Detection and Classification of Leukemia Using Deep Learning

Abstract

Abstract: The practice of medicine is getting modernized every year and continuously moving towards more automated systems that help and improves the healthcare practice to be more productive with treatments and accurate in their assessments. Leukemia is a form of cancer that can be a fatal disease, and to rehabilitate and treat it requires a correct and early diagnosis. Standard methods have transformed into automated computer tools for analyzing, diagnosing, and predicting symptoms. Advanced methods can be used to help patients detect terminal disorders such as leukemia, which is a fatal disorder and common cancer type amongst children. The methods used for the identification of leukemia subtypes in the suggested framework are Dense Convolutional Neural Network (DenseNet-121) and Residual Convolutional Neural Network (ResNet-34). Because advanced CNN models, such as ResNet and DenseNet, are deeper and more complex having the ability to learn better. Keywords: Leukemia, Deep Learning, Classification, DenseNet, ResNet, CNN