ArticlePLoS computational biology2021
Red blood cell phenotyping from 3D confocal images using artificial neural networks.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 37 citations in OpenAlex.
- Unbiased Morphometric Assessment of Red Blood Cell Storage Lesion in the Presence of Shear-Induced Stomatocytes.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2025Article
- Advances in Red Blood Cells Research.Cells · 2024Article
- Osmotic gradient ektacytometry - a novel diagnostic approach for neuroacanthocytosis syndromes.Frontiers in neuroscience · 2024Article
- Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images.Biomedical optics express · 2023Article
- Computer vision quantitation of erythrocyte shape abnormalities provides diagnostic, prognostic, and mechanistic insight.Blood advances · 2023Article
- Big Data in Transfusion Medicine and Artificial Intelligence Analysis for Red Blood Cell Quality Control.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2023Review
- Human umbilical cord blood cells suffer major modification by fixatives and anticoagulants.Frontiers in physiology · 2023Article
- SHAPR predicts 3D cell shapes from 2D microscopic images.iScience · 2022Article
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- In Vitro Erythropoiesis at Different pOCells · 2022Article
- Storage-Induced Micro-Erythrocytes Can Be Quantified and Sorted by Flow Cytometry.Frontiers in physiology · 2022Article
- Erysense, a Lab-on-a-Chip-Based Point-of-Care Device to Evaluate Red Blood Cell Flow Properties With Multiple Clinical Applications.Frontiers in physiology · 2022Article
- Structural and mechanical properties of the red blood cell's cytoplasmic membrane seen through the lens of biophysics.Frontiers in physiology · 2022Review
- Commentary: Acanthocytes identified in Huntington's disease.Frontiers in neuroscience · 2022Article
- Micro-CT for Biological and Biomedical Studies: A Comparison of Imaging Techniques.Journal of imaging · 2021Review
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- Rare Anemias: Are Their Names Just Smoke and Mirrors?Frontiers in physiology · 2021Article
Corrections and comments
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Authors and funding
10 authors at 5 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The investigation of cell shapes mostly relies on the manual classification of 2D images, causing a subjective and time consuming evaluation based on a portion of the cell surface. We present a dual-stage neural network architecture for analyzing fine shape details from confocal microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease, namely hereditary spherocytosis. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification. The results show the relation between the particular genetic mutation causing the disease and the shape profile. With the obtained 3D phenotypes, we suggest our method for diagnostics and theragnostics of blood diseases. Besides the application employed in this study, our algorithms can be easily adapted for the 3D shape phenotyping of other cell types and extend their use to other applications, such as industrial automated 3D quality control.
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