Automated analysis of blood smear images for leukemia detection: a comprehensive review

A Mittal, S Dhalla, S Gupta, A Gupta - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
Leukemia, the malignancy of blood-forming tissues, becomes fatal if not detected in the early
stages. It is detected through a blood smear test that involves the morphological analysis of …

All-IDB: The acute lymphoblastic leukemia image database for image processing

RD Labati, V Piuri, F Scotti - 2011 18th IEEE international …, 2011 - ieeexplore.ieee.org
The visual analysis of peripheral blood samples is an important test in the procedures for the
diagnosis of leukemia. Automated systems based on artificial vision methods can speed up …

An attention-based deep learning for acute lymphoblastic leukemia classification

M Jawahar, LJ Anbarasi, S Narayanan… - Scientific Reports, 2024 - nature.com
The bone marrow overproduces immature cells in the malignancy known as Acute
Lymphoblastic Leukemia (ALL). In the United States, about 6500 occurrences of ALL are …

Automated screening system for acute myelogenous leukemia detection in blood microscopic images

S Agaian, M Madhukar… - IEEE Systems …, 2014 - ieeexplore.ieee.org
Acute myelogenous leukemia (AML) is a subtype of acute leukemia, which is prevalent
among adults. The average age of a person with AML is 65 years. The need for automation …

Recognition of acute lymphoblastic leukemia cells in microscopic images using k-means clustering and support vector machine classifier

MM Amin, S Kermani, A Talebi… - Journal of Medical …, 2015 - journals.lww.com
Acute lymphoblastic leukemia is the most common form of pediatric cancer which is
categorized into three L1, L2, and L3 and could be detected through screening of blood and …

Computer aided diagnosis in digital pathology application: Review and perspective approach in lung cancer classification

AK AlZubaidi, FB Sideseq, A Faeq… - 2017 annual conference …, 2017 - ieeexplore.ieee.org
This electronic document is a “live” template and already defines the components of your
paper [title, text, heads, etc.] in its style sheet This paper provide a broad review for most …

[HTML][HTML] A decision support system for Acute Leukaemia classification based on digital microscopic images

AS Negm, OA Hassan, AH Kandil - Alexandria engineering journal, 2018 - Elsevier
In the era of digital microscopic imaging, Image Processing, data analysis, classification,
decision support systems have emerged as one of the most important tools for diagnostic …

Convolutional neural networks for recognition of lymphoblast cell images

T Pansombut, S Wikaisuksakul… - Computational …, 2019 - Wiley Online Library
This paper presents the recognition for WHO classification of acute lymphoblastic leukaemia
(ALL) subtypes. The two ALL subtypes considered are T‐lymphoblastic leukaemia (pre‐T) …

Rough set theory with Jaya optimization for acute lymphoblastic leukemia classification

G Jothi, HH Inbarani, AT Azar, KR Devi - Neural Computing and …, 2019 - Springer
Early diagnosis of malignant leukemia can enormously help the physicians in choosing the
right treatment for the patient. A lot of diagnostic techniques are available to identify …

The burden of leukemia in the Kingdom of Saudi Arabia: 15 years period (1999–2013)

A Bawazir, N Al-Zamel, A Amen, MA Akiel, NM Alhawiti… - BMC cancer, 2019 - Springer
Background Leukemia is a malignant neoplasm that arises from hematopoietic cells. The
number of leukemia cases has dramatically increased from 297,000 to 437, 033 cases …