| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | sibgrapi.sid.inpe.br | |||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | |||
| Identifier | 8JMKD3MGPAW/3RNF7US | |||
| Repository | sid.inpe.br/sibgrapi/2018/08.29.19.07 | |||
| Last Update | 2018:08.29.19.07.29 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/sibgrapi/2018/08.29.19.07.29 | |||
| Metadata Last Update | 2022:06.14.00.09.11 (UTC) administrator | |||
| DOI | 10.1109/SIBGRAPI.2018.00058 | |||
| Citation Key | JaderFonRuiPitOli:2018:DeInSe | |||
| Title | Deep instance segmentation of teeth in panoramic X-ray images  | |||
| Format | On-line | |||
| Year | 2018 | |||
| Access Date | 2025, May 09 | |||
| Number of Files | 1 | |||
| Size | 1860 KiB | |||
| 2. Context | ||||
| Author | 1 Jader, Gil 2 Fontinele, Jefferson 3 Ruiz, Marco 4 Pithon, Matheus 5 Oliveira, Luciano | |||
| Affiliation | 1 UFBA 2 UFBA 3 UFBA 4 UESC 5 UFBA | |||
| Editor | Ross, Arun Gastal, Eduardo S. L. Jorge, Joaquim A. Queiroz, Ricardo L. de Minetto, Rodrigo Sarkar, Sudeep Papa, João Paulo Oliveira, Manuel M. Arbeláez, Pablo Mery, Domingo Oliveira, Maria Cristina Ferreira de Spina, Thiago Vallin Mendes, Caroline Mazetto Costa, Henrique Sérgio Gutierrez Mejail, Marta Estela Geus, Klaus de Scheer, Sergio | |||
| e-Mail Address | lrebouca@ufba.br | |||
| Conference Name | Conference on Graphics, Patterns and Images, 31 (SIBGRAPI) | |||
| Conference Location | Foz do Iguaçu, PR, Brazil | |||
| Date | 29 Oct.-1 Nov. 2018 | |||
| Publisher | IEEE Computer Society | |||
| Publisher City | Los Alamitos | |||
| Book Title | Proceedings | |||
| Tertiary Type | Full Paper | |||
| History (UTC) | 2018-08-29 19:07:29 :: lrebouca@ufba.br -> administrator :: 2022-06-14 00:09:11 :: administrator -> :: 2018 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Version Type | finaldraft | |||
| Keywords | instance segmentation tooth segmentation panoramic X-ray image | |||
| Abstract | In dentistry, radiological examinations help specialists by showing structure of the tooth bones with the goal of screening embedded teeth, bone abnormalities, cysts, tumors, infections, fractures, problems in the temporomandibular regions, just to cite a few. Sometimes, relying solely in the specialist's opinion can bring differences in the diagnoses, which can ultimately hinder the treatment. Although tools for complete automatic diagnosis are no yet expected, image pattern recognition has evolved towards decision support, mainly starting with the detection of teeth and their components in X-ray images. Tooth detection has been object of research during at least the last two decades, mainly relying in threshold and region-based methods. Following a different direction, this paper proposes to explore a deep learning method for instance segmentation of the teeth. To the best of our knowledge, it is the first system that detects and segment each tooth in panoramic X-ray images. It is noteworthy that this image type is the most challenging one to isolate teeth, since it shows other parts of patient's body (e.g., chin, spine and jaws). We propose a segmentation system based on mask region-based convolutional neural network to accomplish an instance segmentation. Performance was thoroughly assessed from a 1500 challenging image data set, with high variation and containing 10 categories of different types of buccal image. By training the proposed system with only 193 images of mouth containing 32 teeth in average, using transfer learning strategies, we achieved 98% of accuracy, 88% of F1-score, 94% of precision, 84% of recall and 99% of specificity over 1224 unseen images, results very superior than other 10 unsupervised methods. | |||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2018 > Deep instance segmentation... | |||
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Deep instance segmentation... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
| |||
| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGPAW/3RNF7US | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPAW/3RNF7US | |||
| Language | en | |||
| Target File | tooth_segmentation.pdf | |||
| User Group | lrebouca@ufba.br | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | |||
| Next Higher Units | 8JMKD3MGPAW/3RPADUS 8JMKD3MGPEW34M/4742MCS | |||
| Citing Item List | sid.inpe.br/sibgrapi/2018/09.03.20.37 46 sid.inpe.br/sibgrapi/2022/06.10.21.49 5 | |||
| 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 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 volume | |||