MRI scan database for classifying Meningioma Tumor in humans

This is the MRI scan database used in the research work of classifying Meningioma Tumor in humans by using hybrid Ensemble Deep Learning Network  AlGoRes. It consist of two sets; one for training and another one for testing the Deep Learning Network  AlGoRes.

Training data set consist of 822 imagers with meningioma_tumor and 395 images without tumor.

Testing data set consist of 115 imagers with meningioma_tumor and 104 images without tumor.

This study focuses on an ensemble framework effectuated through pre-trained deep learning networks such as the AlexNet, ResNet-50 and GoogleNet to procure a hybrid network named AlGoRes. The transfer learning from the pre-trained networks is employed further to comprehend the training and classification of meningioma tumors from the incorporated dataset. The results obtained thus evince that the classification accuracy is optimized in the constructed hybrid network as juxtaposed with the individual pre-trained networks. The simulations are carried out in MATLAB using the MRI scan database that demonstrates that the proposed approach holds substantial potential with respect to assisting healthcare professionals in early diagnosis, treatment planning, monitoring, along with improving patient outcomes and quality of care for meningioma patients.