Neuro Vision: Deep Learning-Based Brain Tumor Identification

Main Article Content

Shreya Nehe
Renuka Gunjal
Komal Mane
Nafisa Desai
Rudraksh Patil

Abstract

 


Early and accurate identification of brain tumours from MRI images is essential to prevent severe and life-threatening conditions. The complex nature of brain tissues makes tumour detection, segmentation, and classification a challenging process. Tumour differ in size, shape, texture, and position, which reduces the accuracy of traditional detection methods. In this paper, a deep learning-based system is introduced using Convolutional Neural Networks (CNNs) for automatic brain tumour analysis. Image enhancement techniques such as Denoising Wavelet Transform (DWT) and Diffusion Tensor Imaging (DTI) are applied to improve image clarity and feature extraction. The use of multimodal MRI scans provides detailed structural information, leading to better tumour segmentation and classification. The proposed system improves diagnostic accuracy and supports doctors in making faster and more dependable clinical decisions.


 

Article Details

How to Cite
Nehe, S., Gunjal, R., Mane, K., Desai, N., & Patil, R. (2026). Neuro Vision: Deep Learning-Based Brain Tumor Identification. International Journal of Electrical, Electronics and Computer Systems, 15(1S), 234–240. https://doi.org/10.65521/ijeecs.v15i1S.3061
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Articles

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