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 language | English (US) |
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Pages (from-to) | 257-265 |
Number of pages | 9 |
Journal | Computerized Medical Imaging and Graphics |
Volume | 28 |
Issue number | 5 |
DOIs | |
State | Published - Jul 2004 |
Externally published | Yes |
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