Automated Digital Cytomorphology
Automated Digital Cytomorphology - Related Videos
08:25
Workflow for Automated Digital Peripheral Blood and Bone Marrow Cytomorphology, With Consideration of Critical Cellular Misclassifications
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2026
The workflow of automated digital cytomorphology of peripheral blood and bone marrow is described. After standardized smear preparation and staining, a scanner captures specimen images. AI-powered software locates, records, and preliminarily classifies nucleated cells, followed by expert review. The focus is on critical cellular misclassifications with potential for misdiagnosis.
10:55
Digital Microfluidics for Automated Proteomic Processing
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Cited by 30 •
2009
Digital Microfluidics is a technique characterized by the manipulation of discrete droplets (~nL - mL) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. Here, we report a platform capable of automating several proteomic processing steps.
11:41
Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales
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Cited by 61 •
2010
We have developed a computer program to analyze neuronal morphology. In combination with two existing open source analysis tools, our program performs Sholl analysis and determines the number of neurites, branch points, and neurite tips. The analyses are performed so that local changes in neurite morphology can be observed.
08:22
Electrowetting-based Digital Microfluidics Platform for Automated Enzyme-linked Immunosorbent Assay
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Cited by 11 •
2020
Electrowetting-based digital microfluidic is a technique that utilizes a voltage-driven change in the apparent contact angle of a microliter-volume droplet to facilitate its manipulation. Combining this with functionalized magnetic beads enables the integration of multiple laboratory unit operations for sample preparation and identification of pathogens using Enzyme-linked Immunosorbent Assay (ELISA).
08:06
Automated Acoustic Dispensing for the Serial Dilution of Peptide Agonists in Potency Determination Assays
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Cited by 1 •
2016
Peptide adsorption to plasticware during traditional tip-based serial dilutions can significantly impact potency determination and confound the understanding of structure-activity relationships used for lead identification and lead optimization phases of drug discovery. Here methods for automated acoustic non-contact serial dilution of peptide samples are described.
FAQs
The image-processing stage supports cell-level analysis by identifying individual cells within digitized microscopic images. It then converts each cell’s observable morphology into measurable features, including size, shape, structure, and staining characteristics. Those feature values can be reviewed individually or used to recognize cellular patterns, allowing computational analysis to operate on standardized image-derived information.
Rule-based algorithms apply predefined criteria to cellular features, whereas machine-learning algorithms classify patterns computationally. The choice affects how classification logic is expressed and evaluated. In medical workflows, either approach still requires validation and expert oversight, because automated output is intended to support interpretation rather than replace it.
Reliable results depend on specimen quality, validated algorithms, and expert oversight. Poor specimen quality can limit the usefulness of digitized cellular information, while an unvalidated algorithm may produce classifications that are not sufficiently trustworthy for interpretation. Validation and specialist review therefore provide safeguards for medical use and quality assurance.
A practical workflow begins with imaging a specimen, followed by image processing to identify cells. The system extracts morphological and staining features, applies rule-based or machine-learning classification, and presents results for expert review. This sequence creates a reproducible path from the microscopic image to cellular measurements and classified patterns, supporting routine interpretation and larger-scale review.
In medicine, the approach can support hematology and cytology workflows through cell counting, abnormality detection, and review of large specimen sets. These uses are relevant when many cells or cases must be examined consistently. The resulting image-based measurements can help organize interpretation while retaining expert involvement in the final assessment.
Beyond immediate review, automated outputs can create reproducible data for research and quality assurance. Repeated measurements and classifications provide a structured basis for examining cellular patterns across specimen sets, while quality-assurance use can help monitor consistency of the analytical process. These benefits depend on validated methods and appropriate expert interpretation.