Abstract
Midline shift (MLS) is the most important quantitative feature clinicians use to evaluate the severity of brain compression by various pathologies. We proposed a model of the deformed midline according to the biomechanical properties of different types of intracranial tissue. The model comprised three segments. The upper and lower straight segments represented parts of the tough meninges separating two hemispheres, and the central curved segment, formed by a quadratic Bezier curve, represented the intervening soft brain tissue. For each point of the model, the intensity difference was calculated over 48 adjacent point pairs at each side. The deformed midline was considered ideal as summed square of the difference across all midline points approaches global minimum, simulating maximal bilateral symmetry. Genetic algorithm was applied to optimize the values of the three control points of the Bezier curve. Our system was tested on images containing various pathologies from 81 consecutive patients treated in a single institute over one-year period. The deformed midlines itself as well as the amount of midline shift were evaluated by human experts, with satisfactory results.
Original language | English |
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Pages (from-to) | 305-311 |
Number of pages | 7 |
Journal | Biomedical Engineering - Applications, Basis and Communications |
Volume | 18 |
Issue number | 6 |
DOIs | |
Publication status | Published - Dec 25 2006 |
Keywords
- Brain deformation
- Computed tomography
- Decision support system
- Genetic algorithm
- Medical image analysis
- Midline shift
- Pathological image
- Symmetry detection
ASJC Scopus subject areas
- Bioengineering
- Biophysics
- Biomedical Engineering