Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging.
Matheus Calil FaleirosMarcello Henrique Nogueira-BarbosaVitor Faeda DaltoJosé Raniery Ferreira JúniorAriane Priscilla Magalhães TenórioRodrigo Luppino-AssadPaulo Louzada-JuniorRangaraj Mandayam RangayyanPaulo Mazzoncini de Azevedo-MarquesPublished in: Advances in rheumatology (London, England) (2020)
Our results show the potential of machine learning methods to identify SIJ subchondral bone marrow edema in axSpA patients and are promising to aid in the detection of active inflammatory sacroiliitis on MRI STIR sequences. Multilayer Perceptron (MLP) achieved the best results.
Keyphrases
- machine learning
- magnetic resonance imaging
- bone marrow
- end stage renal disease
- artificial intelligence
- contrast enhanced
- oxidative stress
- ejection fraction
- deep learning
- newly diagnosed
- computed tomography
- mesenchymal stem cells
- prognostic factors
- peritoneal dialysis
- magnetic resonance
- diffusion weighted imaging
- patient reported outcomes
- real time pcr
- sensitive detection
- genetic diversity