AIMC Topic: Leukocytes

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Label-Free Identification of White Blood Cells Using Machine Learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
White blood cell (WBC) differential counting is an established clinical routine to assess patient immune system status. Fluorescent markers and a flow cytometer are required for the current state-of-the-art method for determining WBC differential cou...

Machine learning algorithms for the detection of spurious white blood cell differentials due to erythrocyte lysis resistance.

Journal of clinical pathology
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...

LeukocyteMask: An automated localization and segmentation method for leukocyte in blood smear images using deep neural networks.

Journal of biophotonics
Digital pathology and microscope image analysis is widely used in comprehensive studies of cell morphology. Identification and analysis of leukocytes in blood smear images, acquired from bright field microscope, are vital for diagnosing many diseases...

Feature extraction using traditional image processing and convolutional neural network methods to classify white blood cells: a study.

Australasian physical & engineering sciences in medicine
White blood cells play a vital role in monitoring health condition of a person. Change in count and/or appearance of these cells indicate hematological disorders. Manual microscopic evaluation of white blood cells is the gold standard method, but the...

More Than Just a Removal Service: Scavenger Receptors in Leukocyte Trafficking.

Frontiers in immunology
Scavenger receptors are a highly diverse superfamily of proteins which are grouped by their inherent ability to bind and internalize a wide array of structurally diverse ligands which can be either endogenous or exogenous in nature. Consequently, sca...

Fine-grained leukocyte classification with deep residual learning for microscopic images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past developm...

Development of a Robust Algorithm for Detection of Nuclei and Classification of White Blood Cells in Peripheral Blood Smear Images.

Journal of medical systems
Peripheral Blood Smear analysis plays a vital role in diagnosis of many diseases such as leukemia, anemia, malaria, lymphoma and infections. Unusual variations in color, shape and size of blood cells indicate abnormal condition. We used a total of 11...

Computer Aided Solution for Automatic Segmenting and Measurements of Blood Leucocytes Using Static Microscope Images.

Journal of medical systems
Blood leucocytes segmentation in medical images is viewed as difficult process due to the variability of blood cells concerning their shape and size and the difficulty towards determining location of Blood Leucocytes. Physical analysis of blood tests...

Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception.

Journal of healthcare engineering
This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucleated cell usually stained that is salient obviously, the proposed method is suitable to segment nuc...

Monitoring bottlenose dolphin leukocyte cytokine mRNA responsiveness by qPCR.

PloS one
Both veterinarians caring for dolphins in managed populations and researchers monitoring wild populations use blood-based diagnostics to monitor bottlenose dolphin (Tursiops truncatus) health. Quantitative PCR (qPCR) can be used to assess cytokine tr...