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.

Graphical abstract

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.

中文翻译：

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B-Map：一种用于检测大脑中异物的基于模糊的模型

为了应对医疗并发症，科学家和医生更多地依赖数字化的历史证据。它帮助他们识别疾病并开发新的药物和策略。作者设计了一个名为 B-Map 的模型。它可以使用模糊规则检测和分割大脑中的任何异物。该模型可以检测癌症和脑肿瘤等物体。拟议的工作旨在设计一个分类器。分类器将有助于使用一个应用程序检测所有可能的异物。B-Map 已经与 K-means 和 ANN 等基准算法进行了比较。发现所提出的模型的性能明显优于当前技术。原始患者的样本报告取自不同的医学实验室。

图形概要

图形编号与论文中一样保留。所提出的模型能够找到边缘并分割不同类型的异物，或者可以说是出乎意料的发展。图 12 显示了大脑 MRI 切片的外边缘。患者的 MRI 非常清楚地显示脑积水。同样被分割并显示在图 13 中。图 14 显示了良性发展的部分，15 显示了癌性发展，它们再次被所提出的模型成功分割。

进行测试的数据是原始患者的临床数据。由于无法共享患者的详细信息和数据，作者无法将数据上传到存储库中。研究完成后，将创建一个基准数据集并将其上传到公共领域，以便研究人员可以访问它。