Segmentation and Estimation of the Histological Composition of the Tumor Mass in Computed Tomographic Images of Neuroblastoma

Abstract

The problem that we investigate in the present paper Is the improvement of the analysis of the primary tumor mass, in patients with advanced neuroblastoma, using X-ray computed tomography (CT) exams. To achieve this goal, we propose a methodology for the estimation of the histological content of the mass that comprises a technique for semi-automatic segmentation of the primary tumor mass in CT images of neuroblastoma and a statistical method to estimate, from segmented CT images, the histological composition of the primary tumor. The results of the method are compared with the results of histological analysis of surgically resected tumor mass. Keyww%Is - Image segmentation, computed tomography, feature extraction, neuroblastoma

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA409694

Entities

People

  • Fabio J. Ayres
  • Marcelo K. Zuffo
  • Marcelo Valente
  • Rangaraj M. Rangayyan
  • Vicente O. Filho

Organizations

  • University of Calgary

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Algorithms
  • Cancer
  • Computer Vision
  • Computers
  • Diagnostic Imaging
  • Engineering
  • Health Services
  • Image Processing
  • Image Segmentation
  • Imaging Techniques
  • Medical Personnel
  • Neoplasms
  • Physicians
  • Probability
  • Probability Density Functions
  • Tomography
  • X-Ray Computed Tomography

Fields of Study

  • Physics

Readers

  • Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference