| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
| Identifier | 6qtX3pFwXQZG2LgkFdY/Rv77P |
| Repository | sid.inpe.br/sibgrapi@80/2007/09.19.00.20 |
| Last Update | 2007:09.19.00.20.10 (UTC) administrator |
| Metadata Repository | sid.inpe.br/sibgrapi@80/2007/09.19.00.20.11 |
| Metadata Last Update | 2022:05.18.22.21.14 (UTC) administrator |
| Citation Key | TaralloGonzFrad:2007:PrDiIm |
| Title | Processing of Digital Images of Cutaneous Ulcers Through Artificial Neural Network  |
| Format | On-line |
| Year | 2007 |
| Access Date | 2024, Oct. 04 |
| Number of Files | 1 |
| Size | 151 KiB |
| 2. Context | |
| Author | 1 Tarallo, André de Souza 2 Gonzaga, Adilson 3 Frade, Marco Andrey Cipriani |
| Affiliation | 1 USP 2 USP 3 USP |
| Editor | Gonçalves, Luiz Wu, Shin Ting |
| Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI) |
| Conference Location | Belo Horizonte, MG, Brazil |
| Date | 7-10 Oct. 2007 |
| Publisher | Sociedade Brasileira de Computação |
| Publisher City | Porto Alegre |
| Book Title | Proceedings |
| Tertiary Type | Technical Poster |
| History (UTC) | 2008-07-17 14:09:44 :: tarallo@sel.eesc.usp.br -> administrator :: 2009-08-13 20:38:37 :: administrator -> banon :: 2010-08-28 20:02:31 :: banon -> administrator :: 2022-05-18 22:21:14 :: administrator -> :: 2007 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Keywords | Leg Ulcer Computer Vision Artificial Neural Network |
| Abstract | Treatments of leg ulcers are generally make by direct manipulation for analysis of its evolution. The treatment efficiency is observed through the reduction of the size of ulcers in relation to the amount of tissues found in their beds, which are classified as granulated/slough. These results usually are obtained through analyses performed after consultation due to the time these analyses take. This work proposes a new non-invasive technique for the follow-up of treatments aimed at cutaneous ulcers. In this methodology, it was proposed that digital photos of cutaneous ulcers would be submitted to an artificial neural network, so that all surrounding the wound except for the wound itself could be extracted (skin/background), thus obtaining the ulcerated area. Computer vision techniques have been applied in order to classify the different types of tissues in the ulcer bed. The results obtained have been compared with the results obtained by Image J software. |
| Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2007 > Processing of Digital... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| data URL | http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/Rv77P |
| zipped data URL | http://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/Rv77P |
| Language | en |
| Target File | Processing of Digital Images of Cutaneous Ulcers Through Artificial Neural Network.pdf |
| User Group | tarallo@sel.eesc.usp.br administrator |
| Visibility | shown |
| 5. Allied materials | |
| Mirror Repository | sid.inpe.br/sibgrapi@80/2007/08.02.16.22 |
| Next Higher Units | 8JMKD3MGPEW34M/46SF8Q5 |
| Citing Item List | sid.inpe.br/sibgrapi/2022/05.14.00.14 27 |
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
| 6. Notes | |
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume |