Leukemia segmentation and classification: A comprehensive survey

S Saleem, J Amin, M Sharif, GA Mallah, S Kadry… - Computers in Biology …, 2022 - Elsevier
Blood is made up of leukocytes (WBCs), erythrocytes (RBCs), and thrombocytes. The ratio of
blood cancer diseases is increasing rapidly, among which leukemia is one of the famous …

Hybrid techniques for the diagnosis of acute lymphoblastic leukemia based on fusion of CNN features

IA Ahmed, EM Senan, HSA Shatnawi, ZM Alkhraisha… - Diagnostics, 2023 - mdpi.com
Acute lymphoblastic leukemia (ALL) is one of the deadliest forms of leukemia due to the
bone marrow producing many white blood cells (WBC). ALL is one of the most common …

Assessing the impact of data augmentation and a combination of CNNs on leukemia classification

ML Claro, R de MS Veras, AM Santana, LHS Vogado… - Information …, 2022 - Elsevier
An accurate early-stage leukemia diagnosis plays a critical role in treating and saving
patients' lives. The two primary forms of leukemia are acute and chronic leukemia, which is …

A2M-LEUK: attention-augmented algorithm for blood cancer detection in children

FM Talaat, SA Gamel - Neural Computing and Applications, 2023 - Springer
Leukemia is a malignancy that affects the blood and bone marrow. Its detection and
classification are conventionally done through labor-intensive and specialized methods. The …

Colour and texture descriptors for visual recognition: A historical overview

F Bianconi, A Fernández, F Smeraldi, G Pascoletti - Journal of Imaging, 2021 - mdpi.com
Colour and texture are two perceptual stimuli that determine, to a great extent, the
appearance of objects, materials and scenes. The ability to process texture and colour is a …

[HTML][HTML] Advancing laboratory medicine practice with machine learning: swift yet exact

J You, HS Seok, S Kim, H Shin - Annals of Laboratory …, 2024 - pmc.ncbi.nlm.nih.gov
Machine learning (ML) is currently being widely studied and applied in data analysis and
prediction in various fields, including laboratory medicine. To comprehensively evaluate the …

Automatic detection and counting of blood cells in smear images using retinanet

G Drałus, D Mazur, A Czmil - Entropy, 2021 - mdpi.com
A complete blood count is one of the significant clinical tests that evaluates overall human
health and provides relevant information for disease diagnosis. The conventional strategies …

Automatic classification of pulmonary nodules in computed tomography images using pre-trained networks and bag of features

T Lima, D Luz, A Oseas, R Veras, F Araújo - Multimedia Tools and …, 2023 - Springer
Lung cancer has the highest incidence in the world. The standard tests for its diagnostics are
medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of …

Deep Learning and Entropy-Based Texture Features for Color Image Classification

E Lhermitte, M Hilal, R Furlong, V O'brien… - Entropy, 2022 - mdpi.com
In the domain of computer vision, entropy—defined as a measure of irregularity—has been
proposed as an effective method for analyzing the texture of images. Several studies have …

On the reliability of CNNs in clinical practice: a computer-aided diagnosis system case study

A Loddo, L Putzu - Applied Sciences, 2022 - mdpi.com
Leukocytes classification is essential to assess their number and status since they are the
body's first defence against infection and disease. Automation of the process can reduce the …