Year: 2025
Type: article
Abstract: This research introduces a stepwise method for enhancing and segmenting MRI brain scans, utilizing classical image processing techniques including anisotropic diffusion, skull extraction, and contrast enhancement strategies like top-hat and histogram-based filtering. The tumor segmentation process leverages the watershed transform for precise boundary detection. The entire workflow, developed in Python with OpenCV and scikit-image, was applied to a curated set of 80 brain MRI samples. Qualitative analysis suggests that this resource-efficient and explainable pipeline reliably identifies tumor regions with high clarity — making it practical for clinical environments with limited computational infrastructure.
Author: Manoj N Sogi
Language: English
Subfield: Neurology
Field: Neuroscience
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4412638584