Three-Dimensional Segmentation of the Tumor in Computed Tomographic Images of Neuroblastoma

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dc.contributor.authorDeglint, Hanford J.
dc.contributor.authorRangayyan, Rangaraj M.
dc.contributor.authorFABIO JOSE AYRES
dc.contributor.authorBoag, Graham S.
dc.contributor.authorZuffo, Marcelo K.
dc.creatorDeglint, Hanford J.
dc.creatorRangayyan, Rangaraj M.
dc.creatorBoag, Graham S.
dc.creatorZuffo, Marcelo K.
dc.date.accessioned2024-11-11T23:43:31Z
dc.date.available2024-11-11T23:43:31Z
dc.date.issued2007
dc.description.abstractSegmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost Always heterogeneous in nature; furthermore, viable tumor, necrosis, and normal tissue are often intermixed. Tumor definition and diagnosis require the analysis of the spatial distribution and Hounsfield unit (HU) values of voxels in computed tomography (CT) images, coupled with a knowledge of normal anatomy. Segmentation and analysis of the tissue composition of the tumor can assist in quantitative assessment of the response to therapy and in the planning of delayed surgery for resection of the tumor. We propose methods to achieve 3-dimensional segmentation of the neuroblastic tumor. In our scheme, some of the normal structures expected in abdominal CT images are delineated and removed from further consideration; the remaining parts of the image volume are then examined for the tumor mass. Mathematical morphology, fuzzy connectivity, and other image processing tools are deployed for this purpose. Expert knowledge provided by a radiologist in the form of the expected structures and their shapes, HU values, and radiological characteristics are incorporated into the segmentation algorithm. In this preliminary study, the methods were tested with 10 CT exams of four cases from the Alberta Children’s Hospital. False-negative error rates of less than 12% were obtained in eight of the 10 exams; however, seven of the exams had false-positive error rates of more than 20% with respect to manual segmentation of the tumor by a radiologist.en
dc.formatDigital
dc.format.extentp. 72 – 87
dc.identifier.doi10.1007/10278-006-0769-3
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/7213
dc.language.isoInglês
dc.relation.ispartofJ Digit Imaging
dc.subject3D image segmentationen
dc.subjectNeuroblastomaen
dc.subjectComputed tomographyen
dc.subjectFuzzy connectivityen
dc.subjectTumor segmentationen
dc.titleThree-Dimensional Segmentation of the Tumor in Computed Tomographic Images of Neuroblastoma
dc.typejournal article
dspace.entity.typePublication
local.identifier.sourceUrihttps://link.springer.com/article/10.1007/10278-006-0769-3#citeas
local.publisher.countryNão Informado
local.subject.cnpqCIENCIAS DA SAUDE::MEDICINA::RADIOLOGIA MEDICA
local.subject.cnpqCIENCIAS DA SAUDE::MEDICINA::CLINICA MEDICA::CANCEROLOGIA
local.subject.cnpqENGENHARIAS::ENGENHARIA BIOMEDICA
local.subject.cnpqENGENHARIAS::ENGENHARIA ELETRICA
local.subject.cnpqCIENCIAS EXATAS E DA TERRA::MATEMATICA::MATEMATICA APLICADA
local.typeArtigo Científico
publicationvolume.volumeNumber20
relation.isAuthorOfPublication37971022-7c69-4e93-9186-4c9431a1f95c
relation.isAuthorOfPublication.latestForDiscovery37971022-7c69-4e93-9186-4c9431a1f95c
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