Vendor source

Reviewed 28 May 2026

Completeness Strong (67%)

JLD-01K

JLK Inc.

JLD-01K is based on the Convolutional Neural Network (CNN), a type of deep learning model, that detects nodules in pulmonary CT images. Measure the diameter and volume of the nodules found, proceed quantitatively, categorize the LungRADs category, and specify the total number of nodules per patient. In addition, 2D views of Axial, Coronal, Sagittal, etc. are provided through the web-based UI, and lungs and nodules are visualized and displayed through 3D views.

Supported by 1 paper

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Key Features

  • Lung nodules detection and quantification
  • LungRADs categorization
  • Report generation
  • Vancouver Risk calculator

General Information

Product name

JLD-01K

Company

Modality

CT

Main task

Not specified

Subspeciality

Chest

Disease targeted

Lung cancer

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class I

Verified by Health AI Register

Other certifications

Not specified

Technical Specifications

Patient population age

Not specified

Input

Lung CT

Input format

DICOM, JPG

Output

Location annontation, nodule diameter and volume, LungRADs category, Vancouver Risk Calculator

Output format

Report, UI

Integration

Stand-alone third party application

Deployment

Cloud-based, Hybrid solution, Locally on dedicated hardware

Trigger for analysis

On demand, triggered by a user through e.g. a button click, image upload

Processing time

< 10 seconds

Population

All chest CT

Market Presence

On market since

09-2019

AI Platforms

Resellers

Not specified

Countries present

3

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of installations, Number of users

Source: Vendor | First published: Jul 1, 2020 | Last updated: May 28, 2026

JLD-01K - JLK Inc.