Three Dimensional Volumetric Modeling of the Internal Brain Structure Using Magnetic Resonance Imaging Slices

Abstract

The conventional cross sections of the brain, provided by magnetic resonance imaging (MRI) scanners, comprise a sparse dataset of 2-D gray-level images, that is neither capable of representing the 3-D nature of the brain, nor differentiating its various component parts in a convenient way. The target of the developed work is to fuse more information from the original MRI cross sections, which leads to building a 3-D computerized color-coded model of the normal human brain. The proposed model is beneficial in many areas like medical training, radiation treatment, 3-D model matching, or volume mensuration of brain component parts. This paper presents a revision of the different methods for building 3-D brain models, along with their advantages and disadvantages. A proposed method for building a 3-D brain model is then introduced. The method consists of three stages: interpolation of the original MRI slices, segmentation of the different brain tissues, and 3-D volumetric reconstruction. The resultant model can be geometrically transformed and arbitrarily dissected. The results are shown throughout the paper. Finally, the conclusions drawn from this work, as well as possible future extensions of the work, are listed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA412530

Entities

People

  • A. A. Sallam
  • E. H. Mohamed
  • M. S. Aboul-soud

Organizations

  • Suez Canal University

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Brain
  • Cerebral Cortex
  • Classification
  • Computer Vision
  • Correlation Techniques
  • Diagnostic Imaging
  • Electrical Engineering
  • Engineering
  • Graphical User Interface
  • Interpolation
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Medical Personnel
  • Neural Networks
  • Neuroimaging
  • Three Dimensional

Fields of Study

  • Engineering

Readers

  • Business Analytics
  • Computer Vision.
  • Neuroscience