Busca avançada

(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Morphological classification of odontogenic keratocysts using Bouligand-Minkowski fractal descriptors

Texto completo
Autor(es):
Florindo, Joao B. ; Bruno, Odemir M. ; Landini, Gabriel
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: COMPUTERS IN BIOLOGY AND MEDICINE; v. 81, p. 1-10, FEB 1 2017.
Citações Web of Science: 1
Resumo

The Odontogenic keratocyst (OKC) is a cystic lesion of the jaws, which has high growth and recurrence rates compared to other cysts of the jaws (for instance, radicular cyst, which is the most common jaw cyst type). For this reason OKCs are considered by some to be benign neoplasms. There exist two sub-types of OKCs (sporadic and syndromic) and the ability to discriminate between these sub-types, as well as other jaw cysts, is an important task in terms of disease diagnosis and prognosis. With the development of digital pathology, computational algorithms have become central to addressing this type of problem. Considering that only basic feature-based methods have been investigated in this problem before, we propose to use a different approach (the Bouligand - Minkowski descriptors) to assess the success rates achieved on the classification of a database of histological images of the epithelial lining of these cysts. This does not require the level of abstraction necessary to extract histologically-relevant features and therefore has the potential of being more robust than previous approaches. The descriptors were obtained by mapping pixel intensities into a three dimensional cloud of points in discrete space and applying morphological dilations with spheres of increasing radii. The descriptors were computed from the volume of the dilated set and submitted to a machine learning algorithm to classify the samples into diagnostic groups. This approach was capable of discriminating between OKCs and radicular cysts in 98% of images (100% of cases) and between the two sub-types of OKCs in 68% of images (71% of cases). These results improve over previously reported classification rates reported elsewhere and stiggest that Bouligand Minkowski descriptors are useful features to be used in histopathological images of these cysts. (AU)

Processo FAPESP: 13/22205-3 - Organização espacial de tecidos e análise fractal para a taxonomia automatizada de plantas
Beneficiário:Joao Batista Florindo
Linha de fomento: Bolsas no Exterior - Estágio de Pesquisa - Pós-Doutorado
Processo FAPESP: 12/19143-3 - Geometria fractal e análise de imagens aplicadas à Biologia Vegetal
Beneficiário:Joao Batista Florindo
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 14/08026-1 - Visão artificial e reconhecimento de padrões aplicados em plasticidade vegetal
Beneficiário:Odemir Martinez Bruno
Linha de fomento: Auxílio à Pesquisa - Regular