Automated Detection of Acute Lymphoblastic Leukemia Subtypes from Microscopic Blood Smear Images using Deep Neural Networks

Md. Taufiqul Haque Khan Tusar, Roban Khan Anik
7/30/2022
eess.IVcs.AIcs.CV

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

An estimated 300,000 new cases of leukemia are diagnosed each year which is 2.8 percent of all new cancer cases and the prevalence is rising day by day. The most dangerous and deadly type of leukemia is acute lymphoblastic leukemia (ALL), which affects people of all age groups, including children and adults. In this study, we propose an automated system to detect various-shaped ALL blast cells from microscopic blood smears images using Deep Neural Networks (DNN). The system can detect multiple subtypes of ALL cells with an accuracy of 98 percent. Moreover, we have developed a telediagnosis software to provide real-time support to diagnose ALL subtypes from microscopic blood smears images.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Explainable AI in Diagnosing and Anticipating Leukemia Using Transfer Learning Method

87% match2023

A survey on automated detection and classification of acute leukemia and WBCs in microscopic blood cells

87% match2023

A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification

85% match2024

Patient-Level Diagnosis of Acute Myeloid Leukemia via Deep Learning Analysis of Bone Marrow Smear

85% match2026

A study on deep feature extraction to detect and classify Acute Lymphoblastic Leukemia (ALL)

85% match2024

BloodCell-Net: A lightweight convolutional neural network for the classification of all microscopic blood cell images of the human body

85% match2024

Cite this paper

@article{tusar2022automated,
  title  = {Automated Detection of Acute Lymphoblastic Leukemia Subtypes from Microscopic Blood Smear Images using Deep Neural Networks},
  author = {Md. Taufiqul Haque Khan Tusar and Roban Khan Anik},
  year   = {2022},
  eprint = {2208.08992},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2208.08992v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2208.08992.svg)](https://codeofpaper.com/paper/2208.08992)

Discussion