Image segmentation

Pathology

Pattern recognition (psychology)

Brain tumor

Biology

Noise (video)

Algorithm

Image (mathematics)

Stage (stratigraphy)

Paleontology

Artificial intelligence

Mathematical morphology

Computer science

Computation

Computer vision

Medicine

Segmentation

Image processing

Procedia Computer Science

This study proposes a computer aided detection approach to diagnose brain tumor in its early stage using Mathematical Morphological Reconstruction (MMR). Image is pre-processed to remove noise and artefacts and then segmented to find regions of interest with probable tumor. A large number of textural and statistical features are extracted from the segmented image to classify whether the brain tumor in the image is benign or malignant. Experimental results show that the segmented images have a high accuracy while substantially reducing the computation time. The study shows that the proposed solution can be used to diagnose brain tumor in patients with a high success rate.

Image Segmentation for Early Stage Brain Tumor Detection using Mathematical Morphological Reconstruction