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Blood Cells

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[Chinese expert consensus on the technical and clinical practice specifications of artificial intelligence assisted morphology examination of blood cells (2024)].

Zhonghua xue ye xue za zhi = Zhonghua xueyexue zazhi
Blood cell morphological examination is a crucial method for the diagnosis of blood diseases, but traditional manual microscopy is characterized by low efficiency and susceptibility to subjective biases. The application of artificial intelligence (AI...

ReRNet: A Deep Learning Network for Classifying Blood Cells.

Technology in cancer research & treatment
AIMS: Blood cell classification helps detect various diseases. However, the current classification model of blood cells cannot always get great results. A network that automatically classifies blood cells can provide doctors with data as one of the c...

Expert knowledge for the recognition of leukemic cells.

Applied optics
This work shows the advantage of expert knowledge for leukemic cell recognition. In the medical area, visual analysis of microscopic images has regularly used biological samples to recognize hematological disorders. Nowadays, techniques of image reco...

Blood Cell Classification Based on Hyperspectral Imaging With Modulated Gabor and CNN.

IEEE journal of biomedical and health informatics
Cell classification, especially that of white blood cells, plays a very important role in the field of diagnosis and control of major diseases. Compared to traditional optical microscopic imaging, hyperspectral imagery, combined with both spatial and...

Recognition of peripheral blood cell images using convolutional neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Morphological analysis is the starting point for the diagnostic approach of more than 80% of hematological diseases. However, the morphological differentiation among different types of normal and abnormal peripheral blood c...

Learning Single-Cell Distances from Cytometry Data.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric, a function that quantif...

Live remote digital microscopy in peripheral blood smear evaluation: Intraobserver concordance and experience.

International journal of laboratory hematology
INTRODUCTION: Peripheral blood smear (PBS) review is a routine laboratory test which requires pathologist's interpretation when abnormal indices, atypical cells, or critical findings are identified. Real-time remote digital microscopy (DM) can potent...

Structured Pyramidal Neural Networks.

International journal of neural systems
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper prop...

Image processing and machine learning in the morphological analysis of blood cells.

International journal of laboratory hematology
INTRODUCTION: This review focuses on how image processing and machine learning can be useful for the morphological characterization and automatic recognition of cell images captured from peripheral blood smears.

Comparison of the solid phase and liquid-liquid extraction methods for methadone determination in human serum and whole blood samples using gas chromatography/mass spectrometry.

Arhiv za higijenu rada i toksikologiju
The aim of this study was to determine the optimal biological sample and the optimal extraction technique for monitoring methadone concentrations in biological samples. We analysed methadone in serum and whole blood samples using gas chromatography/m...