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Auto Lung Nodule Detection
Auto Lung Nodule Detection
Samsung Healthcare
**Only available with Samsung Electronics systems.**
For Auto Lung Nodule Detection multiple deep learning algorithms help predict lung nodule in general chest radiography as a second reader.
Information source:
Vendor
Last updated:
Oct. 28, 2021
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
Auto Lung Nodule Detection
Company
Samsung Healthcare
Subspeciality
Chest
Modality
X-ray
Disease targeted
Lung cancer
Key-features
Lung nodule detection
Suggested use
During: interactive decision support (shows abnormalities/results only on demand)
After: diagnosis verification
Technical Specifications
Data characteristics
Population
Input
Chest X-ray
Input format
DICOM
Output
annotation overlay
Output format
DICOM
Technology
Integration
Stand-alone third party application
Deployment
Locally virtualized (virtual machine, docker)
Trigger for analysis
On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time
< 3 sec
Regulatory
Certification
CE
Certified, Class IIa
, MDD
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
The ALND system detects the suspected locations by first performing pixel-based calculation of the probability that a nodule may be present over the whole image, and then applies a set threshold to display the suspected location to the user in the form of a circular region of interest (ROI).
Market
Market presence
On market since
12-2018
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription
Based on
Number of installations
Evidence
Evidence
Peer reviewed papers on performance
Deep Convolutional Neural Network–based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs
(read)
Non-peer reviewed papers on performance
Other relevant papers