Paper Title :Brain Tumour Detection Using Deep Convolutional Neural Network
Author :Shubhanshu Pandey, Zubair Khan, Monika Vishwakarma
Article Citation :Shubhanshu Pandey ,Zubair Khan ,Monika Vishwakarma ,
(2023 ) " Brain Tumour Detection Using Deep Convolutional Neural Network " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 61-64,
Volume-11,Issue-5
Abstract : The idea of CNN is A tumor is nothing but excess cells growing in an uncontrolled manner. Brain tumor cells
grow in a way that they eventually take up all the nutrients meant for the healthy cells and tissues, which results in brain
failure. Currently, doctors locate the position and the area of brain tumor by looking at the MR Images of the brain of the
patient manually. This results in inaccurate detection of the tumor and is considered very time consuming. A Brain Cancer is
very critical disease which causes deaths of many individuals. The brain tumor detection and classification system is
available so that it can be diagnosed at early stages. Cancer classification is the most challenging tasks in clinical diagnosis.
The classification of brain tumors is one of the most significant and difficult problems to solve. As a result of the fact that
manual classification with the assistance of humans might result in incorrect diagnoses and forecasts. In addition to this,
whenever there is a substantial amount of information that must be processed manually, the process develops into a lengthy
activity that is difficult to complete. As a result of the fact that brain tumors can take on a wide variety of forms, as well as
the fact that there is a certain degree of similarity among normal and tumor tissues, it can be challenging to distinguish
sections of a patient's brain that contain tumors from scans of that brain.
Keyword - Classification, Diagnosis, Brain Cancer, Brain Tumor
Type : Research paper
Published : Volume-11,Issue-5
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-19797
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Copyright: © Institute of Research and Journals
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Published on 2023-09-08 |
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