Computer Vision in Medical Devices

Ensure Manufacturing Quality by Detecting Defective Medical Devices with Akridata

Undetected device defects cost medical device manufacturers billions of dollars each year. Use Akridata Inspection Studio to build, test, and deploy high-accuracy computer vision models that keep both patients and profits healthy.

There were 975 medical device recalls in the United States in 2023, resulting in 283 million recalled units as well as significant financial and reputation loss.

Manual inspection processes simply don’t provide the level of consistency needed to meet strict industry standards. But manufacturers are struggling to implement effective computer vision systems and often lack the image data needed to train their inspection models.

SOLUTION

Reliable Device Defect Detection

Goal

Improve the Precision and Reliability of Automated Vision Systems to Prevent Defect Escapes and Faulty Shipments.

Problem

Manual device inspections are susceptible to human error, and classical vision systems that are rule-based don’t yield well for process variations. As a result, defective devices end up in patients’ hands.

Solution

Leverage Akridata’s Inspection Studio to build and deploy reliable inspection models that are based on state-of-the-art deep learning and transformer architectures. Can work with your existing hardware.

See how Akridata can help.

HOW IT WORKS

Integrated Device Inspection System

Image Data Collection

As a hardware-free solution, Inspection Studio serves as an added intelligence layer to help you make better inspection decisions. The software collects data from the image database associated with your current vision system and can be easily customized to match your specific environment.

Advanced Device Inspection

Using deep learning AI models and batch-based analysis, Inspection Studio detects even the most subtle variations in device construction, catching defects earlier in the production process. The model can also verify that each device has the necessary manufacturer marks and/or ID numbers.

Defect Categorization and Decision

Inspection Studio determines whether identified irregularities are acceptable cosmetic variations or unacceptable functional defects that could negatively impact device performance. Model data can also help identify the root cause of defects in order to implement corrective procedures.

Continuous Deployment and Monitoring

The vision model continues to update and improve itself with every inspected image, delivering consistently reliable results without the fatigue factor of human inspection. It reduces manufacturing bottlenecks and can be easily scaled across multiple production facilities.

Need More?

Akridata Edge Data Platform

Don’t have an in-house Data Science team for device defect detection?

Akridata Edge provides ready-to-use medical device models that have been rigorously tested and refined using millions of device images, ensuring accurate defect detection.

Customer spotlight

Medical Device Manufacturer Decreased False Positives by 40%

A medical device client sought to improve accuracy and efficiency in its computer vision-based inspection lines. The company's existing system fell short despite repeated model tuning. Real-world production conditions and a rigid, speed-focused approach caused incorrect part flagging, posing the challenge of maintaining speed without sacrificing accuracy or risking defective product shipments.

Leveraging Akridata Inspection Studio, the company achieved a 40% decrease in false positives and a 30% reduction in false negatives, significantly reducing inventory wastage and safeguarding the brand’s esteemed reputation.