To cope up with the medical complications, scientists and physicians rely more on digitized historical evidence. It helps them to identify the disease and to develop new drugs and strategies. The authors have designed a model called B-Map. It can detect and segmenting any foreign object in the brain using fuzzy rules. The model can detect objects such as cancer and brain tumor. The proposed work aims at designing a classifier. The classifier would help to detect all possible foreign objects using one application. B-Map has been compared with benchmark algorithms such as K-means and ANN. It was found that the proposed model performs significantly better than the current techniques. Original patients’ sample reports are taken from various medical laboratories. The figure numbers are retained as in the paper. The proposed model is able to find the edges and segment different types of foreign objects or one can say unexpected developments. Figure 12 shows the outer edges of a section of a brain MRI. The patient’s MRI very clearly shows Hydrocephalus. The same is segmented and shown in Fig. 13. Figure 14 shows a segment of benign development and 15 shows a cancerous development which are again successfully segmented by the proposed model. The data on which testing is done is clinical data of the original patients. As the patient’s details and data cannot be shared the author’s cannot upload the data in the repository. As soon as the research completes, a benchmark dataset will be created and uploaded in public domain so that researchers can access it.
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