Pre-Processing Investigation For Brain Abnormality Detection And Analysis Through MRI of Brain

Both men and women face equal risk from conditions such brain tumours, strokes, blood clots, and multiple sclerosis (MS). The most frequent and prevalent of these brain illnesses is a brain tumour. The prognosis and therapy for a brain lesion depend on how quickly and precisely it is diagnosed. However, neuroradiology experts are the only ones qualified to make the diagnosis, as it is extremely difficult. Each medical report from an imaging investigation must be reviewed and confirmed by at least two physicians. If there's a problem, it could mean a biopsy or even surgery. This study describes a fully automated procedure for removing artefacts and the skull from magnetic resonance (MR) pictures of the brain by utilising computational geometry, wavelet decomposition, and thresholding. The intermediate step of correct preprocessing of MR images is thresholding using the standard deviation method. For various MR images, the suggested preprocessing approach achieves a high degree of accuracy with a small error rate. This preliminary processing is employed to lessen the likelihood of erroneous detection. As a result, the accuracy with which diseases are diagnosed using brain MRI by a computer system is improved.