Categorization & Classification of Acute & Chronic Leukaemia using Visual Geometry Group -16 Deep Convolutional Neural Network Architecture
Roopashree, Malini Suvarna, Dayakshini Dayakshini · 2023
A significant issue in the field of disease diagnosis is the accurate differentiation of malignant leukocytes with minimal expense in the early stages of the disease. This is necessary for early detection and diagnosis of leukaemia. Although there is a lot of leukaemia, there is a dearth of flow cytometry tools, and the techniques used at laboratory diagnostic centers take a lot of time. The CNN-based architecture will be a promising solution for the same. In this, we have developed the VGG-16-based model for the detection of leukemia & achieved an accuracy of around 90%