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4 papers · 1 filter
"It depends": Configuring AI to Improve Clinical Usefulness Across Contexts
Hubert D. Zając, Jorge M. N. Ribeiro, Silvia Ingala +6
Artificial Intelligence (AI) repeatedly match or outperform radiologists in lab experiments. However, real-world implementations of radiological AI-based systems are found to provi…
A sensitivity analysis to quantify the impact of neuroimaging preprocessing strategies on subsequent statistical analyses
Brice Ozenne, Martin Norgaard, Cyril Pernet +1
Even though novel imaging techniques have been successful in studying brain structure and function, the measured biological signals are often contaminated by multiple sources of no…
Data harvesting vs data farming: A study of the importance of variation vs sample size in deep learning-based auto-segmentation for breast cancer patients
ES Buhl, E Maae, LW Matthiessen +7
The aim of this study was to investigate the difference in output, when training a model in three different scenarios: a large clinical delineated data set (with 700/78 patients fo…
Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI
Jon Middleton, Marko Bauer, Kaining Sheng +5
The identification and localisation of pathological tissues in medical images continues to command much attention among deep learning practitioners. When trained on abundant datase…