A systematic review on recent advancements in deep and machine learning based detection and classification of acute lymphoblastic leukemia
Automatic Leukemia or blood cancer detection is a challenging job and is very much
required in healthcare centers. It has a significant role in early diagnosis and treatment …
required in healthcare centers. It has a significant role in early diagnosis and treatment …
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
Recent advances of deep learning for computational histopathology: principles and applications
Simple Summary The histopathological image is widely considered as the gold standard for
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
the diagnosis and prognosis of human cancers. Recently, deep learning technology has …
Automatic white blood cell classification using pre-trained deep learning models: Resnet and inception
M Habibzadeh, M Jannesari, Z Rezaei… - … on machine vision …, 2018 - spiedigitallibrary.org
This works gives an account of evaluation of white blood cell differential counts via computer
aided diagnosis (CAD) system and hematology rules. Leukocytes, also called white blood …
aided diagnosis (CAD) system and hematology rules. Leukocytes, also called white blood …
Automatic detection and classification of leukocytes using convolutional neural networks
J Zhao, M Zhang, Z Zhou, J Chu, F Cao - Medical & biological engineering …, 2017 - Springer
The detection and classification of white blood cells (WBCs, also known as Leukocytes) is a
hot issue because of its important applications in disease diagnosis. Nowadays the …
hot issue because of its important applications in disease diagnosis. Nowadays the …
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 …
provide important information about the health status of human beings, the ratio of sub-types …
Unsupervised learning for cell-level visual representation in histopathology images with generative adversarial networks
The visual attributes of cells, such as the nuclear morphology and chromatin openness, are
critical for histopathology image analysis. By learning cell-level visual representation, we …
critical for histopathology image analysis. By learning cell-level visual representation, we …
WBC image classification and generative models based on convolutional neural network
Background Computer-aided methods for analyzing white blood cells (WBC) are popular
due to the complexity of the manual alternatives. Recent works have shown highly accurate …
due to the complexity of the manual alternatives. Recent works have shown highly accurate …
Medical hyperspectral image classification based on end-to-end fusion deep neural network
To solve the problem of supervised convolutional neural network (CNN) models suffering
from limited samples, a two-channel CNN is developed for medical hyperspectral images …
from limited samples, a two-channel CNN is developed for medical hyperspectral images …
Recognition of different types of leukocytes using YOLOv2 and optimized bag-of-features
White blood cells (WBCs) protect human body against different types of infections including
fungal, parasitic, viral, and bacterial. The detection of abnormal regions in WBCs is a difficult …
fungal, parasitic, viral, and bacterial. The detection of abnormal regions in WBCs is a difficult …