machine-learning-algorithms-for-early-detection-bone-metastases-an

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine learning (ML) algorithms permit the integration of different features into a model to perform classification or regression tasks with an accuracy ...

Friedrich-Alexander Universität Erlangen-Nürnberg

Seven T ultra-high field MRI systems have recently been approved for clinical use by the U.S. and European regulatory agencies. These systems are now being used clinically and will likely be more widely available in the near future. One of the applications of 7 T systems is musculoskeletal disease and particularly peripheral arthritis imaging. Since the introduction of potent anti-rheumatic therapies over the last two decades MRI has gained increasing importance particularly for assessment of disease activity in early stages of several rheumatic disorders. Commonly gadolinium-based contrast agents are used for assessment of synovitis. Due to potential side-effects of gadolinium non-enhanced techniques are desirable that enable visualization of inflammatory disease manifestations. The feasibility of 7 T MRI for evaluation of peripheral arthritis has not been shown up to now. Aim of our study was to evaluate the feasibility of contrast-enhanced (CE) and non-enhanced MRI at 7 T for the assessment of knee joint synovitis.

Christoph Treutlein

Department of Radiology,
University Hospital Erlangen,
Department of Radiology, University Hospital Erlangen

Friedrich-Alexander Universität Erlangen-Nürnberg

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Christoph Treutlein

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Radiology,University Hospital Erlangen,Department of Radiology, University Hospital Erlangen

Friedrich-Alexander Universität Erlangen-Nürnberg

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Department of Radiology,
University Hospital Erlangen,
Department of Radiology, University Hospital Erlangen