 ident: 25 publication-title: Educational and Psychological Measurement doi: 10.1177/001316446002000104 |
SSID | ssj0000816096 |
Score | 2.4224274 |
Snippet | The aim of this paper was to develop a computer assisted tissue classification (granulation, necrotic, and slough) scheme for chronic wound (CW) evaluation... |
SourceID | pubmedcentral proquest gale crossref pubmed hindawi emarefa |
SourceType | Open Access Repository Aggregation Database Index Database Publisher |
StartPage | 1 |
SubjectTerms | Accuracy Algorithms Automation Bayes Theorem Burns Chronic Disease Classification Computer-aided design Diabetes Diabetic Foot Digital cameras Evaluation Humans Image Processing, Computer-Assisted - methods Innovations Methods Photography Pressure ulcers Studies Support Vector Machine Tissue engineering Wound healing Wounds and Injuries - classification Wounds and Injuries - pathology |
SummonAdditionalLinks | – databaseName: Hindawi Publishing dbid: RHX link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1Na9tAEB3agEMvIW3zocQNW5qriKT91NGEGBNID61DfRO7qxUxJHKpbfL3MyPJok5CyE1CIyG93dW82Z19A3Ce-FCZirvYKSph5nmJRzyNObciy9IKgy6aGrj5qSa34nomZ12C7PLlEj56OwzPU3GBxEAa_NV-NIYU8n9NZv1MCpWOSPK2ilwqMBbivNuI9-zuLdczCA8WD2z_Kx7cURD8OH-Naj7PmPzPBY33Ya_jjmzUNvZn-BDqL7B7062Of4Xfo_VqgQw0lGza4MmakpeUDNTgz8abTCyGVJUh927kXufuHi1bkVz2h8ossVGv13kAt-Or6eUk7oomxF5mehVnqkLKg7SlVDyUVSmkUcpj0GaRSsgs5L4MuTSeIzg6lE5UAX22RTvHnRCWH8JOvajDMbDEq8QZL6TXSgStrHRJ7o3VmfW5qUQE5xs8i7-tNkbRxBRSFgR70cIewWGHdW9Fa6cZj2BI0Bc0lBBVjx3bFyNBO-SETnQEP7omefvpw01zFd3wWxakK4dUR8s8gu_9ZXo-pZTVYbFubJDaKmHSN2xUinwVXbaJ4KjtAf27UGxGyo4R6K2-0RuQcPf2lXp-1wh4C1JtS83Juz7wFD7RWTvtM4Sd1b91-IZEaOXOmnHwBJbS_p4 priority: 102 providerName: Hindawi Publishing – databaseName: ProQuest Technology Collection dbid: 8FG link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3fb9QwDLZgaIgXxIBB2TEFsddqbfOzT9Np4piQxgub2FuVpKl20ugNdqf9-7PTXMchdG-VakWt48SfHeczwFHhQ2c67nKnqIWZ5y0-8TLn3IqqKjsMuig1cP5dnV2Kb1fyKiXc7lJZ5XpPjBt1u_CUIz8mqjD0XlrWJ7e_c-oaRaerqYXGU3hWEhMe3RSffR1zLNRUoqiH_nKlwCiJ83RFD0fDsL8Uxwg4pKk2nNJu-GXxwY6b9O41hcf38_-B0H9rKf9yTrNX8DKhSjYdzGAPnoT-NTw_T-fmb-DHdLVcIDYNLbuImmaxGSaVCcWZYbN1jRZDEMsQlUci2Lm7QcmBPpf9pAZMbDoyeb6Fy9mXi9OzPLVTyL2s9DKvVIdgCAFNq3hou1ZIo5THcM4iyJBVqH0bamk8R-Xo0DrRBfTmFuUcd0JYvg87_aIP74EVXhXOeCG9ViJoZaUram-srqyvTScyOFrrs7kdWDOaGG1I2ZDam0HtGewnXY9SdKpa8QwmpPqGFhlq1aPJ-2Yq6O6c0IXO4HOaku2jT9bT1aSFedc8mlEGn8bXND4Vm_VhsYoyCHqVMOUWGVUikkVnbjJ4N1jA-C0UtRHnYwZ6wzZGAaL03nzTz68jtbcgPrfSfNj-6Qfwgv5zyARNYGf5ZxU-IjZausO4AB4A78YJYw priority: 102 providerName: ProQuest – databaseName: Scholars Portal Journals: Open Access dbid: M48 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3daxQxEB9KpeJLqR_VtadE7Ovq7uZzH6Qc4lGE88Ue9m1Jsll60O5pvaP63zuT_aBXSh98C2QSwswk-U0-fgNwnPnQmIa71ClKYeZ5jSWep5xbURR5g0EXHQ3Mv6nThfh6Ls93YEjG2Svw972hHeWTWlxffvjz6-8JTvhPccJLifF7Lj4icpAG1-JHheCCXH3e4_y4JJsch9IlmssFhkuc93_17rQnbmCEIMTYt7VR7YUriwU7Ltx7FxQy3yzvA6Z331fe2rBmB7DfI0027VzjKeyE9hk8nvd36c_h-3SzXiFeDTU7i9pnMUEmPR2K1mKz4d0WQ2DLEKlHctilu0TJjlKX_aCkTGw6snu-gMXsy9nn07RPsZB6Weh1WqgGARKCnFrxUDe1kEYpjyGeReAhi1D6OpTSeI560qF2ogm4w1uUc9wJYfkh7LarNrwClnmVOeOF9FqJoJWVLiu9sbqwvjSNSOB40Gf1s2PSqGIEImVFFqg6CyRw2Ot6lKKb1oInMCHVV-QKqFWP08BXU0H_6YTOdALve5M83PtkMFc1-FpFLHQIjLQsE3g3VlP_9ACtDatNlEEgrITJH5BROaJb3OBNAi87DxjHMnhVAnrLN0YBovnermmXF5HuWxDHW25e_3fLI3hCKugOjiawu77ehDcIpdbubZwm_wDo7Rgg priority: 102 providerName: Scholars Portal |
Title | Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment |
URI | https://search.emarefa.net/detail/BIM-503323 https://dx.doi.org/10.1155/2014/851582 https://www.ncbi.nlm.nih.gov/pubmed/25114925 https://www.proquest.com/docview/1552819759 https://search.proquest.com/docview/1553106481 https://search.proquest.com/docview/1611634298 https://pubmed.ncbi.nlm.nih.gov/PMC4121018 |
Volume | 2014 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9tAEB4BFRWXqi9a0zRyVa4mtvfpY4pIo0pBiIKam-Vdr0Uk4iBIxN9nZv0QqSoOvVi2dvzQzKznG3v2G4Dj2LpKV8xERlILM8tK3GNJxFjB0zSpMOmiTwOzczm95r_mYr4DolsL44v2rVmc1LfLk3px42sr75Z21NWJjS5mp5xYrxI92oVdxdizFN2_fnWCt22ayiUcUyPG2nV5GDox10_4CFGG0NTHhvA1sfNtBaV9tyxwp-hf0vs3lB4_Lv4FQv-upXwWnCZv4U2LKsNx8_TvYMfV7-H1rP1v_gF-jzfrFWJTV4ZXXtOhb4ZJZULeMuGkq9EKEcSGiMo9EezC3KJkQ58b_qEGTOG4Z_L8CNeTs6vTadS2U4isSNU6SmWFYAgBTSmZK6uSCy2lxXSuQJAhUpfZ0mVCW4Z6Uq40vHIYzQuUM8xwXrBD2KtXtfsMYWxlbLTlwirJnZKFMHFmdaHSwma64gEcd_rM7xrWjNxnG0LkZIG8sUAAh62ueyn6q5qyAAak-pwmGWrVosvbfMxp7RxXsQrge2uSl68-6MyVtxPzISfGOQRBSmQBfOuH6fpUbFa71cbLIOiVXCcvyMgEkSwGcx3Ap8YD-mfpvCoAteUbvQBRem-PoKd7au_Ws4_--8wvcEAqaD4SDWBvfb9xXxE2rc0QJ8tc4VZPfg7h1Y-z84tLPJpxjdvL6Xzop9ETxxkXeA |
link.rule.ids | 230,315,733,786,790,869,884,891,2236,12083,12792,21416,24346,27955,27956,31752,31753,33406,33407,33777,33778,43343,43633,43838,53825,53827,74100,74390,74657 |
linkProvider | National Library of Medicine |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3db9MwED9BpwEvE1-DsAJG7DVaEn_mCXVoVYG1QtCJvUWO42iVIB2sFf8-d4kbVoT6FiknKzmffb87n38HcJw4X5ual3GpqIWZ4xU-8TTm3IosS2sMuig1MJ2pyYX4eCkvQ8LtJpRVbvbEdqOulo5y5CdEFYbeS8v83fXPmLpG0elqaKFxF_aIctMMYO_0bPb5S59lobYSSd51mEsFxkmch0t6OB4G_qk4QcghTbbllvb9D4sPtt-m968oQP69-B8M_bea8pZ7Gj-Eg4Ar2agzhEdwxzeP4d40nJw_ga-j9WqJ6NRXbN7qmrXtMKlQqJ0bNt5UaTGEsQxxeUsFuyi_o2RHoMu-UQsmNuq5PJ_Cxfhs_n4Sh4YKsZOZXsWZqhEOIaSpFPdVXQlplHIY0FmEGTLzuat8Lo3jqBztq1LUHv25RbmSl0JYfgiDZtn458ASp5LSOCGdVsJrZWWZ5M5YnVmXm1pEcLzRZ3Hd8WYUbbwhZUFqLzq1R3AYdN1L0blqxiMYkuoLWmaoVYdG74qRoNtzQic6grdhSnaPPtxMVxGW5k3x15AieNO_pvGp3Kzxy3Urg7BXCZPukFEpYll05yaCZ50F9N9CcRuxPkagt2yjFyBS7-03zeKqJfcWxOiWmhe7P_013J_Mp-fF-YfZpyN4QP_c5YWGMFj9WvuXiJRW5auwHP4AHUENug |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV3db9MwED_B0Ka9THyNZRQIYq9Rk_gzT6gCqvGxCYlN9C2yHUerxNKNteLf585xA0Wob5F8spzz2fc7-3w_gJPc-Va3zGZWEoWZYw1-sSJjzPCyLFoMuuho4Oxcnl7yTzMxi_lPdzGtcr0nho26WTg6Ix9TqTD0XkpU4zamRXx9P317c5sRgxTdtEY6jfvwAL1kTjQOaqaG8xYimMirnmuu4BgxMRaf62HPY3SDfIzgQ-hyw0Ht-muDH2bYsHevKFT-Nf8fIP03r_IvRzV9CAcRYaaT3iQewT3fPYa9s3iH_gS-TVbLBeJU36QXQetpIMaklKEwS-l0na-VIqBNEaGHorBz-wMl-1K66XciY0onQ1XPp3A5_XDx7jSL1AqZE6VaZqVsERghuGkk803bcKGldBjaGQQcovSVa3wltGOoHOUby1uPnt2gnGWWc8MOYadbdP4I0tzJ3GrHhVOSeyWNsHnltFGlcZVueQIna33WN30FjTpEHkLUpPa6V3sCh1HXgxTdsJYsgRGpvqYFh1p1aP6unnB6R8dVrhJ4E6dke--j9XTVcZHe1X9MKoHXQzP1T4lnnV-sggwCYMl1sUVGFohq0bHrBJ71FjCMhSI4qv-YgNqwjUGAyntvtnTzq1Dmm1Ntt0Ifbx_6K9jDdVB_-Xj--Tns0y_3B0Qj2Fn-XPkXCJmW9mVYC78BM9oQdw |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Automated+Tissue+Classification+Framework+for+Reproducible+Chronic+Wound+Assessment&rft.jtitle=BioMed+research+international&rft.au=Mukherjee%2C+Rashmi&rft.au=Manohar%2C+Dhiraj+Dhane&rft.au=Das%2C+Dev+Kumar&rft.au=Achar%2C+Arun&rft.date=2014-01-01&rft.pub=Hindawi+Publishing+Corporation&rft.issn=2314-6133&rft.eissn=2314-6141&rft.volume=2014&rft_id=info:doi/10.1155%2F2014%2F851582&rft_id=info%3Apmid%2F25114925&rft.externalDBID=PMC4121018 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2314-6133&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2314-6133&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2314-6133&client=summon |