Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/48804
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Pandey, Pulkit | en_US |
dc.contributor.author | Bhan, Anupama | en_US |
dc.contributor.author | Dutta, Malay Kishore | en_US |
dc.contributor.author | Travieso, Carlos M. | en_US |
dc.date.accessioned | 2018-11-24T01:04:40Z | - |
dc.date.available | 2018-11-24T01:04:40Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.isbn | 9781538608500 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/48804 | - |
dc.description.abstract | Identification of the Root canal length is a major concern in the dentistry worldwide, which currently seeks the manual calculation in order to detect the measurement of the teeth. Intensity inhomogeneity often is a major problem in dental x-rays which causes considerable difficulties in segmentation. For better computer-aided diagnosis in dentistry, having a precise tooth segmentation is a critical task, as the cysts and inflammatory lesions generally occur around tooth root areas and these areas in radiographs are generally subject to noise, poor contrast, and very uneven illumination. This paper presents an effective segmentation method using a combinational approach of Local Gaussian Distribution fitting energy along with level sets. Here the local intensities of images are defined by Gaussian distributions which are combined with the level set function for accurate segmentations of teeth contour. The experimental results indicate that segmentation achieves the less number of iterations making it computationally fast and work in real time situation. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | 2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedings | en_US |
dc.source | 2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedings (7985529) | en_US |
dc.subject | 3314 Tecnología médica | en_US |
dc.subject.other | CLAHE | en_US |
dc.subject.other | Segmentation | en_US |
dc.subject.other | Bilateral filter | en_US |
dc.subject.other | Gaussian Distribution | en_US |
dc.subject.other | Independent level sets | en_US |
dc.title | Automatic Image Processing Based Dental Image Analysis Using Automatic Gaussian Fitting Energy and Level Sets | en_US |
dc.type | info:eu-repo/semantics/conferenceObject | en_US |
dc.type | ConferenceObject | en_US |
dc.relation.conference | 5th IEEE International Work Conference on Bio-Inspired Intelligence, IWOBI 2017 | en_US |
dc.identifier.doi | 10.1109/IWOBI.2017.7985529 | en_US |
dc.identifier.scopus | 85028578154 | - |
dc.contributor.authorscopusid | 56988601500 | - |
dc.contributor.authorscopusid | 56205889500 | - |
dc.contributor.authorscopusid | 35291803600 | - |
dc.contributor.authorscopusid | 6602376272 | - |
dc.identifier.issue | 7985529 | - |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Actas de congresos | en_US |
dc.utils.revision | Sí | en_US |
dc.date.coverdate | Julio 2017 | en_US |
dc.identifier.conferenceid | events121608 | - |
dc.identifier.ulpgc | Sí | es |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.event.eventsstartdate | 10-07-2017 | - |
crisitem.event.eventsenddate | 12-07-2017 | - |
crisitem.author.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.author.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.dept | Departamento de Señales y Comunicaciones | - |
crisitem.author.orcid | 0000-0002-4621-2768 | - |
crisitem.author.parentorg | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.fullName | Travieso González, Carlos Manuel | - |
Appears in Collections: | Actas de congresos |
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