Abstract
Despite current advances in neuro-imaging, the characterisation of paediatric brain tumours and neurological disorders is very challenging. Whilst Magnetic Resonance Imaging (MRI) provides images of superb clarity, it gives little information on how aggressive a tumour is. It is also very difficult to visually inspect any underlying textural patterns between tumours on MR images. This gives rise to the need for a quantitative means of analysing MR images for characterising tumours. In this work, we present a preliminary investigation into the effectiveness of texture analysis as a quantitative approach for classifying paediatric brain tumours.
Original language | English |
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Pages (from-to) | 169-71 |
Number of pages | 3 |
Journal | Studies in health technology and informatics |
Volume | 190 |
Publication status | Published - 2013 |
Keywords
- Algorithms
- Artificial Intelligence
- Brain
- Brain Neoplasms
- Child
- Child, Preschool
- Female
- Humans
- Image Interpretation, Computer-Assisted
- Infant
- Infant, Newborn
- Magnetic Resonance Imaging
- Male
- Pattern Recognition, Automated
- Pilot Projects
- Reproducibility of Results
- Sensitivity and Specificity
- Journal Article