Bone Scan
Conditions
Brief summary
Recently, artificial intelligence algorithms reducing noise by deep learning have been developed with application to SPECT and PET images. Many studies have reported the possibility of reducing the recording time in bone scintigraphy by applying artificial intelligence algorithms reducing noise
Detailed description
Only two studies compared images denoised by a Deep Learning algorithm to those denoised by conventional filters (Gaussian and median filters). The first study was conducted only on patients, without phantom analysis and without taking into account the size of the lesions. The second study included an analysis on phantom and patients, but with application to planar images rather than to SPECT images that are increasingly used today The hypothesis of our study conducted on phantom and patients is that an artificial intelligence algorithm reducing noise could replace the conventional filters usually used in bone SPECT for the denoising of scintigraphic images.
Interventions
to apply an artificial intelligence algorithm to treat the imaging
Sponsors
Central Hospital, Nancy, France
Study design
Observational model
OTHER
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 99 Years
Healthy volunteers
No
Inclusion criteria
Patients who had a whole-body thee dimensions bone scan for rheumatological or oncological indications.
Exclusion criteria
Patients opposed to the use of their data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| To compare imaging treated by the intelligence artificial algorithm with imaging treated with the traditionnal filter artificial algorithm | one day | Quantification value on imaging measured with intelligence artificial algorithm compared with quantification value measured with conventional filter |
Countries
France
Outcome results
None listed