A survey on applications of deep learning in microscopy image analysis
Z Liu, L Jin, J Chen, Q Fang, S Ablameyko, Z Yin… - Computers in biology …, 2021 - Elsevier
Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
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 …
LeuFeatx: Deep learning–based feature extractor for the diagnosis of acute leukemia from microscopic images of peripheral blood smear
The abnormal growth of leukocytes causes hematologic malignancies such as leukemia.
The clinical assessment methods for the diagnosis of the disease are labor-intensive and …
The clinical assessment methods for the diagnosis of the disease are labor-intensive and …
Comparison of traditional image processing and deep learning approaches for classification of white blood cells in peripheral blood smear images
Automated classification and morphological analysis of white blood cells has been
addressed since last four decades, but there is no optimal method which can be used as …
addressed since last four decades, but there is no optimal method which can be used as …
A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images
L Boldú, A Merino, A Acevedo, A Molina… - Computer Methods and …, 2021 - Elsevier
Background and objectives Morphological differentiation among blasts circulating in blood
in acute leukaemia is challenging. Artificial intelligence decision support systems hold …
in acute leukaemia is challenging. Artificial intelligence decision support systems hold …
Deep learning approach to peripheral leukocyte recognition
Q Wang, S Bi, M Sun, Y Wang, D Wang, S Yang - PloS one, 2019 - journals.plos.org
Microscopic examination of peripheral blood plays an important role in the field of diagnosis
and control of major diseases. Peripheral leukocyte recognition by manual requires medical …
and control of major diseases. Peripheral leukocyte recognition by manual requires medical …
EEG classification of driver mental states by deep learning
Driver fatigue is attracting more and more attention, as it is the main cause of traffic
accidents, which bring great harm to society and families. This paper proposes to use deep …
accidents, which bring great harm to society and families. This paper proposes to use deep …
An automatic nucleus segmentation and CNN model based classification method of white blood cell
White blood cells (WBCs) play a remarkable role in the human immune system. To diagnose
blood-related diseases, pathologists need to consider the characteristics of WBC. The …
blood-related diseases, pathologists need to consider the characteristics of WBC. The …
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 …
AdaEn-Net: An ensemble of adaptive 2D–3D Fully Convolutional Networks for medical image segmentation
MB Calisto, SK Lai-Yuen - Neural Networks, 2020 - Elsevier
Abstract Fully Convolutional Networks (FCNs) have emerged as powerful segmentation
models but are usually designed manually, which requires extensive time and can result in …
models but are usually designed manually, which requires extensive time and can result in …