%0 Journal Article %1 duddi2025design %A Duddi, Dr. M. V. Vijaya Saradhi | Gali Lahari Reddy | Ale Laxminarayana | Alladi Yuvaraj Kumar | Tanishq %D 2025 %J INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT %K Convolutional MRI Network, Neural U-Net, brain scans tumor, %N 1 %P 663-665 %T Design and Development of Brain Tumor Classification using Hybrid Deep Learning Algorithm %U https://www.ijtsrd.com/computer-science/other/75030/design-and-development-of-brain-tumor-classification-using-hybrid-deep-learning-algorithm/dr-m-v-vijaya-saradhi %V 9 %X Traditional brain tumor classification methods face limitations regarding time consuming manual analysis and the potential for inaccuracies. The study proposes a novel approach for brain tumor classification using a hybrid deep learning model incorporating U Net and CNNs. The model will be trained on a large dataset of labeled MRI images to learn features and classify tumors automatically. This approach promises faster diagnoses, improved accuracy compared to traditional methods, and reduced workload for radiologists. The research aims to explore the application of other imaging modalities and expand the scope of the tumor detection system. Dr. M. V. Vijaya Saradhi | Gali Lahari Reddy | Ale Laxminarayana | Alladi Yuvaraj Kumar | Tanishq Duddi "Design and Development of Brain Tumor Classification using Hybrid Deep Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-1 , February 2025, URL: https://www.ijtsrd.com/papers/ijtsrd75030.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/75030/design-and-development-of-brain-tumor-classification-using-hybrid-deep-learning-algorithm/dr-m-v-vijaya-saradhi

@article{duddi2025design, abstract = {Traditional brain tumor classification methods face limitations regarding time consuming manual analysis and the potential for inaccuracies. The study proposes a novel approach for brain tumor classification using a hybrid deep learning model incorporating U Net and CNNs. The model will be trained on a large dataset of labeled MRI images to learn features and classify tumors automatically. This approach promises faster diagnoses, improved accuracy compared to traditional methods, and reduced workload for radiologists. The research aims to explore the application of other imaging modalities and expand the scope of the tumor detection system. Dr. M. V. Vijaya Saradhi | Gali Lahari Reddy | Ale Laxminarayana | Alladi Yuvaraj Kumar | Tanishq Duddi "Design and Development of Brain Tumor Classification using Hybrid Deep Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-1 , February 2025, URL: https://www.ijtsrd.com/papers/ijtsrd75030.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/75030/design-and-development-of-brain-tumor-classification-using-hybrid-deep-learning-algorithm/dr-m-v-vijaya-saradhi }, added-at = {2025-06-30T13:49:28.000+0200}, author = {Duddi, Dr. M. V. Vijaya Saradhi | Gali Lahari Reddy | Ale Laxminarayana | Alladi Yuvaraj Kumar | Tanishq}, biburl = {https://www.bibsonomy.org/bibtex/28eae9bf1ef786d444e338e54b262421d/ijtsrd}, interhash = {321446d00bf70cd1b91af5dcd96349ae}, intrahash = {8eae9bf1ef786d444e338e54b262421d}, issn = {2456-6470}, journal = {INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT}, keywords = {Convolutional MRI Network, Neural U-Net, brain scans tumor,}, language = {english}, month = feb, number = 1, pages = {663-665}, timestamp = {2025-06-30T13:49:28.000+0200}, title = {Design and Development of Brain Tumor Classification using Hybrid Deep Learning Algorithm }, url = {https://www.ijtsrd.com/computer-science/other/75030/design-and-development-of-brain-tumor-classification-using-hybrid-deep-learning-algorithm/dr-m-v-vijaya-saradhi}, volume = 9, year = 2025 }