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Automated Small Kidney Cancer Detection in Non-Contrast Computed Tomography
In the development of our pipeline, we test three detections models: a shape model, a 2D-, and a 3D axial-sample model.
Calibrating Ensembles for Scalable Uncertainty Quantification in Deep Learning-based Medical Segmentation
On the contrary, we propose a scalable and intuitive framework to calibrate ensembles of deep learning models to produce uncertainty quantification measurements that approximate the classification probability.
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