Deep Learning Image Reconstruction for Gemstone Spectral Imaging Overview

GE HealthCare
Deep Learning Image Reconstruction for Gemstone Spectral Imaging Overview Model Card
Product Details
Model Identifier
Manufacturer
GE HealthCare
Product
Deep Learning Image Reconstruction for Gemstone Spectral Imaging Overview
Version
Unknown
Date Cleared
12/10/2020
FDA Submission No.
Category
MIMPS
Model Characteristics
Inclusion Criteria
CT image
Exclusion Criteria
Unknown
Instructions for Use
Not available
Indications for Use
Indication of Use
The Deep Learning Image Reconstruction for Gemstone Spectral Imaging option is a deep learning based CT reconstruction method intended to produce cross-sectional images by computer reconstruction of dual energy X-ray transmission data acquired with Gemstone Spectral Imaging, for all ages. Deep Learning Image Reconstruction for Gemstone Spectral Imaging can be used for whole body, vascular, and contrast enhanced head CT applications.
Intended User
Unknown
Age
Adult and Pediatric
Anatomy
Whole Body
Modality
CT
Output
Image reconstruction
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
5
No. of Cases
47
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)
All
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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