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MIAAI Group Activities

MIAAI - Medical Image Analysis & Artificial Intelligence

The Medical Image Analysis and Artificial Intelligence (MIAAI) group at the DPU focuses on the analysis of medical imaging for the development of quantitative biomarkers, as well as the use of AI to predict the presence of disease, its progression or treatment response. Currently, it focuses on cancer and the prediction of prognosis and treatment response, but the group’s work can be applied to any area of medical imaging due to its versatility.

MIAAI (Medical Image Analysis & Artificial Intelligence) at Danube Private University in Austria

MIAAI Group Activities

Manual labelling of pathological changes on medical images (segmentation) is essential for many quantitative analyses as well as radiomics. This is usually performed by one or more specialised radiologists/clinicians, requires specialised knowledge and is very time-consuming. Although this type of segmentation is the gold standard, significant variability between different performing specialists has been demonstrated. To reduce time and variability, the development of automated segmentation methods using AI will also be a focus of the MIAAI research group. Fully automated segmentation and image analysis algorithms are a key element of smart medicine and are essential for standardising the methods mentioned. 

Radiomics features can be affected by variability of segmentations and different scanning techniques and image reconstruction methods. The lack of standardisation of radiomics features in different imaging modalities (MRI, CT, mammography, etc.) remains an unsolved problem. The MIAAI group is investigating the use of 3D printed phantoms to explore radiomics features and their robustness for different clinical applications and settings. The reproducibility and repeatability of many radiomics features are investigated using phantom and patient data to develop more robust radiomics predictors in the future.

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