@InProceedings{Bergamasco:2018:3DMeOb,
author = "Bergamasco, Leila Cristina Carneiro",
affiliation = "{University of S{\~a}o Paulo}",
title = "3D medical objects retrieval approach using SPHARMs descriptor and
network flow as similarity measure",
booktitle = "Proceedings...",
year = "2018",
editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and
Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and
Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez,
Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de
and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa,
Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus,
Klaus de and Scheer, Sergio",
organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "CBIR 3D, SPHARMs, medical images, network flows, similairty
measure.",
abstract = "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.",
conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
conference-year = "29 Oct.-1 Nov. 2018",
doi = "10.1109/SIBGRAPI.2018.00049",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2018.00049",
language = "en",
ibi = "8JMKD3MGPAW/3RNPC8H",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3RNPC8H",
targetfile = "3d-medical-objects.pdf",
urlaccessdate = "2024, Apr. 29"
}