A review on traditional machine learning and deep learning models for WBCs classification in blood smear images
In computer vision, traditional machine learning (TML) and deep learning (DL) methods
have significantly contributed to the advancements of medical image analysis (MIA) by …
have significantly contributed to the advancements of medical image analysis (MIA) by …
IoMT‐based automated detection and classification of leukemia using deep learning
N Bibi, M Sikandar, I Ud Din… - Journal of healthcare …, 2020 - Wiley Online Library
For the last few years, computer‐aided diagnosis (CAD) has been increasing rapidly.
Numerous machine learning algorithms have been developed to identify different diseases …
Numerous machine learning algorithms have been developed to identify different diseases …
Leukemia diagnosis in blood slides using transfer learning in CNNs and SVM for classification
LHS Vogado, RMS Veras, FHD Araujo… - … Applications of Artificial …, 2018 - Elsevier
Leukemia is a pathology that affects young people and adults, causing premature death and
several other symptoms. Computer-aided systems can be used to reduce the possibility of …
several other symptoms. Computer-aided systems can be used to reduce the possibility of …
Classification of white blood cells using weighted optimized deformable convolutional neural networks
X Yao, K Sun, X Bu, C Zhao, Y Jin - Artificial Cells, Nanomedicine …, 2021 - Taylor & Francis
Background Machine learning (ML) algorithms have been widely used in the classification of
white blood cells (WBCs). However, the performance of ML algorithms still needs to be …
white blood cells (WBCs). However, the performance of ML algorithms still needs to be …
A deep learning framework for leukemia cancer detection in microscopic blood samples using squeeze and excitation learning
Leukemia is a fatal category of cancer‐related disease that affects individuals of all ages,
including children and adults, and is a significant cause of death worldwide. Particularly, it is …
including children and adults, and is a significant cause of death worldwide. Particularly, it is …
Blood cell image segmentation and classification: a systematic review
Background Blood diseases such as leukemia, anemia, lymphoma, and thalassemia are
hematological disorders that relate to abnormalities in the morphology and concentration of …
hematological disorders that relate to abnormalities in the morphology and concentration of …
Executing spark BigDL for leukemia detection from microscopic images using transfer learning
Acute Leukemia disease is the bone marrow problem common both in children and adults.
Medical image analytics is applied in the field of Digital Image Processing (DIP) and Deep …
Medical image analytics is applied in the field of Digital Image Processing (DIP) and Deep …
A customized efficient deep learning model for the diagnosis of acute leukemia cells based on lymphocyte and monocyte images
S Ansari, AH Navin, AB Sangar, JV Gharamaleki… - Electronics, 2023 - mdpi.com
The production of blood cells is affected by leukemia, a type of bone marrow cancer or blood
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
cancer. Deoxyribonucleic acid (DNA) is related to immature cells, particularly white cells …
Automated detection and classification of leukemia on a subject-independent test dataset using deep transfer learning supported by Grad-CAM visualization
Leukemia is a type of cancer that affects blood cells and causes fatal infection and
premature death. Modern technology enabled by the machine and advanced deep learning …
premature death. Modern technology enabled by the machine and advanced deep learning …
Acute myeloid leukemia (AML) detection using AlexNet model
Acute Myeloid Leukemia (AML) is a kind of fatal blood cancer with a high death rate caused
by abnormal cells' rapid growth in the human body. The usual method to detect AML is the …
by abnormal cells' rapid growth in the human body. The usual method to detect AML is the …