About App
Accelerating Blood Cell Diagnosis with Intelligent Automation
Our AI-powered app has revolutionized blood cell analysis by integrating advanced artificial intelligence and machine learning technologies into diagnostic workflows. Designed for modern laboratories, the app automatically identifies and classifies blood cells from microscopic images, providing fast, accurate, and consistent results. By reducing manual efforts and human errors, it increases clinical accuracy and streamlines hematological assessment.
The Challenges
Microscope images often vary in light, focus, and resolution, making it difficult to see and analyze blood cells.
Red blood cells overlap or cluster at the same time, complicating the separation of cells individually and the counts.
The difference in staining techniques causes variation in cell color and appearance, challenging reliable identity.
Expert labeling of thousands of cells per picture is labor-intensive and breaks the diagnostic process.
Unusual or unusual cells can be similar to ordinary people, making them easier to ignore during manual examination.
Differences in microscope, camera, and sample preparation methods create incompatible images that eliminate clinical reliability.
The Solutions We Offered
Our AI engine improves the quality of medical imaging by adjusting lighting and focus issues, ensuring clearer visualization of blood cells for reliable analysis.
Machine learning algorithms accurately separate overlapping and clustered cells, enabling precise blood cell analysis even in dense samples.
The system applies stain normalization and color correction methods to handle variability in staining, supporting hematology diagnostics across different lab settings.
Artificial intelligence automates cell labeling by detecting and classifying thousands of cells per image, speeding up diagnostics and reducing human effort.
Integrated anomaly detection models highlight unusual or abnormal cells, enhancing sensitivity in hematology and improving early disease detection.
Designed for varied equipment and lab environments, our AI development services support telehealth apps, enabling remote blood cell analysis and expert consultation.
Key Features
AI-Powered Blood Cell Detection
Utilizes advanced deep learning (YOLOv8) for accurate identification of red blood cells, white blood cells, and platelets in microscopic images.
Real-Time Cell Counting with JSON Report
Automatically generates a structured JSON output with precise counts of each cell type, enabling quick and reliable hematology assessments.
Annotated Image Output for Visual Validation
Provides the original image with labeled bounding boxes, helping users visually confirm detections and facilitating transparent, explainable results.
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Contact UsThe Results We Delivered
Here are the key results our system achieved through intelligent automation. These results show average improvement in speed, accuracy, and clinical efficiency.
Improved Diagnostic Accuracy
Detection of consistent and objective cells reduces human error and increases the reliability of blood analysis.
Time and Labor Efficiency
Automation saves time and enables laboratories to handle multiple samples in a short time.
Structured and Scalable Reporting
JSON-based reports support easy integration with lab systems and scalability across clinical settings.
Enhanced Telehealth & Remote Diagnostics
Enables remote blood analysis and expert review through accessible, standardized digital outputs.