Modified Image Segmentation Schemes for Detection & Identification of MRI Brain Tumor Infection
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Abstract
Nowadays an advancement in the medical field has an additional contribution to the human health care system. Many of the time, it cannot be possible to predict MRI brain tumor with naked eyes and unable to identify the disease stage. The patient may lost their live due un accurate and delayed diagnosis. Only CT scan and MRI cannot identify the disease, required supporting soft computing tools (PSO -particle swarm optimization) to diagnose with high accuracy. To perform accurate detection and analysis of the infected tumor, need some additional technical effort. The proposed concept suggests an algorithm using soft computing to identify infected regions of brain tumor along with its comparison with other existing image segmentation method. Result analysis shows that the result obtained with the proposed method are superior to existing segmentation techniques.
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