Rate the Article: Digital Image Processing and Python for Acute Lymphoblastic Leukemia (ALL) Detection using Convolution Neutral Network (CNN) Algorithm, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 2 | Views: 217 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper | Computer Science | India | Volume 13 Issue 4, April 2024 | Rating: 4.6 / 10


Digital Image Processing and Python for Acute Lymphoblastic Leukemia (ALL) Detection using Convolution Neutral Network (CNN) Algorithm

Dr. M. Sangeetha, S. D. Akila


Abstract: The timely identification and diagnosis of leukemia, or the precise differentiation of malignant leukocytes at the lowest possible cost in the early stages of the disease, is a significant problem in the field of illness diagnostics. Despite the high prevalence of leukemia, laboratory diagnosis institutes have limited flow cytometer equipment and labor-intensive procedures. The goal of the current systematic review was to examine the literature on machine learning-based leukemia identification and classification. The promise of machine learning (ML) in the diagnosis of diseases served as the driving force behind it. Leukemia is a malignancy of the blood-forming tissues that affects the lymphatic and bone marrow systems. If caught early, treatment options are more effective. This study created a novel classification model for blood microscopic images that can identify between images with and without leukemia.


Keywords: leukemia diagnosis, machine learning, blood microscopic images, systematic review, cost-effective


Edition: Volume 13 Issue 4, April 2024,


Pages: 858 - 861



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