Acute Lymphoblastic Leukemia Classification With Deep Learning
Prema Ganesan, N. S. Hari Krishnaa, SM Narayan · 2025
Acute Lymphoblastic Leukemia (ALL) is a rapidly progressing blood cancer characterized by the abnormal proliferation of immature lymphoid progenitor cells. This paper investigates the efficacy of various deep learning models, including VGG16, VGG19, InceptionV3, and MobileNetV2, in conjunction with the classification of ALL using the Acute Lymphoblastic Leukemia (ALL) image dataset. Our approach involves initially categorizing images as benign or malignant, followed by sub classification of malignant cases into three stages: Early, Pre, and Pro. We evaluate the performance of the models using metrics such as Accuracy, Precision, Recall, and Confusion Matrix.