Brain tumour classification using neural Network

Computer engineering

Recent development of technologies has created a major development in medical field .one of the most fatal disease brain tumour has been detected using these technologies. 2 D CNN has optimal accuracy in classifying brain tumour comparing the performance of various CNN and the machine learning methods by diagnosis of 3 type of brain tumour revealed that the 2 D CNN achieved exemplary performance and optimal execution time without latency this and encouraged radiologists and the physician to use this system for brain tumour detection .Recent advancements in the field of machine learning, specifically within deep learning, have enabled the recognition and categorization of patterns within medical images. In image process that most successful technique used to CNN has they have many layers and diagnosing accuracy Machine learning is rapidly emerging as a valuable asset across various medical domains, encompassing tasks like disease prognosis, diagnosis, the identification of molecular and cellular structures, tissue segmentation, and image classification Machine learning methods, particularly deep learning, can be crucial in examining, dividing, and categorizing cancer images, particularly those related to brain tumours . Additionally, employing these techniques enables precise and mistake-free tumour recognition, distinguishing them from other similar ailments

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