[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges

T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …

Systematic review of an automated multiclass detection and classification system for acute Leukaemia in terms of evaluation and benchmarking, open challenges …

MA Alsalem, AA Zaidan, BB Zaidan, M Hashim… - Journal of medical …, 2018 - Springer
This study aims to systematically review prior research on the evaluation and benchmarking
of automated acute leukaemia classification tasks. The review depends on three reliable …

Recognition of peripheral blood cell images using convolutional neural networks

A Acevedo, S Alférez, A Merino, L Puigví… - Computer methods and …, 2019 - Elsevier
Background and objectives Morphological analysis is the starting point for the diagnostic
approach of more than 80% of hematological diseases. However, the morphological …

Classification of white blood cells using capsule networks

YY Baydilli, Ü Atila - Computerized Medical Imaging and Graphics, 2020 - Elsevier
Background While the number and structural features of white blood cells (WBC) can
provide important information about the health status of human beings, the ratio of sub-types …

Automated diagnosis of leukemia: a comprehensive review

A Shah, SS Naqvi, K Naveed, N Salem… - IEEE …, 2021 - ieeexplore.ieee.org
Leukemia is the rapid production of abnormal white blood cells that consequently affects the
blood and damages the bone marrow. The overproduction of abnormal and immature white …

Computer aided diagnostic system for detection of leukemia using microscopic images

J Rawat, A Singh, HS Bhadauria, J Virmani - Procedia Computer Science, 2015 - Elsevier
In present scenario, hematological disorders of leukocyte (WBC) are very frequent in
medical practices. This work proposes a novel technique to differentiate ALL (acute …

Acute lymphoblastic leukemia segmentation using local pixel information

SS Al-jaboriy, NNA Sjarif, S Chuprat… - Pattern Recognition …, 2019 - Elsevier
The severity of acute lymphoblastic leukemia depends on the percentages of blast cells
(abnormal white blood cells) in bone marrow or peripheral blood. The manual microscopic …

A review of the automated detection and classification of acute leukaemia: Coherent taxonomy, datasets, validation and performance measurements, motivation, open …

MA Alsalem, AA Zaidan, BB Zaidan, M Hashim… - Computer methods and …, 2018 - Elsevier
Context Acute leukaemia diagnosis is a field requiring automated solutions, tools and
methods and the ability to facilitate early detection and even prediction. Many studies have …

A new acute leukaemia-automated classification system

S Agaian, M Madhukar… - Computer Methods in …, 2018 - Taylor & Francis
Acute leukaemia is a type of cancer that affects the blood and the bone marrow. Detection
and classification of white blood cells is a challenge in image processing, as manual data …

Cancer diagnosis using artificial intelligence: a review

KA Shastry, HA Sanjay - Artificial Intelligence Review, 2022 - Springer
Artificial intelligence (AI) is the usage of scientific techniques to simulate human intellectual
skills and to tackle complex medical issues involving complicated genetic defects such as …