Enhancing Brain Tumor Diagnosis with Deep Transfer Learning: A Multi-Modal Approach

The Tumour Detection model makes it easier to locate the tumor in a human brain by using a multi-modal approach. Our model integrates ResNet and ResUNet to predict as well as locate the tumor with incredible accuracy. The use of ResNet and ResUNet makes the prediction process faster and thus makes it commercially a viable option. The model is aimed to be a quick and easy way to detect tumors in the human brain in areas where accessibility to quality medical expertise is limited.Clinical Relevance—The developed brain tumor detection model operates with an average prediction and localization time of 22 milliseconds on MRI scans. This rapid assessment holds the potential to significantly reduce patient wait times for diagnosis, streamlining the initial consultation process. By identifying the presence or absence of a tumor, the model empowers specialists to proceed with treatment for confirmed cases, optimizing the efficiency of their workflows.