Improved histological brain tumor classification
What is it about?
Providing an improved technique which can assist pathologists in correctly classifying meningioma brain tumours with a significant accuracy.
Why is it important?
A technique for histopathological meningioma tumour classification based on texture measures combination, which aims to overcome intra and inter-observer variability, has been proposed in this study. The morphological gradient of the RGB colour channel that best discriminates the cell-nuclei from the cytoplasm background is selected, and then feature extraction is performed by four statistical and model-based texture measures for discrimination using a Bayesian classifier. The pre-processing phase represented by the appropriate colour channel selection and morphological processing proved to be necessary for increasing texture feature separability, and hence can improve classification accuracy.
The following have contributed to this page: Dr Omar S Al-Kadi