1.3k citations · 2.1k across the 15 of their papers we have counts for
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How can we learn (more) from challenges? A statistical approach to driving future algorithm development
Tobias Roß, Pierangela Bruno, Annika Reinke +12
Challenges have become the state-of-the-art approach to benchmark image analysis algorithms in a comparative manner. While the validation on identical data sets was a great step fo…
Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis
Maximilian Dietrich, Silvia Seidlitz, Nicholas Schreck +16
Sepsis is a leading cause of mortality and critical illness worldwide. While robust biomarkers for early diagnosis are still missing, recent work indicates that hyperspectral imagi…
The Medical Segmentation Decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas +55
International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely inv…
Video-rate multispectral imaging in laparoscopic surgery: First-in-human application
Leonardo Ayala, Sebastian Wirkert, Anant Vemuri +6
Multispectral and hyperspectral imaging (MSI/HSI) can provide clinically relevant information on morphological and functional tissue properties. Application in the operating room (…