BoryLabQC Solution

BoryLabQC Solution | Bory AI Unsuitable Specimen Classification Solution |

An AI specimen quality management solution that analyzes specimen images and laboratory data to identify unsuitable specimens and support quality control operations in diagnostic laboratories

 

BoryLabQC Solution is an AI-based specimen quality classification solution built to analyze specimen conditions and determine whether specimens are unsuitable based on specimen images and laboratory operations data generated in diagnostic laboratories.

 

Diagnostic laboratories may encounter various unsuitable-specimen issues, including insufficient specimen volume, hemolysis, icterus, lipemia, labeling errors, poor barcode readability, container abnormalities, and specimen-type mismatches. These specimen quality problems can lead to testing delays, recollection, retesting, potential result errors, and increased laboratory workload.

 

BoryLabQC Solution is tailored to each customer's laboratory environment and includes specimen image analysis, image preprocessing, specimen-region recognition, label and barcode verification, unsuitable-specimen classification algorithms, a laboratory operations dashboard, middleware integration, and LIS/TLA integration.

 

Rather than selling a specific piece of equipment, this solution is an implementation-focused solution centered on Bory-developed AI specimen classification software, image processing, laboratory data integration, web server and database, administrator dashboard, and Hybrid Web/App operations interface.

 

[Solution Adoption Inquiry][AI Unsuitable Specimen Classification Consultation][Diagnostic Laboratory PoC Inquiry][Request a Proposal]

Customer Challenges

 

Unsuitable specimen checks occur repeatedly

Diagnostic laboratories must repeatedly check for unsuitable specimens during accessioning, preprocessing, analysis, and post-processing.

Issues such as insufficient specimen volume, suspected hemolysis, suspected icterus, suspected lipemia, labeling errors, and barcode recognition errors often depend on visual inspection and staff experience.

BoryLabQC Solution analyzes specimen images with AI to assist unsuitable-specimen classification and helps staff quickly identify specimens requiring review.

 

It is difficult to apply specimen quality criteria consistently

Specimen assessment may vary depending on staff experience, workload, lighting conditions, imaging conditions, and laboratory standards.

BoryLabQC Solution applies image-analysis algorithms and institution-specific criteria to systematize specimen quality assessment and improve consistency in quality control standards.

 

It is difficult to manage unsuitable specimen occurrence data

Even when unsuitable specimens occur, laboratory operations are difficult to improve unless counts by type, time-based status, equipment-level processing status, and retest or recollection status are systematically managed.

BoryLabQC Solution stores classification results and processing histories in a database and supports dashboard monitoring of unsuitable specimen occurrences.

 

Specimen images and laboratory operations data are separated

Specimen images are often stored on imaging devices or equipment, test orders and specimen IDs are held in the LIS or middleware, and processing status is managed in separate systems.

BoryLabQC Solution connects specimen images, specimen IDs, barcodes, test orders, classification results, and processing status in a single workflow linked to laboratory quality control operations.

 

AI classification must be added to existing laboratory automation systems

Institutions already operating an LIS, TLA, analyzers, pre-analytical equipment, post-analytical equipment, and laboratory middleware need to add AI classification capabilities rather than replace their existing systems.

BoryLabQC Solution can integrate with BoryLabLink Solution or the customer's existing middleware so that unsuitable-specimen classification results are reflected in laboratory workflows.

 

Solution Overview

BoryLabQC Solution is a diagnostic laboratory quality management solution that combines AI analysis of specimen images with laboratory operations data integration.

 

Key functions include:

• Specimen image input and collection
• Specimen image preprocessing
• Specimen-region recognition
• Analysis of insufficient specimen volume
• Analysis of suspected hemolysis, icterus, and lipemia
• Label and barcode status verification
• Specimen container condition verification
• Unsuitable specimen type classification
• Storage and retrieval of classification results
• Laboratory quality management dashboard implementation
• LIS, TLA, and middleware integration
• BoryLabLink Solution integration
• Retest and recollection status integration
• Unsuitable specimen statistical report generation
• On-premises deployment on the hospital internal network

 

Key Features

 

1. Specimen Image-Based Quality Classification

BoryLabQC Solution uses AI to analyze specimen images and determine specimen condition and possible quality abnormalities.

Analysis targets can include specimen volume, color, layer separation, turbidity, label position, barcode visibility, and container condition—items considered important in laboratory operations.

 

2. Unsuitable Specimen Type Classification

Unsuitable specimen types can be classified according to laboratory operating standards.

For example, the following types can be configured:

• Insufficient specimen volume
• Suspected hemolysis
• Suspected icterus
• Suspected lipemia
• Labeling error
• Poor barcode readability
• Specimen container abnormality
• Specimen-type mismatch
• Specimen requiring recheck

Classification items can be adjusted according to each institution's testing standards and workflows.

 

3. Specimen Image Preprocessing

BoryLabQC Solution preprocesses captured specimen images into a form suitable for analysis.

It prepares the base data for AI classification by applying lighting correction, specimen-region extraction, background removal, color correction, container-region separation, label-region separation, and barcode-region detection.

 

4. Specimen Region, Label, and Barcode Analysis

The actual specimen region inside the container can be distinguished from the label and barcode regions for analysis.

Insufficient specimen volume, label attachment status, barcode readability, and external container condition can be used as laboratory quality management items.

 

5. Classification Result Review Screen

Laboratory staff can view specimen images, AI classification results, unsuitable specimen type, confidence score, specimen ID, accession time, and processing status on a web or administrator screen.

The system can be configured so staff review the AI's initial classification and, when necessary, mark the case as confirmed, on hold, retest requested, or recollection requested.

 

6. Laboratory Operations Dashboard

Administrators can use the dashboard to view unsuitable specimen occurrences, rates by type, time-based trends, equipment-level processing status, and retest or recollection status.

Statistical screens and reporting functions can be configured for laboratory quality management, operational improvement, and internal reporting.

 

7. LIS, TLA, and Middleware Integration

BoryLabQC Solution can integrate with the customer's LIS, TLA, laboratory middleware, analyzers, and pre-analytical equipment.

Specimen IDs, barcodes, test orders, classification results, and processing status are integrated so unsuitable-specimen results are reflected in laboratory workflows.

 

8. BoryLabLink Solution Integration

BoryLabQC Solution can integrate with BoryLabLink Solution and expand into an integrated diagnostic laboratory operations architecture.

Unsuitable-specimen results can be sent to BoryLabLink middleware and linked to laboratory processes for retesting, recollection, holding, or required review.

 

9. Hybrid Web/App Operations Interface

PC web, tablet, and mobile interfaces can be configured according to the laboratory environment.

Specimen result review, unsuitable specimen list lookup, processing status changes, dashboard viewing, and report lookup can be provided through a Hybrid Web/App interface.

 

10. Hospital Internal Network Deployment

The solution can be deployed on a hospital internal network or closed network to protect patient information and laboratory data.

Servers, databases, AI classification modules, dashboards, user access control, and log management are configured according to hospital security policies.

 

Available Deployment Configurations

 

Basic Deployment Configuration

• Specimen image input module
• Image preprocessing module
• Specimen-region analysis module
• Label and barcode region analysis module
• Unsuitable specimen classification algorithm
• Classification result database
• Specimen classification result lookup screen
• Administrator dashboard
• Unsuitable specimen statistics screen
• User access control

 

Extended Deployment Configuration

• Specimen imaging device integration
• Existing laboratory equipment image integration
• LIS integration
• TLA system integration
• BoryLabLink middleware integration
• Retest and recollection status management
• Test order data integration
• Equipment-level processing status integration
• Unsuitable specimen report generation
• Hybrid Web/App operations interface
• On-premises deployment on the hospital internal network
• Institution-specific classification criteria customization
• External laboratory operations system API integration
• Automated laboratory quality management report generation

 

Application Scenarios

 

Unsuitable Specimen Classification in Diagnostic Laboratories

Specimen images received or preprocessed in a diagnostic laboratory can be analyzed to perform an initial assessment of specimen suitability.

Staff can review AI results and decide whether retesting, recollection, holding, or further confirmation is required according to institutional criteria.

 

Pre-Analytical Specimen Quality Management

The solution can be used as a quality management system to check specimen volume, container condition, label condition, and barcode status during pre-analytical processing.

Early identification before an unsuitable specimen reaches the analytical stage helps reduce testing delays and workflow confusion.

 

Enhancement of Laboratory Automation Systems

AI specimen classification can be added to existing laboratory automation systems through integration with the LIS, TLA, analyzers, pre-analytical equipment, and laboratory middleware.

Image-based quality management capabilities can be expanded while retaining existing systems.

 

Retest and Recollection Management

Specimens requiring retesting or recollection due to insufficient volume, suspected hemolysis, labeling errors, barcode errors, or similar issues can be quickly classified and managed.

Storing classification results and processing history supports retest management and analysis of testing delays.

 

Laboratory Quality Management Dashboard

Laboratory managers can view unsuitable specimen counts, rates by type, time-based occurrence status, processing status, and equipment-level processing status on a dashboard.

The data can support quality management meetings, internal reporting, and workflow improvement.

 

Enhanced Operations for Reference Laboratories and Testing Centers

For reference laboratories and testing centers processing large specimen volumes, specimen quality classification and processing status management are critical.

BoryLabQC Solution can systematically manage large volumes of specimen images and classification results and improve laboratory operating efficiency.

 

Expected Benefits

 

Improved Efficiency of Unsuitable Specimen Checks

A workflow in which AI performs an initial analysis of specimen images and staff review the results can reduce repetitive visual inspection.

 

Early Identification of Testing Delay Factors

Problems that may cause testing delays—such as insufficient volume, suspected hemolysis, labeling errors, and poor barcode readability—can be identified early.

 

Consistent Quality Management Standards

Institution-specific criteria can be reflected in the AI model and operations interface to reduce variation among staff decisions and improve consistency in quality management.

 

Accumulation of Laboratory Operations Data

Unsuitable specimen type, occurrence time, processing status, retest status, and equipment-level processing information can be stored and used for laboratory operations analysis.

 

Enhancement of Existing Systems

Adding AI specimen quality classification to existing LIS, TLA, middleware, and dashboard environments can raise the level of laboratory automation.

 

Stronger Laboratory Quality Management Reporting

Reports on unsuitable specimen occurrences and processing history can support internal reporting, quality management, and workflow improvement.

 

Implementation Process

 

1. Requirements Review

We review the customer's specimen types, unsuitable-specimen criteria, imaging environment, laboratory system configuration, systems to be integrated, and security policies.

 

2. Specimen Image and Data Analysis

We analyze specimen image quality, imaging angle, lighting, container types, label positions, barcode status, existing classification criteria, and data volume.

 

3. Classification Item Definition

Institution-specific classification items are defined, such as insufficient specimen volume, suspected hemolysis, suspected icterus, suspected lipemia, labeling errors, and poor barcode readability.

 

4. PoC Implementation

Using selected specimen images and operations data, we verify AI classification feasibility, result screens, dashboard functions, and middleware integration feasibility.

 

5. AI Classification Model and System Implementation

Image preprocessing, specimen-region analysis, unsuitable-specimen classification algorithms, and result storage structures are built according to customer data and classification criteria.

 

6. Laboratory System Integration

The solution is integrated with the LIS, TLA, BoryLabLink, existing middleware, and laboratory operations systems so classification results are reflected in workflows.

 

7. Operational Validation and Enhancement

Using actual laboratory operations data, we improve classification criteria, screen configuration, alert thresholds, report formats, and processing status management.

 

What BoryLabQC Solution Can Deliver

 

• AI unsuitable specimen classification system implementation
• Specimen image-based quality classification
• Analysis of insufficient specimen volume
• Analysis of suspected hemolysis, icterus, and lipemia
• Label condition verification
• Barcode readability verification
• Specimen container condition verification
• Unsuitable specimen type classification
• Classification result lookup screen implementation
• Laboratory quality management dashboard implementation
• Unsuitable specimen statistical report generation
• Retest and recollection target management integration
• LIS, TLA, and middleware integration
• BoryLabLink Solution integration
• AI classification system deployment on a hospital internal network
• Hybrid Web/App operations interface
• Laboratory operations data integration
• Institution-specific classification criteria customization

 

Adoption Inquiries

 

BoryLabQC Solution can be proposed as a PoC, standalone classification system, middleware-integrated system, internal-network deployment, or institution-specific implementation according to the hospital or testing institution's specimen types, imaging environment, classification criteria, laboratory system architecture, and security policies.

• Inquiry About Adopting the AI Unsuitable Specimen Classification Solution
• Inquiry About an AI Quality Management System for Diagnostic Laboratories
• Specimen Image Analysis PoC Inquiry
• Inquiry About Detecting Insufficient Volume and Suspected Hemolysis
• Label and Barcode Status Analysis Inquiry
• Laboratory Quality Management Dashboard Implementation Inquiry
• LIS, TLA, and Middleware Integration Inquiry
• BoryLabLink Integration Inquiry
• Hospital Internal Network On-Premises Deployment Inquiry
• Institution-Specific Classification Criteria Customization Inquiry
• Request a Proposal

 

Important Information

 

BoryLabQC Solution is an AI-based specimen quality classification solution designed to assist specimen quality management operations in diagnostic laboratories.

This solution supports unsuitable-specimen classification based on specimen images and laboratory data and is not presented as a medical device for disease diagnosis, treatment, or prevention.

 

AI classification results are reference information that supports laboratory staff decisions. Final specimen suitability decisions and follow-up actions must be performed according to the institution's laboratory operating standards and staff verification procedures.

Analysis performance and implementation methods may vary depending on specimen image quality, imaging angle, lighting, container type, label condition, barcode position, specimen type, and institution-specific classification criteria.

 

When integrated with hospital data such as patient information, test orders, and specimen IDs, prior consultation is required regarding personal data protection, medical information security, hospital internal network policies, and data storage and transmission standards.

 

Before adoption, the specimen types, imaging environment, classification items, unsuitable-specimen criteria, integrated systems, server configuration, and personal data processing standards must be reviewed in advance.

 

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BORY.ai Key Services Overview

Bory Co., Ltd. develops products, solutions, platforms, and services for industrial, medical, public-sector, healthcare, and barrier-free applications based on AI technologies involving speech, language, video, sensors, and data.

Below are the main representative domains currently operated or being prepared by Bory Co., Ltd. 

 

Primary Domain	Service/Brand	Description
bory.ai	BORY.ai	The official AI brand website of Bory Co., Ltd., serving as the company’s main website for the integrated presentation of its products, solutions, platforms, and services
borysense.com	BORY SENSE	An AI-powered hearing assistance platform that supports communication for people with hearing disabilities and older adults through real-time captioning, lip-reading AI, and AR glasses integration
borytalk.com	BORY TALK	A web-based conversational AI chatbot service designed for civil service inquiries, consultations, information guidance, and customer support
borykiosk.com	BORY KIOSK	A barrier-free AI kiosk service for older adults and people with disabilities, featuring voice guidance, captioning, and easy-to-use interfaces
boryservice.com	BORY SERVICE	A service portal introducing Bory’s AI services and custom-built AI offerings for industrial, public-sector, and everyday applications
borysong.com	BORY SONG	A music AI service that supports AI-powered composition, music generation, and sound content production