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@article{180254,
        author = {Venkatesan.B and Indhu.N and U.S. Ragupathy},
        title = {A Brain Tumor Detection System for MR Images using Modified Convolutional Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {767-774},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180254},
        abstract = {Brain and spine are the most important 
organs in human body as they control all the physical 
systems. It is well known that the brain is most complex 
organ in human body than the other organs. It is 
observed that brain tumour is one of the major causes 
for the increase in mortality among children and 
adults in the world. Brain tumour is an abnormal 
growth of cells within the brain or in central nervous 
system, which can be cancerous or non-cancerous 
(benign). It is required to develop Computer Aided 
Diagnosis (CAD) system for providing optimal solution 
for brain tumour detection. Brain tumour is generally 
predicted by neurologists with the help of symptoms, 
especially by a doctor who is specialised in treating the 
cancer. A non-invasive method using CAD are rapidly 
growing, not only to replace invasive method but also 
to achieve higher accuracy with less cost. It is also 
observed that the algorithm related to medical images 
are evolved in numbers. Deep learning techniques in 
detecting and classifying the medical image help the 
physicians to get a secondary opinion. An improved 
deep learning approaches is developed to detect the 
brain tumor and achieves 95.23% of classification 
accuracy.},
        keywords = {Brain Image, Convolutional Neural  Network and Deep Learning, Magnetic Resonance  Imaging, Tumor Detection},
        month = {June},
        }