Brain tumour segmentation using SRGB colour space-based density assessment
Abstract
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.
Share this article
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
Google Scholar citation report
Citations : 2495
Onkologia i Radioterapia received 2495 citations as per Google Scholar report
Onkologia i Radioterapia peer review process verified at publons
Indexed In
- Scimago
- SCOPUS
- MIAR
- Euro Pub
- Google Scholar
- Medical Project Poland
- PUBMED
- Cancer Index
- Gdansk University of Technology, Ministry Points 20