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Found 5 papers, 4 papers with code
AeroPath: An airway segmentation benchmark dataset with challenging pathology
In this study, we introduce a new public benchmark dataset (AeroPath), consisting of 27 CT images from patients with pathologies ranging from emphysema to large tumors, with corresponding trachea and bronchi annotations.
AI-Dentify: Deep learning for proximal caries detection on bitewing x-ray -- HUNT4 Oral Health Study
Yet the use of artificial intelligence, and in particular deep-learning, has the potential to aid in the diagnosis by providing a quick and informative analysis of the bitewing images.
Learning deep abdominal CT registration through adaptive loss weighting and synthetic data generation
Conclusion: Using simple concepts, we improved the performance of a commonly used deep image registration architecture, VoxelMorph.
Teacher-Student Architecture for Mixed Supervised Lung Tumor Segmentation
Purpose: Automating tasks such as lung tumor localization and segmentation in radiological images can free valuable time for radiologists and other clinical personnel.
Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding
For the 1178 lymph nodes with a short-axis diameter $\geq10$ mm, our best performing approach reached a patient-wise recall of 92%, a false positive per patient ratio of 5, and a segmentation overlap of 80. 5%.
