• Rajat Kumar
• Animesh Kumar

This information will guide you through the process of creating tumour detection using deep learning using CNN (convolutional neural network). The aim of this work is the implementation of an innovative image fusion system for the detection of brain tumors. Combining MRI and PET images can provide a precise picture of tumor response. With this project, we can test brain tumours with the help of deep learning . We put a sample image and the algorithm will check whether the image is of a normal brain or if there is some abnormalities in the brain. The average slope, mismatch, and entropy of the fusion parameters are calculated and the results indicate the effectiveness of the fusion based on the DWT. This work can be extended to diagnose all kinds of abnormalities in human organs. To achieve a flexible and effective brain tumor segmentation system, this article first proposes a preprocessing approach that processes only a small portion of the image rather than the entire image. This method reduces computation time and solves the over- fitting problem of cascaded deep learning models.

"Brian Tomour Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.d803-d808, April-2024, Available :http://www.jetir.org/papers/JETIR2404399.pdf

"Brian Tomour Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppd803-d808, April-2024, Available at : http://www.jetir.org/papers/JETIR2404399.pdf