AVE 2000 Automated Hematology Morphology Analysis System

Specification

Manufacturer

AVE

SKU: Z764M06391 Categories: , , Brand:

Description

Testing items

White Blood Cells (WBC)

  • Divided into neutrophils, lymphocytes, monocytes, eosinophils, and basophils.
  • The system calculates the percentage of each cell type.
  • Can pre-classify abnormal white blood cells and immature granulocytes.

Platelets (PLT)

  • Categorized into:
    • Normal platelets
    • Large/giant platelets
    • Platelet aggregates
  • Alerts if platelet aggregation exceeds a preset warning value.

Red Blood Cells (RBC)

  • Classified into:
    • Normal RBCs
    • Large RBCs
    • Small RBCs
    • Spherical RBCs
    • Target-shaped RBCs
    • Other forms
  • Calculates the proportion of each cell type.
  • Provides descriptions of RBC morphology.
  • Pre-classifies immature RBCs.

Parasites

  • Detects blood parasites such as:
    • Plasmodium
    • Dirofilaria immitis
    • Trypanosoma
    • Leishmania, etc.
  • Alerts for infections.

Reclassification

  • After manual review, the system allows for:
    • Reclassification of misclassified cells.
    • Identification of previously unidentified cells.

Detection Principle

Slide Preparation Module

  • Automatically adjusts slide preparation settings based on hematology analyzer HCT (hematocrit) results.
  • Simulates manual slide preparation to enhance automation and efficiency in blood slide processing.
  • Transfers prepared slides for staining using the Romanowsky-Giemsa method via a column infiltration staining module.

Microscopy Module

  • Employs artificial intelligence (AI) and machine vision technology for precise blood cell analysis.
  • Uses specific algorithms and big data processing to intelligently identify, classify, and count different blood cell types and components.
  • Enhances diagnostic accuracy through automated detection and classification mechanisms.

Product feature detail diagram

Product Features

Advanced Slide Preparation and Staining Technologies in Hematology

Automatic Slide Preparation: Adjusts slide preparation settings based on hematology analyzer HCT results, simulating manual techniques to achieve fully automated blood slide preparation.

Column Immersion Staining: Applies Wright-Giemsa stain using a column immersion module, ensuring minimal dye consumptionno residue accumulation, and zero cross-contamination.

Staining Workflow:

  • Place slide
  • Add blood
  • Adjust slide preparation settings
  • Slide transfer
  • Automatic staining
  • Constant temperature and flow drying
  • Store slides in a slide basket

Innovative Technologies

  • Single-Use Composite Slide Preparation Belt: Features a disposable belt with a sapphire push head, eliminating the need for cleaning and preventing cross-contamination.
  • Multi-Setting Slide Preparation: Automatically adjusts angle, speed, pressure, and blood drop extension time based on HCT values, ensuring high-quality smears.
  • Slide Drying: Uses constant temperature and airflow for automatic drying, making slides immediately ready for observation.
  • AVE-26 Series Analyzer: A fully automated blood cell morphology analyzer that integrates AI and machine vision for precise identification, classification, and counting of blood components.

Enhancing Hematological Diagnostics with AI and Machine Vision

AI-Powered Recognition & Classification: Leverages artificial intelligence and machine vision, applying specialized algorithms and big data analysis to intelligently recognize, classify, and count blood cells and other components with high accuracy.

Detection Process:

  1. Place stained slide on the microscope stage.
  2. Scan at low magnification to locate target cells.
  3. Apply immersion oil to the slide.
  4. Switch to oil immersion lens (typically 100x) for high-resolution imaging.
  5. Capture and analyze images, followed by automated classification and counting.
  6. Generate a comprehensive diagnostic report with visual and quantitative data.

This streamlined process ensures precision and efficiency in hematological diagnostics.

Enhancing Hematology Workflow with Automated Cell Identification

Low-Magnification (X10) Intelligent Scanning and Target Location: Performs a comprehensive full-slide scan at 10x magnification to identify optimal regions for cell morphology observation.

Targeted Nucleated Cell Analysis: Automatically locates and prioritizes nucleated cells for high-resolution examination, ensuring efficient and focused diagnostic evaluation.

Enhanced Workflow Efficiency: This intelligent scanning approach streamlines the transition to high-magnification imaging, reducing manual effort and improving diagnostic accuracy.

This feature is especially valuable in hematology workflows, where precise identification of nucleated cells is critical for differential counts and morphological assessments.

Smart Recognition and Adaptation: Enhancing Hematological Diagnostics

Automated Recognition Under Oil Immersion: Accurately identifies and classifies blood components at 100x magnification, leveraging AI and machine vision for high-resolution analysis.
Suspicious Target Flagging: Intelligently detects atypical or borderline cells, prompting expert review to ensure diagnostic precision.
Continuous Learning: The system updates its recognition database with new parameters and verified cases, enhancing accuracy and adaptability over time.

Advanced RBC Morphology Analysis for Anemia Diagnosis

Red Blood Cell Morphology Analysis: Classifies RBCs by size, shape, staining, and structural features, calculates distribution percentages, and supports anemia diagnosis. Visual outputs include morphology charts and scatter diagrams for intuitive interpretation.

Oil Immersion (X100) Intelligent Tracking and Image Capture: Ensures high-speed, high-resolution detection by capturing targeted cells under oil immersion, minimizing the risk of missed or overlooked cells.

Granulocyte Nucleus Morphology Analysis: Differentiates neutrophils into band and segmented forms, calculates nuclear distribution percentages, and flags shifts in nuclear morphology, aiding in the assessment of inflammatory or hematologic conditions.

Precision in Platelet Quantification: From Manual Counting to AI Integration

Platelet Morphology Analysis: Evaluates platelet size, shape, and granularity, identifying abnormalities such as giant platelets, hypo- or hypergranulation, and irregular contours, which may indicate underlying hematologic conditions.

Distribution & Aggregation Assessment: Observes platelet dispersion across the smear and detects clumping or aggregation patterns, which can affect automated counts and signal disorders like pseudothrombocytopenia.

Morphology Curve Visualization: Generates a platelet morphology curve to graphically represent size distribution, aiding in the interpretation of platelet population heterogeneity.

Platelet Estimation Box: Utilizes a designated estimation zone to manually count platelets under oil immersion (typically 100x), correlating with automated counts and supporting accurate platelet quantification, especially in cases of flagged or abnormal results.