Acute Lymphoblastic Leukemia Classification With Jetson Nano

Acute lymphoblastic leukemia, or ALL, is a frequent, severe type of blood cancer that mainly affects young-sters.Classifying leukemia subtypes accurately and early is essential for enhancing patient outcomes and treatment planning. With the help of Jetson Nano, a small and potent edge computing platform, we present a novel method in this work for the automatic classification of ALL subtypes.Our system analyzes high-resolution microscopic images of blood samples taken from leukemia patients using deep learning techniques, notably convolutional neural networks (CNNs). Preprocessing techniques are applied to enhance image quality, and a customized CNN architecture is developed and optimized for the Jetson N ano platform. The model is instructed on a sizable dataset comprising diverse leukemia cell images, enabling it to learn intricate patterns and features associated with different ALL subtypes.