Metodologia computacional para detecção automática de estrabismo em imagens digitais através do Teste de Hirschberg
Strabismus is a pathology that affects about 4% of the population causing aesthetic problems, reversible at any age, and irreversible tensorial alterations, modifying the vision mechanism. Hirschberg's test is one of the available exams to detect such pathology. Computer Aided Diagnosis and Det...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2010 |
| País: | Brasil |
| Institución: | Universidade Federal do Maranhão (UFMA) |
| Repositorio: | Biblioteca Digital de Teses e Dissertações da UFMA |
| Idioma: | portugués |
| OAI Identifier: | oai:tede2:tede/1813 |
| Acceso en línea: | http://tedebc.ufma.br:8080/jspui/handle/tede/1813 |
| Access Level: | acceso abierto |
| Palabra clave: | Funções Geoestatísticas Máquina de Vetores de Suporte Método de Hirschberg Estrabismo Reconhecimento de Padrões Processamento de Imagens Image Processing Pattern Recognition Strabismus Support Vector Machine Geostatistical Functions Processamento Gráfico Engenharia Biomédica |
| Sumario: | Strabismus is a pathology that affects about 4% of the population causing aesthetic problems, reversible at any age, and irreversible tensorial alterations, modifying the vision mechanism. Hirschberg's test is one of the available exams to detect such pathology. Computer Aided Diagnosis and Detection Systems have been used with relative success to help health professionals. Nevertheless, the increasingly application of high technology resources to help diagnosis and therapy in ophthalmology is not a reality in the Strabismus sub-specialty. This way, the present work has the objective of introduing a methodology for automatic detection Strabismus in digital images through Hirschberg's test. For such, it is organized in four stages: finding the region of the eyes, precise location of the eyes, limb and bright, and identi cation of Strabismus The methodology presents results of 100% of sensibility, 91,3% of specificity and 94% of match in the identification of Strabismus, comproving the eficiency of the geostatistical functions in the extraction of the texture of the eyes and of the calculations of the alignment between eyes in digital images acquired from Hirschberg's test. |
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