1. A new method to detect brain tumor using with convolution neural networks.
- Author
-
Pappula, Praveen, Ali Shaik, Mohammed, Tallapally, Sampath Kumar, Anitha, Vadlakonda, and Yogendernath, Nagavelli
- Subjects
- *
CONVOLUTIONAL neural networks , *BRAIN tumors , *MAGNETIC resonance imaging , *IMAGE processing , *NEURAL development - Abstract
A human-assisted manual classification might result in erroneous prediction and diagnosis, brain tumor identification is one of the most important and difficult challenges in the realm of medical image processing. Moreover, when there is a big number of data to be helped, it is difficult to work. Because brain tumors have such a wide range of appearances and because tumor and normal tissues are so comparable, extracting tumor areas from pictures is difficult. We suggested a method for extracting brain tumors from "magnetic resonance brain images (MRI)" using a Convolution neural network algorithm, followed by standard "convolutional neural network" categorization. The experiment used a real-time dataset. "Neural Network (CNN)" is a type of neural network that is created using Kera's and Tensor Flow and outperforms regular neural networks. Information on abnormal tissue development in the brain can be gleaned from MRIscanning. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF