| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
| Identifier | 8JMKD3MGPBW34M/387LT3L |
| Repository | sid.inpe.br/sibgrapi/2010/09.06.13.15 |
| Last Update | 2010:09.06.13.15.10 (UTC) administrator |
| Metadata Repository | sid.inpe.br/sibgrapi/2010/09.06.13.15.11 |
| Metadata Last Update | 2022:06.14.00.06.57 (UTC) administrator |
| DOI | 10.1109/SIBGRAPI.2010.18 |
| Citation Key | ParolinHerzJung:2010:SeDiMe |
| Title | Semi-Automated Diagnosis of Melanoma Through the Analysis of Dermatological Images  |
| Format | Printed, On-line. |
| Year | 2010 |
| Access Date | 2024, May 03 |
| Number of Files | 1 |
| Size | 256 KiB |
| 2. Context | |
| Author | 1 Parolin, Alessandro 2 Herzer, Eduardo 3 Jung, Claudio R. |
| Affiliation | 1 Unisinos 2 Unisinos 3 UFRGS |
| Editor | Bellon, Olga Esperança, Claudio |
| e-Mail Address | crjung@inf.ufrgs.br |
| Conference Name | Conference on Graphics, Patterns and Images, 23 (SIBGRAPI) |
| Conference Location | Gramado, RS, Brazil |
| Date | 30 Aug.-3 Sep. 2010 |
| Publisher | IEEE Computer Society |
| Publisher City | Los Alamitos |
| Book Title | Proceedings |
| Tertiary Type | Full Paper |
| History (UTC) | 2010-10-01 04:19:38 :: crjung@inf.ufrgs.br -> administrator :: 2010 2022-06-14 00:06:57 :: administrator -> :: 2010 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Version Type | finaldraft |
| Keywords | image processing medical imaging classification MDA-FKT |
| Abstract | Melanoma is the deadliest kind of skin cancer, but it can be 100% cured if recognized early in advance. This paper proposes a non-invasive automated skin lesion classifier based on digitized dermatological images. In the proposed approach, the lesion is initially segmented using snakes guided by an edge map based on the Wavelet Transform (WT) computed at different resolutions. A set of features is extracted from lesion pixels, and a probabilistic classifier is used to identify melanoma lesions. The detection rate of the proposed system can be adjusted to control the tradeoff between false positives and false negatives, and experimental results indicated that a false negative rate of 1.89% can be achieved, in a total accuracy rate of 82.55%. |
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2010 > Semi-Automated Diagnosis of... |
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Semi-Automated Diagnosis of... |
| 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/8JMKD3MGPBW34M/387LT3L |
| zipped data URL | http://urlib.net/zip/8JMKD3MGPBW34M/387LT3L |
| Language | en |
| Target File | sib10_dermato_camera_ready.pdf |
| User Group | crjung@inf.ufrgs.br |
| Visibility | shown |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPEW34M/46SJT6B 8JMKD3MGPEW34M/4742MCS |
| Citing Item List | sid.inpe.br/sibgrapi/2022/05.14.20.21 9 |
| 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 edition electronicmailaddress group isbn issn label lineage mark mirrorrepository 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 volume |