Software Evaluation for Visualizing Anatomical Structures Not Typically Identified on Clinical MR Images
Conditions
Brief summary
SIS has developed a software technology, based on machine learning and image processing, designed to enhance standard clinical images for the visualization of anatomical structures.
Detailed description
A cohort of 34 subjects will be scanned on a clinical MRI scanner as well as on a 7 Tesla (7T) scanner. Images acquired on the 7T allow to visualize anatomical structures that are not easily identified on standard clinical images. SIS software will be used to visualize selected anatomical features on the clinical image and the results will be compared with the images in the same subject obtained from the 7T MRI.
Interventions
None listed
Sponsors
Surgical Information Sciences Inc.
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
Yes
Inclusion criteria
* All subjects that are willing to be scanned on a 3T and 7T MRI scanners and are not excluded by the
Exclusion criteria
below.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Validation of the accurate visualization of brain structure based on SIS algorithms - 1 | Through study completion, up to 1 year | Difference in distance between brain structure center of mass (COM) |
| Validation of the accurate visualization of brain structure based on SIS algorithms - 2 | Through study completion, up to 1 year | Difference in distance between brain structure mean surface area |
| Validation of the accurate visualization of brain structure based on SIS algorithms - 3 | Through study completion, up to 1 year | Difference in Dice Coefficient between measured brain structures |
Countries
United States
Outcome results
None listed