3D medical objects retrieval approach using SPHARMs descriptor and network flow as similarity measure

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art_BERGAMASCO_3D_medical_objects_retrieval_approach_using_SPHARMs_descriptor_2018.PDF (589.45 KB)
Citações na Scopus
2
Tipo de produção
conferenceObject
Data de publicação
2018
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
IEEE
Autores
BERGAMASCO, Leila C. C.
LIMA, Karla R. P. S.
NUNES, Fatima L. S.
Citação
PROCEEDINGS 2018 31ST SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), p.329-336, 2018
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
The data processing to obtain useful information is a trending topic in the computing knowledge domain since we have observed a high demand arising from society for efficient techniques to perform this activity. Spherical Harmonics (SPHARMs) have been widely used in the three-dimensional (3D) object processing domain. Harmonic coefficients generated by this mathematical theory are considered a robust source of information about 3D objects. In parallel, Ford-Fulkerson is a classical method in graph theory that solves network flows problems. In this work we demonstrate the potential of using SPHARMs along with the Ford-Fulkerson method, respectively as descriptor and similarity measure. This article also shows how we adapted the later to transform it into a similarity measure. Our approach has been validated by a 3D medical dataset composed by 3D left ventricle surfaces, some of them presenting Congestive Heart Failure (CHF). The results indicated an average precision of 90%. In addition, the execution time was 65% lower than a descriptor previously tested. With the results obtained we can conclude that our approach, mainly the Ford-Fulkerson adaptation proposed, has a great potential to retrieve 3D medical objects.
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URI
https://observatorio.fm.usp.br/handle/OPI/31541
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Coleções
Comunicações em Eventos - HC/InCor