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Found 9 papers, 0 papers with code
Handling Label Uncertainty on the Example of Automatic Detection of Shepherd's Crook RCA in Coronary CT Angiography
If a patient exhibits a Shepherd's Crook (SC) Right Coronary Artery (RCA) - an anatomical norm variant of the coronary vasculature - the complexity of this procedure is increased.
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology
Deep learning (DL) shows notable success in biomedical studies.
DeepTechnome: Mitigating Unknown Bias in Deep Learning Based Assessment of CT Images
Reliably detecting diseases using relevant biological information is crucial for real-world applicability of deep learning techniques in medical imaging.
Building Brains: Subvolume Recombination for Data Augmentation in Large Vessel Occlusion Detection
The best configuration detects LVOs with an AUC of 0. 91, LVOs in the ICA with an AUC of 0. 96, and in the MCA with 0. 91 while accurately predicting the affected side.
An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes
In the work at hand, we place the algorithm in a clinical context by evaluating the labeling and occlusion detection on stroke patients, where we have achieved labeling sensitivities comparable to other works between 92\,\% and 95\,\%.
CAD-RADS Scoring using Deep Learning and Task-Specific Centerline Labeling
With coronary artery disease (CAD) persisting to be one of the leading causes of death worldwide, interest in supporting physicians with algorithms to speed up and improve diagnosis is high.
Detection of Large Vessel Occlusions using Deep Learning by Deforming Vessel Tree Segmentations
Training the EfficientNetB1 architecture on 100 data sets, the proposed augmentation scheme was able to raise the ROC AUC to 0. 85 from a baseline value of 0. 56 using no augmentation.
Explaining Clinical Decision Support Systems in Medical Imaging using Cycle-Consistent Activation Maximization
Clinical decision support using deep neural networks has become a topic of steadily growing interest.
Scale-Space Anisotropic Total Variation for Limited Angle Tomography
Hence, the main purpose of this paper is to reduce streak artifacts at various scales.
