Classification of Gallbladder Cancer Using Average Ensemble Learning

Gallbladder cancer is a highly challenging malignancy within the field of oncology, distinguished by its diagnosis at an advanced stage and its restricted rates of survival. Gallbladder cancer classification from ultrasound images is a very difficult task due to poor image quality and speckle artifact. We suggest employing an ensemble of well-known Convolutional Neural Network models, such as VGG16, VGG19, XceptionNet, and ResNet50, to evaluate their effectiveness in differentiating between normal, benign, and malignant gall bladder conditions. As a result, the ensemble deep learning model significantly enhances the accuracy of classification.