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Update RSNA: Heart and Lung Imaging
Seminar in Radiological Diagnostics: "RSNA Update – Heart and Lung Imaging"
PET scans of torso with relevant false positives highlighted by red dotted circles, true positives in green
Representative prediction pitfalls in cases with high DSC
LMU University Hospital: Artificial Intelligence for TNM Staging in NSCLC – How Reliable Are AI-Based Segmentations?
The recent study “Artificial intelligence for TNM staging in NSCLC – a critical appraisal of segmentation utility in [¹⁸F]FDG PET/CT” provides a…
Research with mint mintLesion Clinical Research PET
Participants at the RECIST and Beyond workshop in Cologne during hands-on training with mint Lesion for structured tumor response assessment.
The two-day “RECIST and Beyond” workshop at radCIO Cologne offered intensive hands-on training on RECIST, iRECIST, mRECIST and LI-RADS, with real-case reporting performed directly in mint Lesion.
Successful “RECIST and Beyond” Workshop in Cologne: Advancing Precision in Oncologic Imaging
How can complex tumor findings be assessed accurately, reproducibly, and in line with clinical guidelines?
mintLesion Standardized Reading Procedures Clinical Routine HCC Structured Reporting
RSNA 2025
Annual Meeting of the Radiological Society of North America
Screenshot of the mint Lesion interface showing RANO 2.0 configuration, tumor burden calculations, and structured neuro-oncology assessment tools.
mint Lesion fully supports RANO 2.0 implementation with configurable parameters, automated tumor burden calculations, and structured workflows for neuro-oncology clinical trials.
Implementing RANO 2.0 for Neuro-Oncology Clinical Trials in mint Lesion
Tumor response assessment in neuro-oncology clinical trials requires careful attention to measurement protocols and confirmation scan requirements. To…
mintLesion Clinical Trials Neuro Structured Reporting
BioPharma Clinical Trials Nexus
24th BioPharma Clinical Trials Nexus
Interview with Prof. Timm Denecke about the RACOON-MARDER project and AI-powered early detection of liver cancer using MRI
An in-depth interview with Prof. Timm Denecke about the RACOON-MARDER project, which aims to predict hepatocellular carcinoma risk using MRI, AI, and clinical data.
“Making the Invisible Visible”: How RACOON-MARDER Aims to Improve Early Detection of Liver Cancer Using MRI and AI
Hepatocellular carcinoma (HCC) is a potentially deadly tumor. The decisive factor is the timing of diagnosis: if HCC is detected early, there is a…