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Found 6 papers, 2 papers with code
Gadolinium dose reduction for brain MRI using conditional deep learning
Recently, deep learning (DL)-based methods have been proposed for the computational reduction of gadolinium-based contrast agents (GBCAs) to mitigate adverse side effects while preserving diagnostic value.
Multilingual Natural Language Processing Model for Radiology Reports -- The Summary is all you need!
In this study, the generation of radiology impressions in different languages was automated by fine-tuning a model, publicly available, based on a multilingual text-to-text Transformer to summarize findings available in English, Portuguese, and German radiology reports.
Towards Unifying Anatomy Segmentation: Automated Generation of a Full-body CT Dataset via Knowledge Aggregation and Anatomical Guidelines
We examine its plausibility and usefulness using three complementary checks: Human expert evaluation which approved the dataset, a Deep Learning usefulness benchmark on the BTCV dataset in which we achieve 85% dice score without using its training dataset, and medical validity checks.
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries
It is an open secret that ImageNet is treated as the panacea of pretraining.
Logion: Machine Learning for Greek Philology
This paper presents machine-learning methods to address various problems in Greek philology.
k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
Results: Both datasets were very similar to the ground truth (DICE scores of 92\%-98\% and Hausdorff distances of under 5. 5 mm).
