Improving interdisciplinary communication when using PI-RADS v2.1
Dr. Robert McFarland shares his experience of using mint Lesion™ at his radiology practice in this brief interview. He talks about the challenges of…
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University Hospital Tübingen: Study shows prediction power of clinical and CT imaging biomarkers
A recent retrospective study [1] conducted by researchers at University Hospital Tuebingen focused on identifying imaging and clinical predictors of…
Recording of RSNA 2019 AI theater presentation | Power food for AI
At this year’s RSNA, Mint Medical presented its AI approach to the audience at the AI theater. Tobias Gottmann and Aditya Jayaram highlighted how…
Data-driven healthcare through FIHR®-enabled interoperability
Nowadays, it is not unusual for healthcare systems to use numerous clinical applications from different vendors. Most tend to prefer flexibility for…
mint Lesion radiomics leverage precision medicine
The benefits that texture analysis and radiomics have shown already, and the improved availability of large data sets led to an increased interest in…
Enhanced value of health data through Common Data Elements (CDE)
Today, it is generally agreed that standardized language used in radiology reports improves communication with the treatment team and patients, with a…
Potential of longitudinal data from single site and multi-center clinical trials for AI-research
Prof. Dr. Hans-Christoph Becker from Stanford University, a long-standing user of mint Lesion™, shares his experience of using the software in this…
Home of excellence for cancer care innovation
In a multidisciplinary center that networks medical research, natural sciences, engineering sciences, computer science and business administration, in…
Royal Marsden London: Study shows prediction power of CT-based 2D and 3D texture analysis for liver metastases
In a retrospective study [1], a team from Royal Marsden in London and Sutton explored changes of CT texture analysis metrics in unresectable liver…