Search for collections on FTS Digilib

An Intelligent Telediagnosis of Acute Lymphoblastic Leukemia using Histopathological Deep Learning

Khan Tusar, Md. Taufiqul Haque and Islam, Md. Touhidul and Sakil, Abul Hasnat and Khandaker, M N Huda Nahid and Hossain, Md. Monir (2024) An Intelligent Telediagnosis of Acute Lymphoblastic Leukemia using Histopathological Deep Learning. Journal of Computing Theories and Applications, 2 (1). pp. 1-12. ISSN 3024-9104

[thumbnail of 10358-Article Text-33261-2-10-20240615.pdf]
Preview
Text
10358-Article Text-33261-2-10-20240615.pdf - Published Version

Download (796kB) | Preview

Abstract

Leukemia, a global health challenge characterized by malignant blood cell proliferation, demands innovative diagnostic techniques due to its increasing incidence. Among leukemia types, Acute Lymphoblastic Leukemia (ALL) emerges as a particularly aggressive form affecting diverse age groups. This study proposes an advanced mechanized system utilizing Deep Neural Networks for detecting ALL blast cells in microscopic blood smear images. Achieving a remarkable accuracy of 97% using MobileNetV2, our system demonstrates high sensitivity and specificity in identifying multiple ALL sub-types. Furthermore, we introduce cutting-edge telediagnosis software facilitating real-time support for clinicians in promptly and accurately diagnosing various ALL subtypes from microscopic blood smear images. This research aims to enhance leukemia diagnosis efficiency, which is crucial for the timely intervention and managing this life-threatening condition.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: dl fts
Date Deposited: 24 Nov 2024 06:53
Last Modified: 24 Nov 2024 07:55
URI: https://dl.futuretechsci.org/id/eprint/20

Actions (login required)

View Item
View Item