1. Identificação | |
Tipo de Referência | Artigo em Evento (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Código do Detentor | ibi 8JMKD3MGPEW34M/46T9EHH |
Identificador | 8JMKD3MGPEW34M/43B355H |
Repositório | sid.inpe.br/sibgrapi/2020/09.27.18.07 |
Última Atualização | 2020:09.28.21.58.13 (UTC) administrator |
Repositório de Metadados | sid.inpe.br/sibgrapi/2020/09.27.18.07.19 |
Última Atualização dos Metadados | 2022:06.14.00.00.08 (UTC) administrator |
DOI | 10.1109/SIBGRAPI51738.2020.00030 |
Chave de Citação | SilvaPinhPithOliv:2020:StToSe |
Título | A study on tooth segmentation and numbering using end-to-end deep neural networks |
Formato | On-line |
Ano | 2020 |
Data de Acesso | 17 maio 2024 |
Número de Arquivos | 1 |
Tamanho | 3515 KiB |
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2. Contextualização | |
Autor | 1 Silva, Bernardo Peters Menezes 2 Pinheiro, Laís Bastos 3 Pithon, Matheus Melo 4 Oliveira, Luciano Rebouças de |
Afiliação | 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) |
Endereço de e-Mail | bpmsilva@gmail.com |
Nome do Evento | Conference on Graphics, Patterns and Images, 33 (SIBGRAPI) |
Localização do Evento | Porto de Galinhas (virtual) |
Data | 7-10 Nov. 2020 |
Editora (Publisher) | IEEE Computer Society |
Cidade da Editora | Los Alamitos |
Título do Livro | Proceedings |
Tipo Terciário | Full Paper |
Histórico (UTC) | 2020-09-28 21:58:13 :: bpmsilva@gmail.com -> administrator :: 2020 2022-06-14 00:00:08 :: administrator -> bpmsilva@gmail.com :: 2020 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Tipo de Versão | finaldraft |
Palavras-Chave | deep neural networks instance segmentation and numbering panoramic dental X-rays |
Resumo | 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. |
Arranjo 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2020 > A study on... |
Arranjo 2 | urlib.net > SDLA > Fonds > Full Index > A study on... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | paper-camera-ready-final-com-acento.pdf | 28/09/2020 18:05 | 3.4 MiB | paper-camera-ready-final.pdf | 27/09/2020 15:07 | 3.4 MiB | |
Conteúdo da Pasta agreement | |
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4. Condições de acesso e uso | |
URL dos dados | http://urlib.net/ibi/8JMKD3MGPEW34M/43B355H |
URL dos dados zipados | http://urlib.net/zip/8JMKD3MGPEW34M/43B355H |
Idioma | en |
Arquivo Alvo | paper-camera-ready-final-com-acento.pdf |
Grupo de Usuários | bpmsilva@gmail.com |
Visibilidade | shown |
Permissão de Atualização | não transferida |
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5. Fontes relacionadas | |
Repositório Espelho | sid.inpe.br/banon/2001/03.30.15.38.24 |
Unidades Imediatamente Superiores | 8JMKD3MGPEW34M/43G4L9S 8JMKD3MGPEW34M/4742MCS |
Lista de Itens Citando | sid.inpe.br/sibgrapi/2020/10.28.20.46 6 |
Acervo Hospedeiro | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notas | |
Campos Vazios | 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 |
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7. Controle da descrição | |
e-Mail (login) | bpmsilva@gmail.com |
atualizar | |
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