Brain tumour segmentation using SRGB colour space-based density assessment


Author(s): Nibedita Pati*, Millee Panigrahi and Krishna Chandra Patra

Medical image processing helps diagnose diseases early. Brain tumour segmentation is a medical imaging speciality. Computer vision and machine learning help doctors diagnose diseases effectively. This study uses Standard RGB (SRGB) density analysis to isolate brain tumours on MRI images. Input intensity values are normalized using SRGB colour space and a Gaussian filter to identify tumours from the background. Adaptive threshold identifies brain MRI tumour spaces. Brain tumour space is derived using area and density functions. Applying morphological functions eliminates false positives to detect the accurate tumour space. The proposed technique is evaluated using recall, precision, and F–measure.

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Awards Nomination

Editors List

  • Prof. Elhadi Miskeen

    Obstetrics and Gynaecology Faculty of Medicine, University of Bisha, Saudi Arabia

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh




  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis


  • Fava Maria Giovanna


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