Prognosis of Neurological Disorder
S.Gnanavel1, M.Sreekrishna2, Nivedha K3, Preethi S, Pranav V4
1S.Gnanavel, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India.
2M.Sreekrishna, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai, India.
3Nivedha K, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai.
4Preethi S, UG Scholar, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai.
5Pranav V, UG Scholar, Department of Computer Science and Engineering, Rajalakshmi Engineering College, Chennai.
Manuscript received on February 28, 2020. | Revised Manuscript received on March 22, 2020. | Manuscript published on March 30, 2020. | PP: 5305-5311 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9841038620/2020©BEIESP | DOI: 10.35940/ijrte.F9841.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Neurological disorders of the brain are generally difficult to diagnose at the early stages. Since common symptoms like headaches, fatigue or difficulty in speaking and understanding can be related to any neurological disorder. It can be noted that most of the neurological disorders are curable if detected at an early stage. Thus, the life expectancy of the patient will be increased through an early detection and an early start of the curative procedure. An accurate identification of the disorder can be done by processing the MRI images of the patient. While brain disorders like tumor, stroke can be classified with an abnormal growth of the brain tissue., disorders like Alzheimer’s occur due to degeneration of brain cells. Since all the neurological disorders have common symptoms differentiating them at the beginning stages is considered a challenge. A rule based expert system with a set of rules is used for processing the symptom experienced by the patient. Each symptom is associated with a weighting factor that determines the risk to a particular disorder. Once the risk factor is evaluated the MRI images of the patient is scanned to obtain the severity of the disorder. By utilizing an expert system for analysis of symptom and image processing to detect the region of abnormality we may derive accurate results. Thus an effective prognosis can help patients get into the treatment at the earliest.
Keywords: Neurological Disorders, MRI (Magnetic Resonance Imaging), Pre-Processing, Feature Extraction, Classification.
Scope of the Article: Signal and Speech Processing.