Characterization of Bone Tumors in Computed Tomography and in Magnetic Resonance Imaging by Machine Learning
Recruiting
- Conditions
- D48.9Neoplasm of uncertain or unknown behaviour, unspecified
- Registration Number
- DRKS00024574
- Lead Sponsor
- MU München
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- All
- Target Recruitment
- 2000
Inclusion Criteria
Patients in tumor orthopedics at the LMU with a clinical diagnosis of a bone tumor (malignant/benign) and corresponding radiological examinations as well as histopathological findings/clinical diagnoses
Exclusion Criteria
missing images (X-ray, MRI, CT)
lack of histopathological findings / clinical diagnosis
Study & Design
- Study Type
- observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Comparison of the sensitivity/specificity regarding the detected bone tumors by the artificial intelligence compared to the results of the histopathology. The results of the histopathology correspond to the reference standard.
- Secondary Outcome Measures
Name Time Method Comparison of sensitivity and specificity of radiology (resident, fellow, expert) versus artificial intelligence