Research at MIRA
Research at MIRA
MIRA aims to conduct world-leading research to improve diagnosis and treatment in cardiovascular disease and cancer and for monitoring during interventions, by harnessing the existing technical and clinical expertise, our access to large annotated medical image databases, and state-of-the-art methods in AI/machine learning.
- Muller S, Abildsnes H, Østvik A, Kragset O, Gangås I, Birke H, Langø T, Arum CJ. Can a Dinosaur Think? Implementation of Artificial Intelligence in Extracorporeal Shock Wave Lithotripsy. Eur Urol Open Sci. 2021 Mar 21;27:33-42. doi: 10.1016/j.euros.2021.02.007. PMID: 34337515
- Østvik A, Salte IM, Smistad E, Nguyen TM, Melichova D, Brunvand H, Haugaa K, Edvardsen T, Grenne B, Lovstakken L. Myocardial Function Imaging in Echocardiography Using Deep Learning, IEEE Trans Med Imaging, May 2021. DOI: 10.1109/TMI.2021.3054566
- Pedersen A, Valla M, Bofin AM, De Frutos JP, Reinertsen I, Smistad E, "FastPathology: An Open-Source Platform for Deep Learning-Based Research and Decision Support in Digital Pathology," in IEEE Access, vol. 9, pp. 58216-58229, 2021, doi: 10.1109/ACCESS.2021.3072231
- Nketiah GA, Elschot M, Scheenen TW, Maas MC, Bathen TF, Selnæs KM; PCa-MAP Consortium. Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study. Sci Rep. 2021 Jan 22;11(1):2085
- Sunoqrot MRS, Nketiah GA, Selnæs KM, Bathen TF, Elschot M. Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition. MAGMA. 2021 Apr;34(2):309-321