Deep learning for the detection of acute lymphoblastic leukemia subtypes on microscopic images: A systematic literature review
Computer vision research in detecting and classifying the subtype Acute Lymphoblastic
Leukemia (ALL) has contributed to computer-aided diagnosis with improved accuracy …
Leukemia (ALL) has contributed to computer-aided diagnosis with improved accuracy …
Morphology-based deep learning enables accurate detection of senescence in mesenchymal stem cell cultures
L He, M Li, X Wang, X Wu, G Yue, T Wang, Y Zhou… - BMC biology, 2024 - Springer
Background Cell senescence is a sign of aging and plays a significant role in the
pathogenesis of age-related disorders. For cell therapy, senescence may compromise the …
pathogenesis of age-related disorders. For cell therapy, senescence may compromise the …
An effective WBC segmentation and classification using MobilenetV3–ShufflenetV2 based deep learning framework
White Blood Cells are essential in keeping track of a person's health. However, the
pathologist's experience will determine how the blood smear is evaluated. Furthermore, it is …
pathologist's experience will determine how the blood smear is evaluated. Furthermore, it is …
Biomedical Image Segmentation: A Systematic Literature Review of Deep Learning Based Object Detection Methods
Biomedical image segmentation plays a vital role in diagnosis of diseases across various
organs. Deep learning-based object detection methods are commonly used for such …
organs. Deep learning-based object detection methods are commonly used for such …
StainGAN: Learning a structural preserving translation for white blood cell images
Abstract Analysis of white blood cells in blood smear images plays a vital role in computer‐
aided diagnosis for the analysis and treatment of many diseases. However, different …
aided diagnosis for the analysis and treatment of many diseases. However, different …
Robust detection and refinement of saliency identification
Salient object detection is an increasingly popular topic in the computer vision field,
particularly for images with complex backgrounds and diverse object parts. Background …
particularly for images with complex backgrounds and diverse object parts. Background …
ResNeXt-CC: a novel network based on cross-layer deep-feature fusion for white blood cell classification
Y Luo, Y Xu, C Wang, Q Li, C Fu, H Jiang - Scientific Reports, 2024 - nature.com
Accurate diagnosis of white blood cells from cytopathological images is a crucial step in
evaluating leukaemia. In recent years, image classification methods based on fully …
evaluating leukaemia. In recent years, image classification methods based on fully …
A lightweight white blood cells detection network based on CenterNet and feature fusion modules
L Wu, Y Zou, C Zuo, L Chen, B Zhou… - Measurement Science …, 2024 - iopscience.iop.org
White blood cells (WBCs) detection is significant to the diagnosis of many diseases.
However, the detection accuracy can be influenced by the significant differences in color …
However, the detection accuracy can be influenced by the significant differences in color …
[HTML][HTML] Parallel attention multi-scale mandibular fracture detection network based on CenterNet
T Zhou, Y Du, J Mao, C Peng, H Wang… - … Signal Processing and …, 2024 - Elsevier
Objective Using the target detection methods to assist in detecting the fracture sites can
provide corresponding treatment information to doctors. However, there are great variance …
provide corresponding treatment information to doctors. However, there are great variance …
Multiclass Classification of Heterogeneous Blood Cells Using Deep Learning and contourlet Transform
O Eslamifar, M Soltani, MJR Fatemi - 2024 - researchsquare.com
The classification of human blood cells is very important in the diagnosis of inflammation,
infection and blood disorders such as leukemia. Diagnosis of blood malignancies requires …
infection and blood disorders such as leukemia. Diagnosis of blood malignancies requires …