Automated detection and volume measurement of plexiform neurofibromas in neurofibromatosis 1 using magnetic resonance imaging

Jeffrey Solomon, Katherine Warren, Eva Dombi, Nicholas Patronas, Brigitte Widemann

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

An automated technique for segmentation and volumetric measurement of plexiform neurofibromas (PN) in neurofibromatosis 1 using short T1-inversion recovery magnetic resonance images is presented. The algorithm described implements heuristics derived from human-based recognition of lesions. This technique combines region-based with boundary-based segmentation. Two observers, who performed semi-automated volume calculations and manual tracings to estimate tumor volume, validated this method on 9 PNs of different size and location. This automated method was reproducible (coefficient of variation 0.6-5.6%), yielded similar results to manual tumor tracings (R=0.999), and will likely improve the ability to measure PNs in ongoing clinical trials.

Original languageEnglish (US)
Pages (from-to)257-265
Number of pages9
JournalComputerized Medical Imaging and Graphics
Volume28
Issue number5
DOIs
StatePublished - Jul 2004
Externally publishedYes

Keywords

  • Edge detection
  • Histogram
  • Image processing
  • Neurofibromatosis 1
  • Plexiform neurofibromas
  • Volumetric analysis

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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