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Cell Count

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[Flow cytometry increases the proportion of valuable samples in cerebrospinal fluid with normal cell count in malignant blood diseases].

Revista medica de Chile
BACKGROUND: The alteration of cerebrospinal fluid (CSF) in hematologic neoplasms is a poor prognostic marker. The characteristics of CSF are usually analyzed by flow cytometry or cytology. However, paucicellular CSF samples (≤5 cells/dL) can sometime...

A novel deep learning-based method for automatic stereology of microglia cells from low magnification images.

Neurotoxicology and teratology
Microglial cells mediate diverse homeostatic, inflammatory, and immune processes during normal development and in response to cytotoxic challenges. During these functional activities, microglial cells undergo distinct numerical and morphological chan...

Assessing Fuchs Corneal Endothelial Dystrophy Using Artificial Intelligence-Derived Morphometric Parameters From Specular Microscopy Images.

Cornea
PURPOSE: The aim of this study was to evaluate the efficacy of artificial intelligence-derived morphometric parameters in characterizing Fuchs corneal endothelial dystrophy (FECD) from specular microscopy images.

High cell density cultivation of Corynebacterium glutamicum by deep learning-assisted medium design and the subsequent feeding strategy.

Journal of bioscience and bioengineering
To improve the cell productivity of Corynebacterium glutamicum, its initial specific growth rate was improved by medium improvement using deep neural network (DNN)-assisted design with Bayesian optimization (BO) and a genetic algorithm (GA). To obtai...

Quality Control in the Corneal Bank with Artificial Intelligence: Comparison of a New Deep Learning-based Approach with Conventional Endothelial Cell Counting by the "Rhine-Tec Endothelial Analysis System".

Klinische Monatsblatter fur Augenheilkunde
Endothelial cell density (ECD) is a crucial parameter for the release of corneal grafts for transplantation. The Lions Eye Bank of Baden-Württemberg uses the "Rhine-Tec Endothelial Analysis System" for ECD quantification, which is based on a fixed co...

The determination of mastitis severity at 4-level using Milk physical properties: A deep learning approach via MLP and evaluation at different SCC thresholds.

Research in veterinary science
Current research aims to generate an alternative model to classical methods in the determination of subclinical mastitis at 4 levels (healthy, suspicious, subclinical, and clinical). For this purpose, multilayer perceptron (MLP) artificial neural net...

A machine-learning-based algorithm for bone marrow cell differential counting.

International journal of medical informatics
BACKGROUND: Differential counting (DC) of different cell types in bone marrow (BM) aspiration smears is crucial for diagnosing hematological diseases. However, a clinically applicable method for automatic DC has yet to be developed.

Development of a deep learning algorithm for Paneth cell density quantification for inflammatory bowel disease.

EBioMedicine
BACKGROUND: Alterations in ileal Paneth cell (PC) density have been described in gut inflammatory diseases such as Crohn's disease (CD) and could be used as a biomarker for disease prognosis. However, quantifying PCs is time-intensive, a barrier for ...

Evaluating deep learning techniques for optimal neurons counting and characterization in complex neuronal cultures.

Medical & biological engineering & computing
The counting and characterization of neurons in primary cultures have long been areas of significant scientific interest due to their multifaceted applications, ranging from neuronal viability assessment to the study of neuronal development. Traditio...