Abstract
Computer-aided diagnostic (CAD) studies are used for scientific observations for explanation since very long time, but they are extraordinarily powerful to perform completely machine-driven algorithmic analyses for brain magnetic resonance imaging lesions. Structural and purposeful imbalance within the human brain could be reviewed. This imbalance analysis of the brain has terrific importance in an image analysis. In the present work, the imbalance between the two hemispheres is considered as the base for the detection of the tumour. We have segmented the brain into the two halves using thresholding technique, followed by statistical feature extraction for the double authentication of the existence of tumour which proves to be the better approach. The approach also takes into consideration corrections needed for the tilt observed while capturing the MRI.
Highlights
In trendy medication practices, medical pictures play a significant role and treated as necessary tools for the patient’s designation and treatment
There are many algorithms in the literature working on the principal of symmetry property of brain
The statistical first order, second order features can be extracted from selected half
Summary
Medical pictures play a significant role and treated as necessary tools for the patient’s designation and treatment. It is terribly troublesome to mechanically find solely the areas of illness in the medical pictures Accessing and researching real medical pictures akin to those of MRI, PET or CT scan could be a terribly advanced task as a result of confidentiality problems as well as significant methodological hurdles. To perform the above-mentioned steps in Brain Tumor Detection, three basic steps are as shown in figure 2. To perform these steps many researches have used different techniques. The major Difficulty faced by the researchers in MRI processing is the diversity of the feasible shape, location and picture intensities of a range of nature of tumours.
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