True Enhance DL

GE HealthCare
True Enhance DL Model Card
Product Details
Model Identifier
Manufacturer
GE HealthCare
Product
True Enhance DL
Version
Unknown
Date Cleared
04/11/2024
FDA Submission No.
Category
MIMPS
Model Characteristics
Inclusion Criteria
Monochromatic, 50 keV GSI images
Exclusion Criteria
Unknown
Instructions for Use
Not available
Indications for Use
Indication of Use
True Enhance DL is a deep learning-based image processing method trained to estimate monochromatic, 50 keV GSI images. The algorithm is intended to improve the contrast of 120 kVp, single energy images of the body. This device is intended to provide non-quantitative, adjunct information and should not be interpreted without the original 120 kVp image. True Enhance DL may be used for patients of all ages.
Intended User
Clinicians
Age
Adult and Pediatric
Anatomy
Whole Body
Modality
CT
Output
Estimate monochromatic, 50 keV GSI images
Details on Training Data Sets
Details on Training Data Sets
No. of Cases
Unknown
Age Range (Years)
Unknown
Sex (%)
  • Female: Unknown
  • Male: Unknown
  • Unknown: Unknown
Output
Unknown
Race (%)
  • White: Unknown
  • Black or African American: Unknown
  • American Indian or Alaska Native: Unknown
  • Asian: Unknown
  • Native Hawaiian or Other Pacific Islander: Unknown
  • Unknown: Unknown
Ethnicity (%)
  • Hispanic or Latino: Unknown
  • Not Hispanic or Latino: Unknown
  • Unknown: Unknown
Geographic Region (%)
  • USA: Unknown
  • International: Unknown
  • Unknown: Unknown
Scanner Manufacturer(s)
Unknown
Scanner Model(s)
Unknown
Model Performance
Study Type
Performance Testing Type
Reader Study
Standalone Model Performance
Reference Standard (Ground Truth)
N/A
No. of Cases
N/A
Age Range (Years)
N/A
Sex (%)
  • Female: N/A
  • Male: N/A
  • Unknown: N/A
Race (%)
  • White: N/A
  • Black or African American: N/A
  • American Indian or Alaska Native: N/A
  • Asian: N/A
  • Native Hawaiian or Other Pacific Islander: N/A
  • Unknown: N/A
Ethnicity (%)
  • Hispanic or Latino: N/A
  • Not Hispanic or Latino: N/A
  • Unknown: N/A
Geographic Region (%)
  • USA: N/A
  • International: N/A
  • Unknown: N/A
Output
N/A
Scanner Manufacturer(s)
N/A
Scanner Model(s)
N/A
No. of Sites
N/A
Model Accuracy
N/A
Model Sensitivity
N/A
Model Specificity
N/A
Reader Study Performance
No. of Readers
Unknown
No. of Cases
Unknown
No. of Sites
Unknown
Output
Unknown
Age Range (Years)
Unknown
Sex (%)
  • Female: Unknown
  • Male: Unknown
  • Unknown: Unknown
Race (%)
  • White: Unknown
  • Black or African American: Unknown
  • American Indian or Alaska Native: Unknown
  • Asian: Unknown
  • Native Hawaiian or Other Pacific Islander: Unknown
  • Unknown: Unknown
Ethnicity (%)
  • Hispanic or Latino: Unknown
  • Not Hispanic or Latino: Unknown
  • Unknown: Unknown
Geographic Region (%)
  • USA: Unknown
  • International: Unknown
  • Unknown: Unknown
Scanner Manufacturer(s)
Unknown
Scanner Model(s)
Unknown
Model Accuracy
Unknown
Model Sensitivity
Not provided
Model Specificity
Not provided
Model Limitations, Warnings, & Precautions
Model Limitations, Warnings, & Precautions
Supported Scanner Manufacturer(s)
Unknown
Slice Thickness
Unknown
Contrast Use
Unknown
MRI Field Strength
Unknown
Reconstruction Kernel Used
Unknown
Alternative Choices
Alternative Choices
Previous Version(s)
Unknown
Contact Information
Contact Information
Point of Contact Name
Unknown
Email
Unknown
Additional Details
Related Use Cases
Unknown
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