| Autor: |
Nibedita Pati, Millee Panigrahi, Patra, Krishna Chandra |
| Rok vydání: |
2022 |
| Předmět: |
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| DOI: |
10.5281/zenodo.8115477 |
| Popis: |
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 |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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