| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
| Identifier | 6qtX3pFwXQZeBBx/wiMNk |
| Repository | sid.inpe.br/banon/2002/11.29.10.53 |
| Last Update | 2002:11.14.02.00.00 (UTC) administrator |
| Metadata Repository | sid.inpe.br/banon/2002/11.29.10.53.37 |
| Metadata Last Update | 2022:06.14.00.12.19 (UTC) administrator |
| DOI | 10.1109/SIBGRAPI.2001.963040 |
| Citation Key | FerreiraBorg:2001:AuMaCl |
| Title | Automated mammogram classification using a multiresolution pattern recognition approach  |
| Year | 2001 |
| Access Date | 2024, May 01 |
| Number of Files | 1 |
| Size | 1262 KiB |
| 2. Context | |
| Author | 1 Ferreira, Cristiane Bastos Rocha 2 Borges, Dibio Leandro |
| Editor | Borges, Leandro Díbio Wu, Shin-Ting |
| Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 14 (SIBGRAPI) |
| Conference Location | Florianópolis, SC, Brazil |
| Date | 15-18 Oct. 2001 |
| Publisher | IEEE Computer Society |
| Publisher City | Los Alamitos |
| Pages | 76-83 |
| Book Title | Proceedings |
| Tertiary Type | Full Paper |
| Organization | SBC - Brazilian Computer Society |
| History (UTC) | 2008-07-17 14:10:52 :: administrator -> banon :: 2008-08-26 15:22:02 :: banon -> administrator :: 2009-08-13 20:37:07 :: administrator -> banon :: 2010-08-28 20:00:12 :: banon -> administrator :: 2022-06-14 00:12:19 :: administrator -> :: 2001 |
| 3. Content and structure | |
| Is the master or a copy? | is the master |
| Content Stage | completed |
| Transferable | 1 |
| Version Type | finaldraft |
| Keywords | automated mammogram classification multiresolution pattern recognition |
| Abstract | In order to fully achieve automated mammogram analysis one has to tackle two problems: classification of radial, circumscribed, microcalcifications, and normal samples; and classification of benign, malign, and normal ones. How to extract and select the best features from the images for classification is a very difficult task, since all of those classes are basically irregular textures with a wide visual variety inside each class. In this paper we propose a multiresolution pattern recognition approach for this problem, by transforming the data of the images in a wavelet basis, and then using special sets of the coefficients as the features tailored towards separating each of those classes. For the experiments we have used samples of images labeled by physicians. Results shown are very promising, and the paper describes possible lines for future directions. |
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2001 > Automated mammogram classification... |
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Automated mammogram classification... |
| 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/6qtX3pFwXQZeBBx/wiMNk |
| zipped data URL | http://urlib.net/zip/6qtX3pFwXQZeBBx/wiMNk |
| Language | en |
| Target File | 76-83.pdf |
| User Group | administrator |
| Visibility | shown |
| 5. Allied materials | |
| Next Higher Units | 8JMKD3MGPEW34M/46Q6TJ5 8JMKD3MGPEW34M/4742MCS |
| Citing Item List | sid.inpe.br/sibgrapi/2022/04.29.19.35 9 |
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
| 6. Notes | |
| Notes | The conference was held in Florianópolis, SC, Brazil, from October 15 to 18. |
| Empty Fields | affiliation archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition electronicmailaddress format group isbn issn label lineage mark mirrorrepository nextedition numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume |