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Previous issue date: 2015-12-04 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / Neste trabalho ? proposto o desenvolvimento de um sistema inteligente capaz de segmentar, contar e classificar individualmente dentes a partir de imagens fotogr?ficas digitais intraorais oclusais.O sistema proposto faz uso combinado das t?cnicas de aprendizagem de m?quina no caso a m?quina de vetor de suporte e processamento digital de imagens. Primeiramente ? feita uma segmenta??o baseada nas cores dos dentes e n?o dentes presentes na imagem atrav?s do uso de m?quina de vetores de suporte. A partir da identifica??o das regi?es de interesse, dentes e n?o dentes, os dados s?o representados de modo que a contagem, detec??o de fronteiras e classifica??o dos dentes possa ser feita. Para contagem e detec??o de fronteiras s?o utilizadas t?cnicas baseadas em operadores morfol?gicos, eros?o e transformada watershed, respectivamente. A classifica??o quanto aos tipos de dentes ? baseada na utiliza??o dos descritores de posi??o e forma, sendo esse ?ltimo definido por descritores de Fourier. O sistema portanto ? capaz de realizar a segmenta??o, a contagem e a classifica??o de dentes presentes nas imagens. / Several are the areas in which digital images are used in solving day-to-day problems.
In medicine the use of computer systems have improved the diagnosis and medical interpretations.
In dentistry it?s not different, increasingly procedures assisted by computers
have support dentists in their tasks. Set in this context, an area of dentistry known as public
oral health is responsible for diagnosis and oral health treatment of a population. To
this end, oral visual inspections are held in order to obtain oral health status information
of a given population. From this collection of information, also known as epidemiological
survey, the dentist can plan and evaluate taken actions for the different problems
identified. This procedure has limiting factors, such as a limited number of qualified professionals
to perform these tasks, different diagnoses interpretations among other factors.
Given this context came the ideia of using intelligent systems techniques in supporting
carrying out these tasks. Thus, it was proposed in this paper the development of an intelligent
system able to segment, count and classify teeth from occlusal intraoral digital
photographic images. The proposed system makes combined use of machine learning
techniques and digital image processing. We first carried out a color-based segmentation
on regions of interest, teeth and non teeth, in the images through the use of Support
Vector Machine. After identifying these regions were used techniques based on morphological
operators such as erosion and transformed watershed for counting and detecting
the boundaries of the teeth, respectively. With the border detection of teeth was possible
to calculate the Fourier descriptors for their shape and the position descriptors. Then
the teeth were classified according to their types through the use of the SVM from the
method one-against-all used in multiclass problem. The multiclass classification problem
has been approached in two different ways. In the first approach we have considered three
class types: molar, premolar and non teeth, while the second approach were considered
five class types: molar, premolar, canine, incisor and non teeth. The system presented a
satisfactory performance in the segmenting, counting and classification of teeth present in
the images.
| Identifer | oai:union.ndltd.org:IBICT/oai:repositorio.ufrn.br:123456789/21042 |
| Date | 04 December 2015 |
| Creators | Lins, Ramon Augusto Sousa |
| Contributors | 10749896434, http://lattes.cnpq.br/1987295209521433, Martins, Allan de Medeiros, 01979076448, http://lattes.cnpq.br/4402694969508077, Soares, Heliana Bezerra, 80674585453, http://lattes.cnpq.br/5057165446370629, Carvalho, Marco Antonio Garcia de, 59564245400, http://lattes.cnpq.br/6366443994619479, D?ria Neto, Adri?o Duarte |
| Publisher | Universidade Federal do Rio Grande do Norte, PROGRAMA DE P?S-GRADUA??O EM ENGENHARIA EL?TRICA E DE COMPUTA??O, UFRN, Brasil |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/masterThesis |
| Source | reponame:Repositório Institucional da UFRN, instname:Universidade Federal do Rio Grande do Norte, instacron:UFRN |
| Rights | info:eu-repo/semantics/openAccess |
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