| 1. Identity statement | |||||||
| Reference Type | Conference Paper (Conference Proceedings) | ||||||
| Site | sibgrapi.sid.inpe.br | ||||||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | ||||||
| Identifier | 8JMKD3MGPEW34M/43B355H | ||||||
| Repository | sid.inpe.br/sibgrapi/2020/09.27.18.07 | ||||||
| Last Update | 2020:09.28.21.58.13 (UTC) administrator | ||||||
| Metadata Repository | sid.inpe.br/sibgrapi/2020/09.27.18.07.19 | ||||||
| Metadata Last Update | 2022:06.14.00.00.08 (UTC) administrator | ||||||
| DOI | 10.1109/SIBGRAPI51738.2020.00030 | ||||||
| Citation Key | SilvaPinhPithOliv:2020:StToSe | ||||||
| Title | A study on tooth segmentation and numbering using end-to-end deep neural networks  | ||||||
| Format | On-line | ||||||
| Year | 2020 | ||||||
| Access Date | 2024, Oct. 04 | ||||||
| Number of Files | 1 | ||||||
| Size | 3515 KiB | ||||||
| 2. Context | |||||||
| Author | 1 Silva, Bernardo Peters Menezes 2 Pinheiro, Laís Bastos 3 Pithon, Matheus Melo 4 Oliveira, Luciano Rebouças de | ||||||
| Affiliation | 1 Universidade Federal da Bahia 2 Universidade Federal da Bahia 3 Universidade Estadual do Sudoeste da Bahia 4 Universidade Federal da Bahia | ||||||
| Editor | Musse, Soraia Raupp Cesar Junior, Roberto Marcondes Pelechano, Nuria Wang, Zhangyang (Atlas) | ||||||
| e-Mail Address | bpmsilva@gmail.com | ||||||
| Conference Name | Conference on Graphics, Patterns and Images, 33 (SIBGRAPI) | ||||||
| Conference Location | Porto de Galinhas (virtual) | ||||||
| Date | 7-10 Nov. 2020 | ||||||
| Publisher | IEEE Computer Society | ||||||
| Publisher City | Los Alamitos | ||||||
| Book Title | Proceedings | ||||||
| Tertiary Type | Full Paper | ||||||
| History (UTC) | 2020-09-28 21:58:13 :: bpmsilva@gmail.com -> administrator :: 2020 2022-06-14 00:00:08 :: administrator -> bpmsilva@gmail.com :: 2020 | ||||||
| 3. Content and structure | |||||||
| Is the master or a copy? | is the master | ||||||
| Content Stage | completed | ||||||
| Transferable | 1 | ||||||
| Version Type | finaldraft | ||||||
| Keywords | deep neural networks instance segmentation and numbering panoramic dental X-rays | ||||||
| Abstract | Shape, number, and position of teeth are the main targets of a dentist when screening for patient's problems on X-rays. Rather than solely relying on the trained eyes of the dentists, computational tools have been proposed to aid specialists as decision supporter for better diagnoses. When applied to X-rays, these tools are specially grounded on object segmentation and detection. In fact, the very first goal of segmenting and detecting the teeth in the images is to facilitate other automatic methods in further processing steps. Although researches over tooth segmentation and detection are not recent, the application of deep learning techniques in the field is new and has not reached maturity yet. To fill some gaps in the area of dental image analysis, we bring a thorough study on tooth segmentation and numbering on panoramic X-ray images by means of end-to-end deep neural networks. For that, we analyze the performance of four network architectures, namely, Mask R-CNN, PANet, HTC, and ResNeSt, over a challenging data set. The choice of these networks was made upon their high performance over other data sets for instance segmentation and detection. To the best of our knowledge, this is the first study on instance segmentation, detection, and numbering of teeth on panoramic dental X-rays. We found that (i) it is completely feasible to detect, to segment, and to number teeth by through any of the analyzed architectures, (ii) performance can be significantly boosted with the proper choice of neural network architecture, and (iii) the PANet had the best results on our evaluations with an mAP of 71.3% on segmentation and 74.0% on numbering, raising 4.9 and 3.5 percentage points the results obtained with Mask R-CNN. | ||||||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2020 > A study on... | ||||||
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > A study on... | ||||||
| doc Directory Content | access | ||||||
| source Directory Content |
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| agreement Directory Content |
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| 4. Conditions of access and use | |||||||
| data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/43B355H | ||||||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/43B355H | ||||||
| Language | en | ||||||
| Target File | paper-camera-ready-final-com-acento.pdf | ||||||
| User Group | bpmsilva@gmail.com | ||||||
| Visibility | shown | ||||||
| Update Permission | not transferred | ||||||
| 5. Allied materials | |||||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | ||||||
| Next Higher Units | 8JMKD3MGPEW34M/43G4L9S 8JMKD3MGPEW34M/4742MCS | ||||||
| Citing Item List | sid.inpe.br/sibgrapi/2020/10.28.20.46 31 sid.inpe.br/sibgrapi/2022/06.10.21.49 2 | ||||||
| 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 | ||||||
| 7. Description control | |||||||
| e-Mail (login) | bpmsilva@gmail.com | ||||||
| update | |||||||